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+{
+  "task_id": "20cf0cb5-2cd4-49db-8dee-c2cf8e021bfc",
+  "job": "LITERATURE_HIGH",
+  "topic": "EDS standards for standards-based k-ratio quantification (Al/Si/Mg, 5 kV)",
+  "pr": 11
+}
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+# Standards-Based k-Ratio Quantification for Low-kV SEM-EDS of AlSi10Mg: A Comprehensive Technical Guide
+
+## 1. What Is an EDS Standard Spectrum, Informationally?
+
+An EDS standard spectrum is far more than an array of channel counts. For it to be usable in standards-based k-ratio quantification, a standard spectrum must be accompanied by a comprehensive set of metadata that documents the exact conditions under which it was acquired, so that the fundamental ratio k = I_unknown / I_standard is meaningful. The k-ratio protocol requires that unknown and standard be measured "under identical conditions of beam energy, known dose, and detector efficiency" (newbury2015performingelementalmicroanalysis pages 1-2). Specifically, the following metadata must be recorded and archived with each standard spectrum:
+
+**Instrumental parameters:** beam energy (accelerating voltage), probe current (measured with a Faraday cup and digital picoammeter for rigorous work), live time and real time (to calculate effective dose and dead time), and the EDS detector's process time/time constant (which must remain fixed—adaptive process time is explicitly discouraged for standards-based work) (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 14-15). The dead time should be kept below approximately 10% to minimize coincidence artifacts, which grow significantly above ~15% dead time (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 6-8).
+
+**Geometric parameters:** detector elevation (take-off) angle, detector azimuthal angle, specimen tilt (preferably zero), detector-to-specimen distance (which sets the solid angle), and the detector active area (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4).
+
+**Detector characterization:** window type and thickness (polymer/Moxtek AP3/AP5 vs. Be vs. windowless), support grid geometry and open area fraction (typically 76–80%), detector dead layer thickness, energy resolution (FWHM at Mn Kα, typically 122–150 eV for modern SDDs), and the energy calibration (zero offset and gain, typically 5 eV/channel) (tsuji2010xrayspectrometry. pages 9-10, goldstein2018energydispersivexray pages 14-15, goldstein2018energydispersivexray pages 15-16, goldstein2018energydispersivexray pages 18-20).
+
+**Standard material parameters:** the identity and known composition of the standard (whether certified by an independent method), its microscopic homogeneity (confirmed by EPMA), and its certification traceability (e.g., NIST SRM certificate) (newbury2019electronexcitedxraymicroanalysis pages 2-3). When pure elements are incompatible with vacuum or suffer oxidation/beam damage, stoichiometric compounds are substituted—e.g., MgO for Mg, KCl for K and Cl, FeS₂ for S, GaP for Ga and P, CaF₂ for Ca and F (newbury2015performingelementalmicroanalysis pages 1-2).
+
+**Sample condition parameters:** surface preparation state (highly polished, not chemically etched; surface roughness <50 nm rms for measurements of photons below 1 keV), coating material and thickness (typically ~8–10 nm carbon), and contamination/oxidation/tarnish state (newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 9-11, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4).
+
+**Administrative parameters:** date and time of acquisition, operator, and instrument identifier (newbury2015performingelementalmicroanalysis pages 11-13).
+
+**The EMSA/MAS .msa format (ISO 22029)** is the standardized spectrum data file format for microbeam analysis, originally defined by Fiori, Swyt, and others and adopted as ISO 22029 "Microbeam Analysis – EMSA/MAS Standard File Format for Spectral-Data Exchange" (dumit2025challengesandfuture pages 9-10). Its required keywords include `#FORMAT`, `#VERSION`, `#TITLE`, `#DATE`, `#TIME`, `#OWNER`, `#NPOINTS`, `#NCOLUMNS`, `#XUNITS`, `#YUNITS`, `#DATATYPE`, `#XPERCHAN`, `#OFFSET`, `#SIGNALTYPE`, and `#SPECTRUM`. Optional but analytically critical keywords include `#BEAMKV`, `#PROBECUR`, `#LIVETIME`, `#REALTIME`, `#ELEVANGLE`, `#AZIMANGLE`, and `#XTILTSTGE`/`#YTILTSTGE`. Notably, the classic EMSA/MAS keyword set does not include dedicated fields for detector window type, dead layer thickness, incomplete charge collection parameters, or FWHM at Mn Kα—these must be recorded in comment fields or external documentation. Scott, Wight, and Thorne (2002, Microsc. Microanal. 8:646–647) proposed extending the format to XML-based "EMSA/MAS 2.0," but the original ASCII format remains dominant.
+
+The following table summarizes the complete metadata requirements:
+
+| Metadata Parameter | Description/Purpose | EMSA/MAS Keyword (where applicable) |
+|---|---|---|
+| Beam energy / accelerating voltage | Required because k-ratios are valid only when unknown and standard are measured under the same excitation conditions; changes ionization cross-sections, overvoltage, depth of generation, and matrix corrections. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 1-2, goldstein2018quantitativeanalysisthe pages 1-4) | `#BEAMKV` |
+| Probe current | Needed to document electron dose and to verify reproducibility/linearity of X-ray intensity; rigorous k-ratio work should measure current with a Faraday cup/picoammeter. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 18-20, goldstein2018quantitativeanalysisthe pages 6-8) | `#PROBECUR` |
+| Live time | Dose in EDS is probe current × live time; live time, not real time, determines effective dose because dead time removes useful counts. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 16-18, goldstein2018energydispersivexray pages 18-20) | `#LIVETIME` |
+| Real time / dead time | Important to assess pulse pile-up/coincidence and detector operating regime; Newbury & Ritchie recommend conservative operation around ~10% dead time for standards-based work, especially when weak peaks sit near coincidence/tail artifacts. (newbury2015performingelementalmicroanalysis pages 20-21, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 18-20, goldstein2018quantitativeanalysisthe pages 6-8) | `#REALTIME`, `#DEADTIME` |
+| Detector elevation / take-off angle | Required geometric parameter for absorption correction; should match between unknown and standard and be verified physically if necessary. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, goldstein2018energydispersivexray pages 14-15) | often `#ELEVANGLE` or vendor-specific |
+| Detector azimuth angle | Needed because detector orientation changes X-ray path length and effective efficiency; should be fixed and recorded for reusable standards. (newbury2015performingelementalmicroanalysis pages 11-13) | often vendor-specific / not always standardized |
+| Specimen tilt | Changes take-off geometry and absorption; Goldstein/Newbury specify tilt should be controlled, preferably zero for bulk standards unless intentionally used. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4) | often `#XTILTSTGE`, `#YTILTSTGE` or vendor-specific |
+| Detector-to-specimen distance / working distance | Sets solid angle and count rate; must be reproducible between standard and unknown. Off-axis position also changes apparent low-energy efficiency because of window-grid/trap shadowing. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, goldstein2018energydispersivexray pages 15-16) | often `#WORKING`, `#DISTANCE` or vendor-specific |
+| Detector active area / solid angle | Needed to interpret count rate and portability of archived spectra; different detector geometries change throughput and sensitivity. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 9-11) | usually not in classic MSA core keywords; vendor-specific |
+| Detector window type and thickness | Critical below ~2 keV because polymer/SiN vs Be windows transmit low-energy X-rays very differently; affects Mg K, Al K, O K, etc. (tsuji2010xrayspectrometry. pages 9-10, ritchie2018exploringthelimits pages 1-4, tong2026measurementuncertaintiesof pages 8-11, goldstein2018energydispersivexray pages 15-16) | usually vendor-specific / not a required classic MSA keyword |
+| Window support grid / electron trap details | Off-axis shadowing and low-energy attenuation can change intensity and background, especially for light elements. (goldstein2018energydispersivexray pages 15-16) | vendor-specific |
+| Detector dead layer / front contact / Si absorption characteristics | Needed when comparing detectors or simulating spectra because fluorescence in dead layer, escape peaks, and efficiency roll-off alter low-energy response. (tsuji2010xrayspectrometry. pages 9-10, goldstein2018energydispersivexray pages 1-2) | vendor-specific |
+| Detector response function / incomplete charge collection behavior | Essential for fitting trace peaks under tails; low-energy tailing and peak-shape differences are detector-specific and limit transferability of standard spectra. (tsuji2010xrayspectrometry. pages 9-10, newbury2011isscanningelectron pages 13-16, giunto2025harnessingautomatedsemeds pages 4-6) | not represented in classic MSA keyword set |
+| Energy calibration zero offset | Required so standard and unknown spectra align channel-for-channel for integrated-peak k-ratios and peak fitting. (goldstein2018quantitativeanalysisthe pages 1-4, goldstein2018energydispersivexray pages 18-20) | `#OFFSET` |
+| Energy calibration gain / channel width | Required to define energy-per-channel; Goldstein recommends fixed channel width (e.g., 5 eV/channel) and consistent calibration. (goldstein2018quantitativeanalysisthe pages 1-4, goldstein2018energydispersivexray pages 18-20) | `#XPERCHAN`, sometimes paired with `#OFFSET` |
+| Number of channels / energy range | Needed to reconstruct spectrum and assure same fitting range; spectra should span low-energy region through the Duane–Hunt limit. (goldstein2018quantitativeanalysisthe pages 1-4, goldstein2018energydispersivexray pages 18-20) | `#NPOINTS`, `#XUNITS` |
+| Energy resolution / FWHM at Mn Kα | Peak overlap sensitivity depends on detector resolution; should be documented because different FWHM values change deconvolution and low-energy tail contributions. (goldstein2018energydispersivexray pages 14-15, ritchie2018exploringthelimits pages 1-4, goldstein2018energydispersivexray pages 1-2) | often `#MNFWHM` or vendor-specific |
+| Process time / shaping time / time constant | Must be fixed; adaptive process time is specifically discouraged for standards-based quantification because it changes peak shape and resolution. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 14-15) | often `#TIMECNST` or vendor-specific |
+| Count total / integrated counts | High-count spectra are needed for robust MLLS fitting and trace-level overlap correction; archive the total counts or dose associated with the standard. (newbury2015performingelementalmicroanalysis pages 20-21, newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 17-20) | `#DATATYPE` with counts array; total counts often derived or vendor-specific |
+| Standard identity | The material used as the standard must be named explicitly so composition, homogeneity, and suitability can be checked. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2, newbury2019electronexcitedxraymicroanalysis pages 5-6, newbury2024testingtheaccuracy pages 1-3) | `#SAMPLE` |
+| Standard composition | Required because k-ratio denominator must correspond to a known concentration in the standard. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2, newbury2019electronexcitedxraymicroanalysis pages 5-6, newbury2024testingtheaccuracy pages 1-3) | no single core keyword; usually comment/header text |
+| Certification / traceability | For rigorous work, the standard composition should be certified or independently established and microscopically homogeneous. (newbury2015performingelementalmicroanalysis pages 2-4, newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2024testingtheaccuracy pages 1-3) | usually comment/header text |
+| Date/time of acquisition | Needed for traceability, detector stability checks, and QA of archived reusable standards. (newbury2015performingelementalmicroanalysis pages 11-13) | `#DATE`, `#TIME` |
+| Operator / instrument identifier | Supports QA and cross-checking of archived standards; important when spectra are reused. (newbury2015performingelementalmicroanalysis pages 11-13) | `#OWNER`, `#TITLE`, vendor-specific instrument fields |
+| Specimen surface preparation state | Surface roughness/topography directly affects low-energy X-rays; for photons below ~1 keV surfaces should be extremely flat, and standards/unknowns should be prepared similarly. (newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4) | usually comment/header text |
+| Coating material and thickness | Carbon or metal coatings absorb low-energy X-rays; mismatch between standard and unknown coatings can cause significant error at low kV. (newbury2015performingelementalmicroanalysis pages 9-11, newbury2015performingelementalmicroanalysis pages 11-13, newbury2024testingtheaccuracy pages 22-24) | usually comment/header text |
+| Contamination / oxidation / tarnish state | Surface films create composite specimens and strongly bias low-energy analysis; should be documented, especially for reactive standards like Mg-bearing materials. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2024testingtheaccuracy pages 22-24) | usually comment/header text |
+| Vacuum / chamber conditions | Useful for assessing contamination growth and detector performance stability during acquisition. (newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2024testingtheaccuracy pages 22-24) | vendor-specific |
+| Peak-family / line selection used for quantification | EDS often quantifies whole line families rather than a single line; the selected family must be known to interpret k-ratios and matrix corrections. (newbury2015performingelementalmicroanalysis pages 1-2, ritchie2018exploringthelimits pages 4-5) | usually analysis metadata, not core MSA |
+| Background/fit model or peak-shape reference linkage | Particularly valuable for trace-overlap cases, because usability of a stored standard also depends on the associated peak-shape references and fitting strategy. (ritchie2018exploringthelimits pages 4-5, newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9) | not in classic MSA core; DTSA-II/project metadata |
+| QA status / same-conditions verification | Archived standards are reusable only if a QA protocol confirms the unknown was measured under the same beam energy, dose, and EDS parameters. (newbury2015performingelementalmicroanalysis pages 11-13) | not a classic MSA keyword; external QA record |
+
+
+*Table: This table summarizes the metadata that must accompany an EDS standard spectrum for rigorous standards-based k-ratio quantification. It combines the practical requirements emphasized by Goldstein/Newbury/Ritchie with the fields typically represented in the EMSA/MAS .msa format and notes where classic MSA keywords are incomplete for modern detector-response details.*
+
+## 2. Are Standard Spectra Transferable Between Instruments?
+
+**The short answer is: generally no, not without significant correction, especially for low-energy lines below ~2 keV.**
+
+The fundamental problem is that the k-ratio protocol requires that unknown and standard spectra be acquired under identical conditions. The stability of modern SDD-EDS detectors permits reuse of previously measured, stored standard spectra on the *same* instrument, provided a quality-assurance protocol confirms that the unknown was measured under the same documented conditions (beam energy, dose, and EDS parameters) (newbury2015performingelementalmicroanalysis pages 11-13). SDDs show nearly constant resolution and calibration across a wide range of input count rates, which enables practical spectrum archiving on a given instrument (newbury2015performingelementalmicroanalysis pages 9-11).
+
+However, cross-instrument transfer faces several detector-specific barriers:
+
+**Resolution differences:** Different SDDs have different FWHM values (typically 122–150 eV at Mn Kα), which change peak shapes and the extent of tails under adjacent peaks—directly relevant to the Al Kα tail under Mg Kα in your case (ritchie2018exploringthelimits pages 1-4, goldstein2018energydispersivexray pages 1-2, goldstein2018energydispersivexray pages 14-15).
+
+**Window transmission:** The choice of window material (polymer/SiN vs. Be vs. windowless) dramatically affects transmission below ~2 keV. Moxtek AP3 and AP5 windows have different thicknesses (380 µm vs. 265 µm ribs), rib widths, and acceptance angles, creating different low-energy efficiencies (goldstein2018energydispersivexray pages 15-16). Be windows absorb essentially all X-rays below ~1 keV, making spectra taken with Be-window detectors incomparable to those from polymer-window detectors for light-element lines (tong2026measurementuncertaintiesof pages 8-11).
+
+**Silicon dead layer and incomplete charge collection (ICC):** Scholze and Procop modeled the EDS spectral response accounting for statistical and electronic noise, ICC (which causes peak tailing on the low-energy side), escape effects, and fluorescence from the front contact/dead layer (tsuji2010xrayspectrometry. pages 9-10). These processes are detector-specific and alter both peak shapes and the continuum particularly at low energies. The ICC tailing is the precise artifact creating your Al Kα tail under Mg Kα.
+
+**Published "standards transfer" methodologies:** Newbury and Ritchie describe a "remote standards standardless" approach in which a library of standard measurements made on another instrument supplies standard intensities, with calculated corrections applied for beam energy and spectrometer efficiency differences. However, they note that no dose calibration is attempted in this approach, so the raw analytical total has no validity and normalization is required—thereby removing important diagnostic indicators of geometric or other deviations (newbury2011isscanningelectron pages 13-16). Newbury and Ritchie (2019) also reference a "golden detector" calibration-transfer technique (from Alvisi et al., 2006), in which a detector calibrated at a synchrotron beamline is used with a carefully chosen reference material to transfer the calibration to other instruments—an approach they note is inherently more accurate than purely first-principles standardless methods (newbury2019electronexcitedxraymicroanalysis pages 16-18).
+
+**Quantitative accuracy penalty:** When comparing measured and DTSA-II simulated spectra for bulk K411 at 20 keV (a surrogate for cross-instrument transfer using a modeled detector response), Newbury and Ritchie found discrepancies ranging from +1.2% for Fe Kα to +19% for Mg K, with the low-energy region showing systematically larger deviations (newbury2011isscanningelectron pages 13-16). This +19% discrepancy for Mg K specifically underscores the severity of the problem for your Mg Kα / Al Kα overlap situation.
+
+**Practical recommendation:** For your specific case (trace Mg Kα at 1.254 keV under the tail of the dominant Al Kα at 1.487 keV), standard spectra should be acquired on your own EDAX Octane Plus SDD on your Apreo SEM under the same conditions as your unknowns. Cross-instrument transfer of standards is not recommended for this challenging low-energy overlap problem.
+
+## 3. Simulated / Synthetic Standards
+
+NIST DTSA-II includes built-in spectrum simulation tools (based on NISTMonte, a Monte Carlo electron trajectory simulator) that can generate synthetic standard spectra from first-principles physics to yield absolute intensities (newbury2011isscanningelectron pages 13-16). The simulation models electron scattering, X-ray generation, self-absorption, secondary fluorescence, and the detector response function.
+
+**Published accuracy assessments:**
+
+When Newbury and Ritchie (2015) used DTSA-II simulated standards to analyze NIST microanalysis glass K2496 at 10 keV, the resulting concentrations were very close to the as-synthesized values, with RDEV values of approximately −1.0% to +1.7% for the constituent elements and precision metrics of ~0.08–1.8% relative (newbury2015performingelementalmicroanalysis pages 20-21). This demonstrates that simulated standards can provide accurate quantification for moderate-to-high-energy X-ray lines in well-controlled measurements.
+
+However, for bulk K411 at 20 keV, a direct comparison of measured and simulated spectra (without scaling) showed discrepancies of +1.2% for Fe Kα up to +19% for Mg K (newbury2011isscanningelectron pages 13-16). The systematically larger error at low photon energies (Mg K at 1.254 keV) reflects the difficulty of accurately modeling the detector response—particularly ICC, dead layer absorption, and window transmission effects—in the sub-2 keV energy range.
+
+**Where simulated standards are acceptable:** Simulated standards are most useful when a flat, bulk reference of the desired composition is unavailable—for example, when analyzing irregularly shaped particles or microstructural features. DTSA-II can simulate a bulk reference spectrum from an estimated composition, with a first normalized analysis serving as that estimate (newbury2011isscanningelectron pages 13-16). For higher-energy lines (>2 keV) and well-characterized detector parameters, simulated standards can approach the accuracy of measured standards.
+
+**Where simulated standards specifically fail:** The simulation's accuracy critically depends on the fidelity of the detector response model. Key failure modes include:
+- **Low-energy peak tailing and ICC:** The incomplete charge collection process, which creates low-energy tails on peaks, is detector-specific and difficult to parameterize accurately from first principles. Giunto et al. (2025) note that detector artifacts "particularly below 2 keV" complicate background fitting and quantification (giunto2025harnessingautomatedsemeds pages 4-6).
+- **Contamination layers and surface effects:** Real specimens accumulate carbon contamination and may have oxidation layers; these are not included in the simulation but strongly affect low-energy X-ray intensities (newbury2024testingtheaccuracy pages 22-24).
+- **Absorption edge structure:** The continuum under characteristic peaks contains absorption edge structures that are broadened by the detector function; at higher beam energies, the peak fitting residuals show non-physical zero-intensity regions, indicating modeling limitations (newbury2024testingtheaccuracy pages 22-24).
+
+**For your specific case:** A simulated Al standard would not accurately reproduce the ICC tail that extends from Al Kα into the Mg Kα region on your specific Octane Plus detector. This tail is the dominant suspected source of your Mg over-estimation, and it is highly detector-specific. A measured Al standard acquired on your own detector is essential to characterize this tail empirically.
+
+## 4. Where to Obtain Physical Standards for Al, Si, and Mg
+
+The following table provides a comprehensive listing of standards suppliers and CRMs relevant to your Al-Si-Mg system:
+
+| Supplier/Source | Product/CRM | Catalogue/SRM Number | Elements/Composition | Notes |
+|---|---|---|---|---|
+| NIST | Glass for microanalysis, K411 | SRM 470 K411 | O-Mg-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; useful as a multi-element glass containing Mg and Si. (newbury2024testingtheaccuracy pages 1-3) |
+| NIST | Glass for microanalysis, K412 | SRM 470 K412 | O-Mg-Al-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; directly relevant to Al-Mg-Si calibration and overlap studies. (newbury2024testingtheaccuracy pages 1-3) |
+| NIST | Gold-silver alloy set | SRM 481 | Au-Ag alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study as a certified alloy series suitable for microanalysis challenge specimens and standards work. (newbury2024testingtheaccuracy pages 1-3) |
+| NIST | Gold-copper alloy set | SRM 482 | Au-Cu alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study; Newbury & Ritchie also discuss spectra of SRM 482 at multiple beam energies. (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 22-24) |
+| NIST | Stainless steel CRM | SRM 479 | Fe-Cr-Ni stainless steel | Explicitly listed in the 5 kV study among NIST microanalysis challenge materials. (newbury2024testingtheaccuracy pages 1-3) |
+| NIST | Transformer steel CRM | SRM 483 | Fe-3Si steel | Mentioned by Newbury & Ritchie 2019 as an EPMA/EDS reference material in quantitative work. (newbury2019electronexcitedxraymicroanalysis pages 5-6) |
+| NIST | Thin-film microanalysis SRM | SRM 2063a | Thin film; composition not verified here | Relevant NIST microanalysis SRM class, but exact composition/details were not verified in the retrieved sources; include only after checking the current NIST certificate. |
+| NIST | K-glass / oxide glass series | SRM 1871, 1872, 1873, 1875 | SRM 1871 K456: O-Si-Pb; SRM 1872 K453: O-Ge-Pb; SRM 1873 K458: O-Si-Zn-Ba; SRM 1875 K496: O-Mg-Al-P | Explicitly listed in the 5 kV study as microanalysis-qualified SRMs. SRM 1875 is especially relevant because it contains Mg and Al. (newbury2024testingtheaccuracy pages 1-3) |
+| Geller MicroAnalytical Laboratory (Topsfield, MA, USA) | Stoichiometric binary compounds prepared for microanalysis | Vendor product line; specific catalogue IDs not verified here | MgO, Al2O3, SiO2, TiN, TiO2, Cr2N, etc. | Explicitly named by Newbury & Ritchie 2024 as a source of stoichiometric compounds with surfaces prepared for microanalysis. Recommended route for MgO, Al2O3, SiO2 standards. (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 14-16) |
+| SPI Supplies (West Chester, PA, USA) | Mineral standards / well-characterized minerals | Vendor product line; specific catalogue IDs not verified here | Minerals such as calcite, dolomite, fluorapatite, wollastonite, zircon; user-requested examples periclase/forsterite/spinel should be checked in current catalog | Explicitly named by Newbury & Ritchie 2024 as a source of minerals of known composition and micro-homogeneity used in the challenge set. (newbury2024testingtheaccuracy pages 1-3) |
+| Astimex Standards Ltd (Toronto, Canada) | Mounted pure-element and compound microanalysis standards | Vendor product line; specific catalogue IDs not verified here | Pure Al, Si, alloys, oxides, silicates, custom mounts | Common EPMA/SEM-EDS supplier, but specific products were not verified in the retrieved literature; check current catalog for Al, Si, Mg-bearing mounts before purchase. |
+| Ted Pella, Inc. | Microanalysis standards and mounts | Vendor product line; specific catalogue IDs not verified here | Pure elements, compounds, calibration mounts | Widely used supplier, but no product-specific verification in retrieved sources; confirm current catalog details. |
+| Micro-Analysis Consultants (MAC), St Ives, UK | Mineral and synthetic EPMA standards | Vendor product line; specific catalogue IDs not verified here | Silicates, oxides, sulfides, synthetic compounds | Common EPMA standards source, but exact catalog entries were not verified in retrieved sources. |
+| P&H Developments | Electron microprobe standards | Vendor product line; specific catalogue IDs not verified here | Mineral and synthetic standards | Named by user request; no product-specific verification found in retrieved sources, so verify directly with supplier. |
+| Alfa Aesar (now Thermo Fisher chemicals) | Reagent compounds | Reagent-grade products; specific catalogue IDs not verified here | BaTiO3, PbS, MoS2 and other compounds | Explicitly named by Newbury & Ritchie 2024 as source of reagent compounds used as challenge specimens; reagent grade is not automatically a microanalysis standard, so homogeneity/prep must be checked. (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 14-16) |
+| Smithsonian microbeam standards collection | Mineral reference materials | Collection-level resource; no single catalogue number | Mineral standards, including Mg-bearing silicates/carbonates depending on collection | Valuable institutional standards resource, but not documented in the retrieved contexts; verify access and material list directly with Smithsonian microbeam facility. |
+| Recommended Mg standard chemistry | MgO (periclase chemistry) | Not a single catalog number | Mg and O | Newbury & Ritchie’s 5 kV study repeatedly used MgO as the Mg standard; their standards table maps Mg to MgO at 5 kV. This is the best-supported Mg standard in the retrieved sources. (newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18) |
+| Recommended Al standard chemistry | Al2O3 | Not a single catalog number | Al and O | In the 5 kV study, Al was standardized with Al2O3 in the standards table; practical if oxide standards are already in the block. (newbury2024testingtheaccuracy pages 14-16) |
+| Recommended Si standard chemistry | SiO2 or pure Si | Not a single catalog number | Si and O, or Si | The 5 kV study shows SiO2 used as a Si standard in multiple entries; Newbury & Ritchie also note that pure Si can be used among pure-element standards. (newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18) |
+| Caution on pure Mg metal | Pure Mg metal | Not recommended as first-choice standard for routine low-kV SEM-EDS | Mg metal, rapidly oxidizing surface | Not directly evaluated in the retrieved papers, but the literature retrieved strongly supports substitution with MgO; this is consistent with the practical oxidation/contamination problem for Mg metal and the repeated use of stoichiometric compounds when pure elements are unstable. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2, newbury2024testingtheaccuracy pages 16-18) |
+
+
+*Table: This table summarizes physical standards sources and certified reference materials relevant to Al, Si, and Mg SEM-EDS/EPMA work, emphasizing items explicitly documented in the Newbury & Ritchie 2024 5 kV study. It distinguishes directly verified standards from commonly used suppliers whose current catalogue details should still be checked before procurement.*
+
+**Standards used in the Newbury & Ritchie 2024 study at 5 keV:** At E₀ = 5 keV, their Table 1 explicitly documents the use of **MgO** as the standard for Mg, **Al₂O₃** for Al, and **SiO₂** (or pure Si) for Si (newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18). Their materials sources included NIST SRMs (SRM 470 K411/K412, SRM 479, SRM 481, SRM 482, SRM 1871–1875 series), minerals from SPI Supplies (West Chester, PA), stoichiometric compounds from Geller MicroAnalytical Laboratory (Topsfield, MA), and reagent compounds from Alfa Aesar (newbury2024testingtheaccuracy pages 1-3).
+
+**On pure Mg metal as a standard:** Newbury and Ritchie consistently use MgO rather than pure Mg metal for their Mg standard (newbury2015performingelementalmicroanalysis pages 1-2, newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18). The general principle stated is that when pure elements are "incompatible with vacuum or suffer electron-beam damage," stoichiometric compounds are substituted (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2). Pure Mg metal oxidizes rapidly, forming a surface MgO layer that grows under the electron beam and in ambient air; this creates a composite specimen that violates the homogeneity assumption of the k-ratio protocol. The EPMA community conventionally uses MgO (periclase), MgAl₂O₄ (spinel), Mg₂SiO₄ (forsterite), or CaMg(CO₃)₂ (dolomite) as Mg standards, with MgO being the simplest and most widely used.
+
+**Specific additional suppliers (not directly verified in the retrieved literature but well-established in the EPMA community):**
+- **Astimex Standards Ltd** (Toronto, Canada): Supplies mounted pure-element and compound standard blocks commonly used in EPMA laboratories.
+- **Micro-Analysis Consultants (MAC)** (St. Ives, UK): Supplies mineral and synthetic microanalysis standards.
+- **Ted Pella, Inc.**: Distributes microanalysis standards and specimen preparation supplies.
+- **P&H Developments**: Supplies EPMA standard materials.
+- **Smithsonian microbeam standards collection**: Curated mineral standards used by the Smithsonian Institution's microbeam facility and distributed to the community.
+
+*Note: Specific catalogue identifiers for Astimex, MAC, Ted Pella, and P&H Developments were not verified in the retrieved literature and should be confirmed with the vendors' current catalogues.*
+
+## 5. Public Repositories of EDS/EPMA Spectra
+
+**NIST DTSA-II internal standards database:** The DTSA-II software distribution (freely available from NIST at https://www.nist.gov/services-resources/software/nist-dtsa-ii) includes a built-in standards/k-ratio database. This database contains reference data for standard spectra and compositions used in the k-ratio quantification engine. However, these are primarily used as the software's internal reference framework for matrix corrections rather than as a downloadable library of measured spectra transferable to other instruments (newbury2011isscanningelectron pages 13-16, newbury2019electronexcitedxraymicroanalysis pages 16-18).
+
+**EMSA/MAS format (ISO 22029):** The standard data exchange format for microbeam analysis spectra is the EMSA/MAS .msa ASCII format, now codified as ISO 22029 (dumit2025challengesandfuture pages 9-10). This format is supported by DTSA-II and most vendor software for import/export of EDS spectra.
+
+**Key limitation on transferability of archived spectra:** Even when spectra are available in .msa format from repositories or community resources, they are generally usable only as **reference/identification spectra** (for qualitative comparison and peak identification) rather than as quantification standards on a different instrument. This is because the spectra encode the detector-specific response function (resolution, tailing, efficiency) of the instrument on which they were acquired (tsuji2010xrayspectrometry. pages 9-10, ritchie2018exploringthelimits pages 1-4, newbury2011isscanningelectron pages 13-16). Newbury and Ritchie's "remote standards" approach can partially address this limitation by applying corrections for spectrometer efficiency differences, but the raw analytical total loses validity and normalization is required (newbury2011isscanningelectron pages 13-16).
+
+**Other resources:**
+- **de-ma.ch web database** (Allaz, 2024, Microsc. Microanal. 30:489–500): A web database for electron and X-ray microanalysis to assist lab managers and users. The detailed contents were not fully verified in the retrieved literature.
+- **NEXL** (Ritchie, 2022, Microsc. Microanal. 28:478–495): Ritchie's reproducible spectrum and hyperspectrum data analysis framework using a defined data format.
+- **University of Oregon CAMCOR**: Maintains standard block documentation that can serve as a community reference but is not a downloadable spectral library.
+- **Zenodo/Figshare deposits**: Individual researchers occasionally deposit EDS datasets; these should be evaluated case-by-case for usability as quantification standards.
+
+**Practical conclusion:** No large, publicly downloadable library of measured EDS standard spectra exists that would be directly usable as quantification standards on an arbitrary instrument. The most reliable path remains acquiring your own standards on your own detector.
+
+## 6. The Specific Low-kV Case: 5 kV Mg Kα in an Al-Rich Matrix
+
+**The analytical challenge:** At 5 kV, Mg Kα (1.254 keV) and Al Kα (1.487 keV) are separated by only ~233 eV. With a typical SDD FWHM of ~55–65 eV at these energies, the peaks are nominally resolved, but the Al Kα peak—which is enormously intense in an 84+ wt% Al matrix—generates a low-energy tail due to incomplete charge collection that extends beneath the much smaller Mg Kα peak. Your measured Mg concentration (0.9–1.6 wt% vs. specification 0.20–0.45 wt%) represents a 2–4× overestimate that is entirely consistent with inadequate characterization of this Al Kα low-energy tail artifact in a standardless quantification framework.
+
+**Accuracy demonstrated at 5 keV with the k-ratio protocol:** Newbury and Ritchie (2024) systematically tested accuracy at E₀ = 5 keV using NIST DTSA-II with the standards-based k-ratio protocol, making 263 concentration measurements for 39 elements in 113 materials. More than 98% of their results fell within ±5% RDEV, and 82% fell within ±2% RDEV (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 18-22). This demonstrates that high-accuracy quantification at 5 keV is achievable with proper standards and protocol. Their analytical platform was a JEOL 8500f with a Bruker Quad SDD array (newbury2024testingtheaccuracy pages 4-6, newbury2024testingtheaccuracy pages 1-3).
+
+**Standards selection for Al, Si, Mg at 5 keV:** In the 5 keV study, MgO was used as the Mg standard, Al₂O₃ as the Al standard, and SiO₂ as the Si standard (newbury2024testingtheaccuracy pages 14-16). These compound standards avoid the surface oxidation problem of pure Mg metal and provide reliable, reproducible compositions.
+
+**Practical recommendations for your measurement:**
+
+1. **Acquire a measured Al standard spectrum on your own detector.** This is the single most important step to characterize the detector-specific Al Kα low-energy tail under Mg Kα. The Al standard spectrum (pure Al metal or Al₂O₃) serves as both a quantification standard and a peak-shape reference for the MLLS fitting in DTSA-II (ritchie2018exploringthelimits pages 4-5, newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9). In DTSA-II, this is accomplished by setting up a "Standard Bundle" that combines the standard spectrum with peak-shape references (ritchie2018exploringthelimits pages 4-5).
+
+2. **Consider acquiring a "blank" spectrum from pure Al** (or an Al-Si binary alloy with no Mg) specifically to characterize and subtract the Al Kα tail contribution under the Mg Kα region. This provides an empirical characterization of the ICC tailing on your specific Octane Plus detector. The peak fitting residual spectrum after fitting Al should show whether any counts remain in the Mg Kα region (newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9).
+
+3. **Collect high-count spectra.** For trace-level Mg (0.2–0.45 wt% is in the minor/trace boundary), long acquisition times are needed to improve counting statistics and detection limits. Detection limits scale as C_DL = [3 × N_B^(1/2) / (N_S − N_B)] × C_S, and practical LODs can reach ~200–500 ppm with sufficient counts (newbury2019electronexcitedxraymicroanalysis pages 13-15). Total spectrum counts of 3–10 million (0.1–5 keV range) were typical in the Newbury & Ritchie 5 keV study (newbury2024testingtheaccuracy pages 4-6, newbury2024testingtheaccuracy pages 1-3).
+
+4. **Use conservative dead time (~10%).** At 5 kV in an Al-rich matrix, the Al Kα peak will be extremely intense. Coincidence peaks (Al+Al at ~2.97 keV, Al+Si, etc.) become significant above ~10–15% dead time and can distort the continuum shape in the fitting region. Choose beam current to keep dead time below 10% on the most highly excited standard (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 6-8).
+
+5. **Surface preparation is critical.** At 5 kV, the electron range is very short (~200–300 nm in Al), so surface roughness, oxidation, and carbon contamination have a proportionally larger effect. Surface roughness should be <50 nm rms for measurements of photon energies below 1 keV, and the same preparation/coating protocol must be applied to both standards and unknowns (newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4). Carbon coatings should be ~8–10 nm and matched between standard and unknown; mismatched coating thickness introduces significant error at low beam energies (newbury2015performingelementalmicroanalysis pages 9-11).
+
+6. **Inspect the peak fitting residual spectrum.** After fitting Al and Si peaks, inspect the residual spectrum in the Mg Kα region to verify whether a genuine Mg peak remains above the fitted background, and whether the residual shows any systematic structure indicating inadequate tail modeling (newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9).
+
+7. **The raw analytical total is diagnostic.** When using the k-ratio protocol (not normalized), the raw analytical total should fall near 1.00 (typically 0.98–1.02 at conventional beam energies). At 5 keV, a broader range of 0.8–1.2 is observed even for carefully vetted materials (newbury2024testingtheaccuracy pages 18-22, newbury2024testingtheaccuracy pages 22-24). A total significantly deviating from unity signals potential problems (missing elements, surface layers, or fitting artifacts).
+
+8. **Verify with a known Mg-bearing reference material.** Analyze NIST SRM 470 K412 glass (which contains Mg, Al, Si, Ca, Fe, and O) at 5 keV to validate your Mg measurement against the certified composition before analyzing the AlSi10Mg alloy. This serves as an independent accuracy check for the specific Al-Mg overlap situation on your instrument.
+
+**Root cause of your Mg overestimate:** In standardless quantification, the vendor's built-in peak model may not accurately represent the ICC tail of Al Kα on your specific Octane Plus detector, leading to systematic misattribution of Al Kα tail counts to the Mg Kα channel. Switching to standards-based k-ratio quantification with DTSA-II, using a measured Al standard from your own detector as both standard and peak-shape reference, should dramatically reduce this systematic error by empirically capturing the actual detector response (newbury2011isscanningelectron pages 13-16, newbury2019electronexcitedxraymicroanalysis pages 16-18).
diff --git a/outputs/eds-standards/artifact-00-artifact-00.md b/outputs/eds-standards/artifact-00-artifact-00.md
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+| Metadata Parameter | Description/Purpose | EMSA/MAS Keyword (where applicable) |
+|---|---|---|
+| Beam energy / accelerating voltage | Required because k-ratios are valid only when unknown and standard are measured under the same excitation conditions; changes ionization cross-sections, overvoltage, depth of generation, and matrix corrections. (pqac-00000000, pqac-00000002, pqac-00000005, pqac-00000022) | `#BEAMKV` |
+| Probe current | Needed to document electron dose and to verify reproducibility/linearity of X-ray intensity; rigorous k-ratio work should measure current with a Faraday cup/picoammeter. (pqac-00000000, pqac-00000013, pqac-00000035, pqac-00000046) | `#PROBECUR` |
+| Live time | Dose in EDS is probe current × live time; live time, not real time, determines effective dose because dead time removes useful counts. (pqac-00000000, pqac-00000013, pqac-00000025, pqac-00000035) | `#LIVETIME` |
+| Real time / dead time | Important to assess pulse pile-up/coincidence and detector operating regime; Newbury & Ritchie recommend conservative operation around ~10% dead time for standards-based work, especially when weak peaks sit near coincidence/tail artifacts. (pqac-00000006, pqac-00000013, pqac-00000035, pqac-00000046) | `#REALTIME`, `#DEADTIME` |
+| Detector elevation / take-off angle | Required geometric parameter for absorption correction; should match between unknown and standard and be verified physically if necessary. (pqac-00000000, pqac-00000002, pqac-00000013, pqac-00000026) | often `#ELEVANGLE` or vendor-specific |
+| Detector azimuth angle | Needed because detector orientation changes X-ray path length and effective efficiency; should be fixed and recorded for reusable standards. (pqac-00000000, pqac-00000013) | often vendor-specific / not always standardized |
+| Specimen tilt | Changes take-off geometry and absorption; Goldstein/Newbury specify tilt should be controlled, preferably zero for bulk standards unless intentionally used. (pqac-00000000, pqac-00000013, pqac-00000022) | often `#XTILTSTGE`, `#YTILTSTGE` or vendor-specific |
+| Detector-to-specimen distance / working distance | Sets solid angle and count rate; must be reproducible between standard and unknown. Off-axis position also changes apparent low-energy efficiency because of window-grid/trap shadowing. (pqac-00000000, pqac-00000002, pqac-00000027) | often `#WORKING`, `#DISTANCE` or vendor-specific |
+| Detector active area / solid angle | Needed to interpret count rate and portability of archived spectra; different detector geometries change throughput and sensitivity. (pqac-00000000, pqac-00000002, pqac-00000015) | usually not in classic MSA core keywords; vendor-specific |
+| Detector window type and thickness | Critical below ~2 keV because polymer/SiN vs Be windows transmit low-energy X-rays very differently; affects Mg K, Al K, O K, etc. (pqac-00000009, pqac-00000010, pqac-00000019, pqac-00000027) | usually vendor-specific / not a required classic MSA keyword |
+| Window support grid / electron trap details | Off-axis shadowing and low-energy attenuation can change intensity and background, especially for light elements. (pqac-00000027) | vendor-specific |
+| Detector dead layer / front contact / Si absorption characteristics | Needed when comparing detectors or simulating spectra because fluorescence in dead layer, escape peaks, and efficiency roll-off alter low-energy response. (pqac-00000009, pqac-00000011) | vendor-specific |
+| Detector response function / incomplete charge collection behavior | Essential for fitting trace peaks under tails; low-energy tailing and peak-shape differences are detector-specific and limit transferability of standard spectra. (pqac-00000009, pqac-00000012, pqac-00000037) | not represented in classic MSA keyword set |
+| Energy calibration zero offset | Required so standard and unknown spectra align channel-for-channel for integrated-peak k-ratios and peak fitting. (pqac-00000022, pqac-00000035) | `#OFFSET` |
+| Energy calibration gain / channel width | Required to define energy-per-channel; Goldstein recommends fixed channel width (e.g., 5 eV/channel) and consistent calibration. (pqac-00000022, pqac-00000035) | `#XPERCHAN`, sometimes paired with `#OFFSET` |
+| Number of channels / energy range | Needed to reconstruct spectrum and assure same fitting range; spectra should span low-energy region through the Duane–Hunt limit. (pqac-00000022, pqac-00000035) | `#NPOINTS`, `#XUNITS` |
+| Energy resolution / FWHM at Mn Kα | Peak overlap sensitivity depends on detector resolution; should be documented because different FWHM values change deconvolution and low-energy tail contributions. (pqac-00000026, pqac-00000010, pqac-00000011) | often `#MNFWHM` or vendor-specific |
+| Process time / shaping time / time constant | Must be fixed; adaptive process time is specifically discouraged for standards-based quantification because it changes peak shape and resolution. (pqac-00000000, pqac-00000013, pqac-00000026) | often `#TIMECNST` or vendor-specific |
+| Count total / integrated counts | High-count spectra are needed for robust MLLS fitting and trace-level overlap correction; archive the total counts or dose associated with the standard. (pqac-00000006, pqac-00000007, pqac-00000017) | `#DATATYPE` with counts array; total counts often derived or vendor-specific |
+| Standard identity | The material used as the standard must be named explicitly so composition, homogeneity, and suitability can be checked. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | `#SAMPLE` |
+| Standard composition | Required because k-ratio denominator must correspond to a known concentration in the standard. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | no single core keyword; usually comment/header text |
+| Certification / traceability | For rigorous work, the standard composition should be certified or independently established and microscopically homogeneous. (pqac-00000002, pqac-00000003, pqac-00000042) | usually comment/header text |
+| Date/time of acquisition | Needed for traceability, detector stability checks, and QA of archived reusable standards. (pqac-00000000, pqac-00000013) | `#DATE`, `#TIME` |
+| Operator / instrument identifier | Supports QA and cross-checking of archived standards; important when spectra are reused. (pqac-00000013) | `#OWNER`, `#TITLE`, vendor-specific instrument fields |
+| Specimen surface preparation state | Surface roughness/topography directly affects low-energy X-rays; for photons below ~1 keV surfaces should be extremely flat, and standards/unknowns should be prepared similarly. (pqac-00000002, pqac-00000007, pqac-00000022) | usually comment/header text |
+| Coating material and thickness | Carbon or metal coatings absorb low-energy X-rays; mismatch between standard and unknown coatings can cause significant error at low kV. (pqac-00000004, pqac-00000007, pqac-00000034) | usually comment/header text |
+| Contamination / oxidation / tarnish state | Surface films create composite specimens and strongly bias low-energy analysis; should be documented, especially for reactive standards like Mg-bearing materials. (pqac-00000003, pqac-00000018, pqac-00000034) | usually comment/header text |
+| Vacuum / chamber conditions | Useful for assessing contamination growth and detector performance stability during acquisition. (pqac-00000018, pqac-00000034) | vendor-specific |
+| Peak-family / line selection used for quantification | EDS often quantifies whole line families rather than a single line; the selected family must be known to interpret k-ratios and matrix corrections. (pqac-00000005, pqac-00000016, pqac-00000024) | usually analysis metadata, not core MSA |
+| Background/fit model or peak-shape reference linkage | Particularly valuable for trace-overlap cases, because usability of a stored standard also depends on the associated peak-shape references and fitting strategy. (pqac-00000016, pqac-00000017, pqac-00000023) | not in classic MSA core; DTSA-II/project metadata |
+| QA status / same-conditions verification | Archived standards are reusable only if a QA protocol confirms the unknown was measured under the same beam energy, dose, and EDS parameters. (pqac-00000000, pqac-00000013) | not a classic MSA keyword; external QA record |
+
+
+*Table: This table summarizes the metadata that must accompany an EDS standard spectrum for rigorous standards-based k-ratio quantification. It combines the practical requirements emphasized by Goldstein/Newbury/Ritchie with the fields typically represented in the EMSA/MAS .msa format and notes where classic MSA keywords are incomplete for modern detector-response details.*
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+| Supplier/Source | Product/CRM | Catalogue/SRM Number | Elements/Composition | Notes |
+|---|---|---|---|---|
+| NIST | Glass for microanalysis, K411 | SRM 470 K411 | O-Mg-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; useful as a multi-element glass containing Mg and Si. (pqac-00000031, pqac-00000042) |
+| NIST | Glass for microanalysis, K412 | SRM 470 K412 | O-Mg-Al-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; directly relevant to Al-Mg-Si calibration and overlap studies. (pqac-00000031, pqac-00000042) |
+| NIST | Gold-silver alloy set | SRM 481 | Au-Ag alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study as a certified alloy series suitable for microanalysis challenge specimens and standards work. (pqac-00000031, pqac-00000042) |
+| NIST | Gold-copper alloy set | SRM 482 | Au-Cu alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study; Newbury & Ritchie also discuss spectra of SRM 482 at multiple beam energies. (pqac-00000031, pqac-00000034, pqac-00000042) |
+| NIST | Stainless steel CRM | SRM 479 | Fe-Cr-Ni stainless steel | Explicitly listed in the 5 kV study among NIST microanalysis challenge materials. (pqac-00000031, pqac-00000042) |
+| NIST | Transformer steel CRM | SRM 483 | Fe-3Si steel | Mentioned by Newbury & Ritchie 2019 as an EPMA/EDS reference material in quantitative work. (pqac-00000039) |
+| NIST | Thin-film microanalysis SRM | SRM 2063a | Thin film; composition not verified here | Relevant NIST microanalysis SRM class, but exact composition/details were not verified in the retrieved sources; include only after checking the current NIST certificate. |
+| NIST | K-glass / oxide glass series | SRM 1871, 1872, 1873, 1875 | SRM 1871 K456: O-Si-Pb; SRM 1872 K453: O-Ge-Pb; SRM 1873 K458: O-Si-Zn-Ba; SRM 1875 K496: O-Mg-Al-P | Explicitly listed in the 5 kV study as microanalysis-qualified SRMs. SRM 1875 is especially relevant because it contains Mg and Al. (pqac-00000031, pqac-00000042) |
+| Geller MicroAnalytical Laboratory (Topsfield, MA, USA) | Stoichiometric binary compounds prepared for microanalysis | Vendor product line; specific catalogue IDs not verified here | MgO, Al2O3, SiO2, TiN, TiO2, Cr2N, etc. | Explicitly named by Newbury & Ritchie 2024 as a source of stoichiometric compounds with surfaces prepared for microanalysis. Recommended route for MgO, Al2O3, SiO2 standards. (pqac-00000031, pqac-00000040) |
+| SPI Supplies (West Chester, PA, USA) | Mineral standards / well-characterized minerals | Vendor product line; specific catalogue IDs not verified here | Minerals such as calcite, dolomite, fluorapatite, wollastonite, zircon; user-requested examples periclase/forsterite/spinel should be checked in current catalog | Explicitly named by Newbury & Ritchie 2024 as a source of minerals of known composition and micro-homogeneity used in the challenge set. (pqac-00000031, pqac-00000042) |
+| Astimex Standards Ltd (Toronto, Canada) | Mounted pure-element and compound microanalysis standards | Vendor product line; specific catalogue IDs not verified here | Pure Al, Si, alloys, oxides, silicates, custom mounts | Common EPMA/SEM-EDS supplier, but specific products were not verified in the retrieved literature; check current catalog for Al, Si, Mg-bearing mounts before purchase. |
+| Ted Pella, Inc. | Microanalysis standards and mounts | Vendor product line; specific catalogue IDs not verified here | Pure elements, compounds, calibration mounts | Widely used supplier, but no product-specific verification in retrieved sources; confirm current catalog details. |
+| Micro-Analysis Consultants (MAC), St Ives, UK | Mineral and synthetic EPMA standards | Vendor product line; specific catalogue IDs not verified here | Silicates, oxides, sulfides, synthetic compounds | Common EPMA standards source, but exact catalog entries were not verified in retrieved sources. |
+| P&H Developments | Electron microprobe standards | Vendor product line; specific catalogue IDs not verified here | Mineral and synthetic standards | Named by user request; no product-specific verification found in retrieved sources, so verify directly with supplier. |
+| Alfa Aesar (now Thermo Fisher chemicals) | Reagent compounds | Reagent-grade products; specific catalogue IDs not verified here | BaTiO3, PbS, MoS2 and other compounds | Explicitly named by Newbury & Ritchie 2024 as source of reagent compounds used as challenge specimens; reagent grade is not automatically a microanalysis standard, so homogeneity/prep must be checked. (pqac-00000031, pqac-00000040) |
+| Smithsonian microbeam standards collection | Mineral reference materials | Collection-level resource; no single catalogue number | Mineral standards, including Mg-bearing silicates/carbonates depending on collection | Valuable institutional standards resource, but not documented in the retrieved contexts; verify access and material list directly with Smithsonian microbeam facility. |
+| Recommended Mg standard chemistry | MgO (periclase chemistry) | Not a single catalog number | Mg and O | Newbury & Ritchie’s 5 kV study repeatedly used MgO as the Mg standard; their standards table maps Mg to MgO at 5 kV. This is the best-supported Mg standard in the retrieved sources. (pqac-00000040, pqac-00000041, pqac-00000043) |
+| Recommended Al standard chemistry | Al2O3 | Not a single catalog number | Al and O | In the 5 kV study, Al was standardized with Al2O3 in the standards table; practical if oxide standards are already in the block. (pqac-00000040, pqac-00000041) |
+| Recommended Si standard chemistry | SiO2 or pure Si | Not a single catalog number | Si and O, or Si | The 5 kV study shows SiO2 used as a Si standard in multiple entries; Newbury & Ritchie also note that pure Si can be used among pure-element standards. (pqac-00000040, pqac-00000041, pqac-00000043) |
+| Caution on pure Mg metal | Pure Mg metal | Not recommended as first-choice standard for routine low-kV SEM-EDS | Mg metal, rapidly oxidizing surface | Not directly evaluated in the retrieved papers, but the literature retrieved strongly supports substitution with MgO; this is consistent with the practical oxidation/contamination problem for Mg metal and the repeated use of stoichiometric compounds when pure elements are unstable. (pqac-00000003, pqac-00000005, pqac-00000043) |
+
+
+*Table: This table summarizes physical standards sources and certified reference materials relevant to Al, Si, and Mg SEM-EDS/EPMA work, emphasizing items explicitly documented in the Newbury & Ritchie 2024 5 kV study. It distinguishes directly verified standards from commonly used suppliers whose current catalogue details should still be checked before procurement.*
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+1. (newbury2015performingelementalmicroanalysis pages 1-2): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.
+
+2. (newbury2015performingelementalmicroanalysis pages 11-13): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.
+
+3. (goldstein2018energydispersivexray pages 14-15): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_16, doi:10.1007/978-1-4939-6676-9\_16. This article has 33 citations.
+
+4. (goldstein2018quantitativeanalysisthe pages 6-8): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_20, doi:10.1007/978-1-4939-6676-9\_20. This article has 9 citations.
+
+5. (newbury2015performingelementalmicroanalysis pages 2-4): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.
+
+6. (tsuji2010xrayspectrometry. pages 9-10): Kouichi Tsuji, Kazuhiko Nakano, Yoshio Takahashi, Kouichi Hayashi, and Chul-Un Ro. X-ray spectrometry. Analytical chemistry, 82 12:4950-87, May 2010. URL: https://doi.org/10.1021/ac101069d, doi:10.1021/ac101069d. This article has 78 citations and is from a highest quality peer-reviewed journal.
+
+7. (goldstein2018energydispersivexray pages 15-16): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_16, doi:10.1007/978-1-4939-6676-9\_16. This article has 33 citations.
+
+8. (goldstein2018energydispersivexray pages 18-20): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_16, doi:10.1007/978-1-4939-6676-9\_16. This article has 33 citations.
+
+9. (newbury2019electronexcitedxraymicroanalysis pages 2-3): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.
+
+10. (newbury2015performingelementalmicroanalysis pages 9-11): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.
+
+11. (goldstein2018quantitativeanalysisthe pages 1-4): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_20, doi:10.1007/978-1-4939-6676-9\_20. This article has 9 citations.
+
+12. (dumit2025challengesandfuture pages 9-10): Verónica I. Dumit, Irini Furxhi, Penny Nymark, Antreas Afantitis, Ammar Ammar, Monica J. B. Amorim, Dalila Antunes, Svetlana Avramova, Chiara L. Battistelli, Gianpietro Basei, Cecilia Bossa, Emil Cimpan, Mihaela Roxana Cimpan, Dmitri Ciornii, Anna Costa, Camilla Delpivo, Maria Dusinska, Ana Sofia Fonseca, Steffi Friedrichs, Vasile‐Dan Hodoroaba, Danail Hristozov, Panagiotis Isigonis, Nina Jeliazkova, Nikolay Kochev, Eva Kranjc, Dieter Maier, Georgia Melagraki, Anastasios G. Papadiamantis, Tomasz Puzyn, Hubert Rauscher, Katie Reilly, Araceli Sánchez Jiménez, Janeck J. Scott‐Fordsmand, Neeraj Shandilya, Hyun Kil Shin, Gergana Tancheva, Jeaphianne P. M. van Rijn, Egon L. Willighagen, Ewelina Wyrzykowska, Martine I. Bakker, Damjana Drobne, Thomas E. Exner, Martin Himly, and Iseult Lynch. Challenges and future directions in assessing the quality and completeness of advanced materials safety data for re‐usability: a position paper from the nanosafety community. Advanced Sustainable Systems, Dec 2026. URL: https://doi.org/10.1002/adsu.202500567, doi:10.1002/adsu.202500567. This article has 2 citations and is from a peer-reviewed journal.
+
+13. (goldstein2018energydispersivexray pages 16-18): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_16, doi:10.1007/978-1-4939-6676-9\_16. This article has 33 citations.
+
+14. (newbury2015performingelementalmicroanalysis pages 20-21): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.
+
+15. (ritchie2018exploringthelimits pages 1-4): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.
+
+16. (tong2026measurementuncertaintiesof pages 8-11): V. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.
+
+17. (goldstein2018energydispersivexray pages 1-2): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_16, doi:10.1007/978-1-4939-6676-9\_16. This article has 33 citations.
+
+18. (newbury2011isscanningelectron pages 13-16): Dale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.
+
+19. (giunto2025harnessingautomatedsemeds pages 4-6): Andrea Giunto, Yuxing Fei, Pragnay Nevatia, Bernardus Rendy, Nathan Szymanski, and Gerbrand Ceder. Harnessing automated sem-eds and machine learning to unlock high-throughput compositional characterization of powder materials. Unknown journal, Oct 2025. URL: https://doi.org/10.21203/rs.3.rs-7837297/v1, doi:10.21203/rs.3.rs-7837297/v1.
+
+20. (newbury2015performingelementalmicroanalysis pages 17-20): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.
+
+21. (newbury2019electronexcitedxraymicroanalysis pages 5-6): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.
+
+22. (newbury2024testingtheaccuracy pages 1-3): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.
+
+23. (newbury2024testingtheaccuracy pages 22-24): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.
+
+24. (newbury2019electronexcitedxraymicroanalysis pages 13-15): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.
+
+25. (ritchie2018exploringthelimits pages 4-5): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.
+
+26. (newbury2015performingelementalmicroanalysis pages 7-9): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.
+
+27. (newbury2019electronexcitedxraymicroanalysis pages 16-18): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.
+
+28. (newbury2024testingtheaccuracy pages 14-16): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.
+
+29. (newbury2024testingtheaccuracy pages 16-18): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.
+
+30. (newbury2024testingtheaccuracy pages 18-22): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.
+
+31. (newbury2024testingtheaccuracy pages 4-6): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.
\ No newline at end of file
diff --git a/outputs/eds-standards/task_response_verbose.json b/outputs/eds-standards/task_response_verbose.json
new file mode 100644
index 0000000..8a6cb3c
--- /dev/null
+++ b/outputs/eds-standards/task_response_verbose.json
@@ -0,0 +1,10734 @@
+{
+  "status": "success",
+  "query": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
+  "user": null,
+  "created_at": "2026-08-21T20:40:01.053495Z",
+  "job_name": "job-futurehouse-paperqa3-high",
+  "share_status": "private",
+  "permitted_accessors": {
+    "users": [],
+    "organizations": []
+  },
+  "build_owner": "FutureHouse",
+  "environment_name": null,
+  "agent_name": null,
+  "task_id": "20cf0cb5-2cd4-49db-8dee-c2cf8e021bfc",
+  "project_id": null,
+  "agent_state": [
+    {
+      "id": "479c9bc7-7a43-4998-bae7-f9553eff0621",
+      "trajectory_id": "20cf0cb5-2cd4-49db-8dee-c2cf8e021bfc",
+      "trajectory_timestep": 20,
+      "step": "after_transition",
+      "state": {
+        "transition": {
+          "timestep": 20,
+          "agent_state": {
+            "tools": [
+              {
+                "type": "function",
+                "info": {
+                  "name": "read_text",
+                  "description": "Given a list of text names, read their contents.\n\nThis tool is valuable to read the full contents of specific parts of documents,\ncomplementing the `gather_evidence` tool's indirect approach.\nThis can be an especially useful tool if `gather_evidence` does not find evidence,\nbut you think it is very likely that specific documents are still relevant to the question.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "text_name_list": {
+                        "description": "A list of up to 10 text names to read.\nThese text names can be any valid text names retrieved by other tools.",
+                        "items": {
+                          "type": "string"
+                        },
+                        "title": "Text Name List",
+                        "type": "array"
+                      }
+                    },
+                    "required": [
+                      "text_name_list"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "clinical_trials_search",
+                  "description": "Search for clinical trials, with support for repeated calls and concurrent execution.\n\nWill add new clinical trials to the state, and return metadata about the number of trials found.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "The search query string. Supports complex boolean expressions, field-specific\nsearches, and query modifiers through operators. All configuration is done through\noperators in the query string.\nQuery Syntax:\n    Basic Search:\n        Simple text automatically uses default EXPANSION[Relaxation] and COVERAGE[Contains]\n        >>> \"heart attack\"\n\n    Modified Search:\n        Use operators to modify search behavior:\n        >>> 'EXPANSION[None]COVERAGE[FullMatch]\"exact phrase\"'\n        >>> 'EXPANSION[Concept]heart attack'\n\n    Field Search:\n        Specify fields using AREA operator:\n        >>> 'AREA[InterventionName]aspirin'\n        >>> 'AREA[Phase]PHASE3'\n\n    Location Search:\n        Use SEARCH operator for compound location queries:\n        >>> 'cancer AND SEARCH[Location](AREA[LocationCity]Boston AND AREA[LocationState]Massachusetts)'\n\n    Complex Boolean:\n        Combine terms with AND, OR, NOT and parentheses:\n        >>> '(cancer OR tumor) AND NOT (EXPANSION[None]pediatric OR AREA[StdAge]CHILD)'\n\n    Date Ranges:\n        Use RANGE to specify date ranges with formats like \"yyyy-MM\" or \"yyyy-MM-dd\".\n        Note that MIN and MAX can be used for open-ended ranges:\n        >>> AREA[ResultsFirstPostDate]RANGE[2015-01-01, MAX]\n\nOperators:\n    EXPANSION[type]: Controls term expansion\n        - None: Exact match only, case and accent sensitive\n        - Term: Includes lexical variants (plurals, spellings)\n        - Concept: Includes UMLS synonyms\n        - Relaxation: Relaxes adjacency requirements (default)\n        - Lossy: Allows missing partial terms\n\n    COVERAGE[type]: Controls text matching\n        - FullMatch: Must match entire field\n        - StartsWith: Must match beginning of field\n        - EndsWith: Must match end of field\n        - Contains: Must match part of field (default)\n\n    AREA[field]: Specifies field to search\n        - See Field Reference for available fields\n\n    SEARCH[type]: Groups field searches\n        - Location: Groups location-related fields\n        - Study: Groups study-related fields\n\nUsage Notes:\n    - All search expressions are implicitly OR expressions\n    - Operator precedence (highest to lowest): terms/source operators, NOT/context operators, AND, OR\n    - Use quotes for exact phrase matching: \"heart attack\"\n    - Use parentheses for grouping: (heart OR cardiac) AND attack\n    - Use backslash to escape operators: \\AND\n    - Default expansion is EXPANSION[Relaxation]\n    - Default coverage is COVERAGE[Contains]\n\nField Reference:\n    High Priority Fields (weight >= 0.8):\n        - NCTId (1.0): Trial identifier\n        - Acronym (1.0): Study acronym\n        - BriefTitle (0.89): Short title\n        - OfficialTitle (0.85): Full official title\n        - Condition (0.81): Medical condition\n        - InterventionName (0.8): Primary intervention name\n        - OverallStatus: Trial status\n\n    Medium Priority Fields (0.5-0.79):\n        - InterventionOtherName (0.75): Alternative intervention names\n        - Phase (0.65): Trial phase\n        - StdAge (0.65): Standard age groups\n        - Keyword (0.6): Study keywords\n        - BriefSummary (0.6): Short description\n        - SecondaryOutcomeMeasure (0.5): Secondary outcomes\n\n    Low Priority Fields (< 0.5):\n        - DesignPrimaryPurpose (0.3): Primary purpose of study\n        - StudyType (0.3)\n        - Various descriptive, location, and administrative fields\n\nSupported Enums:\n    Phase:\n        - EARLY_PHASE1: Early Phase 1\n        - PHASE1: Phase 1\n        - PHASE2: Phase 2\n        - PHASE3: Phase 3\n        - PHASE4: Phase 4\n        - NA: Not Applicable\n\n    StandardAge:\n        - CHILD: Child\n        - ADULT: Adult\n        - OLDER_ADULT: Older Adult\n\n    Status:\n        - RECRUITING: Currently recruiting participants\n        - ACTIVE_NOT_RECRUITING: Active but not recruiting\n        - COMPLETED: Study completed\n        - ENROLLING_BY_INVITATION: Enrolling by invitation only\n        - NOT_YET_RECRUITING: Not yet recruiting\n        - SUSPENDED: Study suspended\n        - TERMINATED: Study terminated\n        - WITHDRAWN: Study withdrawn\n        - AVAILABLE: Available\n        - NO_LONGER_AVAILABLE: No longer available\n        - TEMPORARILY_NOT_AVAILABLE: Temporarily not available\n        - APPROVED_FOR_MARKETING: Approved for marketing\n        - WITHHELD: Withheld\n        - UNKNOWN: Unknown status\n\n    StudyType:\n        - INTERVENTIONAL: Interventional studies\n        - OBSERVATIONAL: Observational studies\n        - EXPANDED_ACCESS: Expanded access studies\n\n    PrimaryPurpose:\n        - TREATMENT: Treatment\n        - PREVENTION: Prevention\n        - DIAGNOSTIC: Diagnostic\n        - ECT: Educational/Counseling/Training\n        - SUPPORTIVE_CARE: Supportive Care\n        - SCREENING: Screening\n        - HEALTH_SERVICES_RESEARCH: Health Services Research\n        - BASIC_SCIENCE: Basic Science\n        - DEVICE_FEASIBILITY: Device Feasibility\n        - OTHER: Other\n\n    InterventionType:\n        - BEHAVIORAL: Behavioral interventions\n        - BIOLOGICAL: Biological interventions\n        - COMBINATION_PRODUCT: Combination product interventions\n        - DEVICE: Device interventions\n        - DIAGNOSTIC_TEST: Diagnostic test interventions\n        - DIETARY_SUPPLEMENT: Dietary supplement interventions\n        - DRUG: Drug interventions\n        - GENETIC: Genetic interventions\n        - PROCEDURE: Procedure interventions\n        - RADIATION: Radiation interventions\n        - OTHER: Other interventions\n\n    DesignAllocation:\n        - RANDOMIZED: Randomized allocation\n        - NON_RANDOMIZED: Non-randomized allocation\n        - NA: Not applicable\n\n    InterventionalAssignment:\n        - SINGLE_GROUP: Single group assignment\n        - PARALLEL: Parallel assignment\n        - CROSSOVER: Crossover assignment\n        - FACTORIAL: Factorial assignment\n        - SEQUENTIAL: Sequential assignment\n\n    ObservationalModel:\n        - COHORT: Cohort\n        - CASE_CONTROL: Case-Control\n        - CASE_ONLY: Case-Only\n        - CASE_CROSSOVER: Case-Crossover\n        - ECOLOGIC_OR_COMMUNITY: Ecologic or Community\n        - FAMILY_BASED: Family-Based\n        - DEFINED_POPULATION: Defined Population\n        - NATURAL_HISTORY: Natural History\n        - OTHER: Other\n\n    DesignMasking:\n        - NONE: None (Open Label)\n        - SINGLE: Single\n        - DOUBLE: Double\n        - TRIPLE: Triple\n        - QUADRUPLE: Quadruple\n\n    WhoMasked:\n        - PARTICIPANT: Participant\n        - CARE_PROVIDER: Care Provider\n        - INVESTIGATOR: Investigator\n        - OUTCOMES_ASSESSOR: Outcomes Assessor",
+                        "title": "Query",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "create_plan",
+                  "description": "Create a plan for to construct a thorough and accurate answer.\n\nDecompose the input task into a set of sub-objectives that need to\nbe met in order to form the answer. Subsequently, when working on solving\nthe query, you can focus on these objectives one by one. Note that the\n`update_plan` tool allows you to change the objectives if needed.\n\nIn addition to the objectives you deem necessary, add one final objective\nto call the `answer` tool with your final answer, so that you do not\nforget to submit your answer.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "plan_json": {
+                        "description": "A JSON string representing the plan. It should be a dictionary\nwith top-level key \"objectives\", whose value is a list of objectives.\nEach objective should be a dictionary with the following keys:\n- \"id\": (int) an integer id for the plan objective\n- \"objective\": (str) a human readable description of the objective's goal\n- \"rationale\": (str) a human readable rationale\n    describing why this objective is necessary and appropriate for the query.\n- \"status\": (str) updated task status, default to pending,\n    one of: pending, in-progress, or completed.\n    \"pending\" is yet to be started,\n    \"in-progress\" is the current objective being solved,\n    \"completed\" is successfully completed with acceptance criteria met.\n- \"result\": (str|None) The result of the objective, default to None.\n- \"evaluation\": (str|None) Description of why the objective result\n    meets the criteria for being complete. Default to None.",
+                        "title": "Plan Json",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "plan_json"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "view_images",
+                  "description": "Retrieve images from a document.\n\nUse this tool when you need to see figures, tables, or other visual content.\nThe tool works by asking a weaker LLM agent to scan through the document, looking for\nvisual content matching the query you provide. When the agent finds matches, it will\ncrop the page to the relevant region. It can be tasked to return multiple images,\nif desired. Note that the weaker LLM may be worse at *understanding* images than\nyou, so double-check its conclusions about the returned images. It is also stateless,\ni.e. it will not remember what you have asked it to find in the past.\n\nUse this tool carefully. It is difficult to retrieve images, and the images\nthemselves will fill up your context window quickly. Here are some guidelines:\n1. ALWAYS use this tool if the question explicitly mentions 'Table X' or 'Figure Y'.\n   These questions require visual content and cannot be answered with text alone.\n2. Use this tool as a fallback when gather_evidence fails repeatedly (2+ times\n   returning 'No relevant evidence'). This suggests the answer may be in visual content.\n3. When gather_evidence returns text mentioning 'see Figure X' or 'shown in Table Y',\n   you should call this tool to examine that specific visual reference.\n4. Only call this tool after directly inspecting relevant text with read_text\n   to confirm the document likely contains the visual you need.\n5. Don't use this tool in a broad-spectrum way (don't call on many documents\n   just to see what might be relevant).\n6. Never call this tool in parallel with itself.\n7. Users like visual evidence, so call this tool at least once before answering so you\n   can provide some image citations in the answer. Add this to your plan so you do not forget.\n   For images to be presented to the user, they must be cited in the final answer after retrieval\n   by this tool. You may ignore this instruction if the request is for the question is asking\n   for a specific piece of information and is not an open-ended research question.\n8. NEVER cite full-page images in your final answer, unless they are full-page panels figures or\n   tables. Cite relevant cropped regions if available, otherwise consider calling this tool again\n   to find a smaller region that answers the query.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "Query to search for visual content in the document. If you know the specific\nfigure/table/formula you are looking for, you can specify it here (e.g. \"find me\nFigure 3\" or \"extract the table on page 10\"). You can also request based on content\n(e.g. \"find me all volcano plots of gene X\" or \"I need the formula for the growth rate\").\nYou can even include explicit instructions for the LLM agent to follow (if helpful, not\nnecessarily required). The more specific and clear your query is here, the higher the\nchance of success.",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "text_name": {
+                        "description": "Name of a text chunk (e.g., 'smith2023example pages 1-5').",
+                        "title": "Text Name",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "query",
+                      "text_name"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "update_plan",
+                  "description": "Update the plan for a specific or new objective using a JSON string to create or\nreplace the existing objective.\n\nThe updated_json should be a JSON string representing a single plan objective object.\n\nYou may use this tool to update an objective, create a new one, or change\nstrategy if the current plan is not working. Only change strategy significantly\nas a last resort, after trying very hard to make the current plan work.\n\nOnly mark an objective as completed if you are absolutely sure that it has been fully\nmet. If it is only partially met, you may add additional objectives to the plan for\nwhat is missing.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "plan_objective_id": {
+                        "description": "The id of the objective to update.",
+                        "title": "Plan Objective Id",
+                        "type": "integer"
+                      },
+                      "updated_plan_objective_json": {
+                        "description": "A JSON string representing the updated objective.\nIt should be a dictionary with the with the following keys:\n- \"id\": (int) an integer id matching plan_objective_id, if not found, a new objective is created.\n- \"objective\": (str) a human readable description of the objective's goal\n- \"rationale\": (str) a human readable rationale\n    describing why this objective is necessary and appropriate for the query.\n- \"status\": (str) updated task status, default to pending,\n    one of: pending, in-progress, or completed.\n    \"pending\" is yet to be started,\n    \"in-progress\" is the current objective being solved,\n    \"completed\" is successfully completed with acceptance criteria met.\n- \"result\": (str|None) The result of the objective, default to None.\n- \"evaluation\": (str|None) Description of why the objective result\n    meets the criteria for being complete. Default to None.",
+                        "title": "Updated Plan Objective Json",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "plan_objective_id",
+                      "updated_plan_objective_json"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "create_artifact",
+                  "description": "Create an artifact that can be used in the final answer, based on information\nyou have collected so far.\n\nHow it works: the full message history thus far is passed to another LLM,\nalong with the question and your description. The LLM is tasked to create\nan artifact that matches your specifications, including a title, caption,\nand markdown content. You drive the process by specifying the type and\ndescribing what you want.\n\nOnly use this tool *after* you have gathered sufficient evidence or\ninformation to create a new artifact. Do not call this tool in parallel\nwith tools that are searching for information or evidence that would be\nnecessary to create this artifact.\n\nIt is very helpful after calls to several search tools,\nafter calls to the `gather_evidence` tool, but it is not required.\nHowever, it should be called before the `answer` tool at\nleast one time, but more may be given if specifically helpful for\nthe task, so that the `answer` tool can use the artifacts for the answer.\n\nAn artifact can be any string representable fact or list of facts,\nformatted using markdown syntax. The artifact will be generated as one of\nthe following types:\n- table: Markdown tables with rows and columns (e.g., findings, methods, molecules)\n- code_block: Code snippets in fenced code blocks\n- blockquote: Quoted text or important facts (using > prefix)\n- image: AI-generated image (chart, diagram, or visualization)\n\nEach artifact consists of:\n- A short title (3-8 words) that names what the artifact contains\n- A caption (1-2 sentences) describing what the artifact shows and why it's useful\n- Markdown content in a single element type (validated automatically with retries if needed)\n  For image type, content is a markdown image embed ``![title](data:image/png;base64,...)``,\n  embedding the PNG directly as a base64 data URL.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "artifact_type": {
+                        "description": "Artifact type to create. Must be one of: table,\ncode_block, blockquote, image.",
+                        "title": "Artifact Type",
+                        "type": "string"
+                      },
+                      "description": {
+                        "description": "Description of what you want in the artifact. Be specific\nabout what information should be included, how it should be organized,\nand what columns/sections/content you want. This guides the summary LLM.\nFor image type, describe the visual you want generated in detail.",
+                        "title": "Description",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "artifact_type",
+                      "description"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "paper_search",
+                  "description": "Search for papers in Google Scholar for you to look at.\n\nCan be called repeatedly with identical parameters to retrieve more results (max 2 repeats).\nA short summary of the retrieved papers will be returned, but to examine the full content of each paper,\nyou must use the gather_evidence tool.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "A Google Scholar search query, which can be a specific phrase, complete sentence,\nor general keywords, e.g. 'machine learning for immunology'. Also can be\ngiven search operators like 'author:'.",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "min_year": {
+                        "anyOf": [
+                          {
+                            "type": "integer"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "filter for minimum publication year.\nThe current year is 2026. If unsure about time range, do not set.",
+                        "title": "Min Year"
+                      },
+                      "max_year": {
+                        "anyOf": [
+                          {
+                            "type": "integer"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "filter for maximum publication year.\nThe current year is 2026. If unsure about time range, do not set.",
+                        "title": "Max Year"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "patent_search",
+                  "description": "Search for patents to increase the patent count.\n\nRepeat previous calls with the same query to continue a search.\nOnly repeat a maximum of three times.\nThis tool can be called concurrently.\nThis tool introduces novel patents, so invoke it when just beginning\nor when unsatisfied with the current evidence.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "A search query for patents (using Google Patents). Never include temporal\nfilters here (e.g. specific years or dates); instead use the `after` and `before`\narguments. Never include author filters here; instead use the `inventor` argument.\nSupports the following syntax, but they can be brittle and are not preferred; try\nsimple queries where possible:\n- Boolean operators: AND (default), OR, and - (NOT)\n- Exact phrases: \"quoted text\"\n- Proximity: NEAR/x, ADJ/x (ordered), WITH (20 words), SAME (200 words)\n- Field search: TI=(title), AB=(abstract), CL=(claims)\n- CPC codes: cpc:A01B or CPC=B60R22/low (includes children)\n- Wildcards: ? (0-1 char), * (0+ chars), # (exactly 1 char)\n- Chemistry: exact molecule names, SSS=molecule (substructure),\n  ~molecule (similar), SMILES strings, SMARTS=pattern, InChI keys,\n  CL=~molecule (chemistry in claims)",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "after": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Minimum patent date. Format: YYYYMMDD.\nExample: '20150101' for patents after Jan 1, 2015.",
+                        "title": "After"
+                      },
+                      "before": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Maximum patent date. Format: YYYYMMDD.\nExample: '20200101' for patents before Jan 1, 2020.",
+                        "title": "Before"
+                      },
+                      "date_type": {
+                        "default": "publication",
+                        "description": "Type of date that after and before refer to. Must be either 'publication'\nor 'filing'. Only necessary to set if after and/or before are set.",
+                        "title": "Date Type",
+                        "type": "string"
+                      },
+                      "inventor": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Filter by inventor name(s). Comma-separated for multiple.",
+                        "title": "Inventor"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "collect_cited_papers_in_evidence",
+                  "description": "Collect papers by traversing the citations of relevant papers to increase the paper count.\n\nThis tool has no effect if called when paper count or relevant papers are zero.\nThis tool will find papers that are likely to lead to more relevant evidence.\nThe papers found have a higher chance of relevance because this tool starts from relevant evidence.\nThis tool's usefulness increases with the amount of gathered evidence as there's more citations to consider.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {},
+                    "required": []
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "gather_evidence",
+                  "description": "Given a specific question, gather evidence from full-text of documents that have been retrieved by\nprevious tool calls.\n\nHere is how the tool works: the provided question is posed to all texts retrieved thus far\nby other tools. An LLM sees each text independently and is prompted to find information relevant\nto the question.\n\nThat is, we sample evidence `e \\sim LLM(prompt, text, q)` for each text. We only return pieces of\nevidence `e` that are sufficiently relevant to the question; if the text is irrelevant, then `e`\nis not included in the final response of this tool. Note that this LLM does not see the conversation\nhistory thus far, only the question and each text. Note that it only sees text, no images or other\nmedia from the contents (though tables and formulae may be parseable in some cases).\n\nThink of this tool as an efficient way to deeply scan all retrieved documents for evidence. It\nis complementary to the `read_text` tool, which can be used to directly inspect a subset of the\nretrieved documents.\n\nA valuable time to invoke this tool is after another tool finds potentially relevant documents.\nFeel free to invoke this tool in parallel with other tools, but do not call this tool in parallel with itself.\nOnly invoke this tool when the document count is above zero, or this tool will be useless.\n\nIf you call this tool 2+ times and repeatedly get 'No relevant evidence found',\nconsider whether the answer might be in visual content (figures/tables) rather than text,\nand use appropriate tools if available to access that content.\n\nOnce you receive evidence from this tool:\n\n1. Read Carefully: Don't skim. The evidence may contain multiple similar terms\n   or values\u2014make sure you identify the RIGHT one.\n\n2. For Comparative Questions: If the question asks \"which X has greatest Y\",\n   check that the evidence includes information about ALL relevant X options, not\n   just one or two. If you only see partial information, gather more evidence.\n\n3. Check for Noise: Verify that numbers or terms aren't just metadata\n   (page numbers, reference IDs, dates). Look for the value in meaningful\n   scientific context.\n\n4. Context Matters: A term appearing 71 times doesn't mean it's always the answer.\n   Verify which occurrence actually answers the question asked.\n\nIf the evidence doesn't clearly answer the question, gather more evidence before\nconcluding. Don't guess based on partial information.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "question": {
+                        "description": "Specific question to gather evidence for.",
+                        "title": "Question",
+                        "type": "string"
+                      },
+                      "text_name_focus_list": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "if there are known text names that are relevant to the question,\nyou can specify them here. This will ensure that the tool will look at these text names\nfirst, and then look at the rest of the evidence. If left as `None`, an embedding\nsearch will be performed on underlying content to find most relevant texts.",
+                        "title": "Text Name Focus List"
+                      }
+                    },
+                    "required": [
+                      "question"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "open_targets_search",
+                  "description": "Search for disease-target associations from OpenTargets database.\n\nAdds new disease-target association data to the state and returns top search results.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "disease_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of disease names to search for.\nUsage:\ndisease_names = [\"Alzheimer's\"] ->\n    Returns top targets for Alzheimer's\ndisease_names = [\"Alzheimer's\", \"Diabetes\"], target_names = [\"PSEN1\"] ->\n    Filters for only PSEN1-Alzheimer's/Diabetes evidence\ndisease_names = [\"Alzheimer's\"], drug_names = [\"Aducanumab\"] ->\n    Filters for Alzheimer's disease-target pairs treated by Aducanumab",
+                        "title": "Disease Names"
+                      },
+                      "target_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of target names to search for.\nUsage:\ntarget_names = [\"BACE1\"] ->\n    Returns top diseases associated with BACE1\ntarget_names = [\"BACE1\", \"APP\"], disease_names = [\"Alzheimer's\"] ->\n    Filters for only these target-Alzheimer's pairs\ntarget_names = [\"BACE1\"], drug_names = [\"Aducanumab\"] ->\n    Filters for BACE1 disease pairs treated by Aducanumab",
+                        "title": "Target Names"
+                      },
+                      "drug_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of drug names to generate or filter results.\nUsage:\ndrug_names = [\"Aducanumab\"] ->\n    Returns all disease-target pairs treated by Aducanumab\ndrug_names = [\"Aducanumab\"], disease_names = [\"Alzheimer's\"] ->\n    Filters for Alzheimer's pairs treated by Aducanumab\ndrug_names = [\"Aducanumab\"], target_names = [\"BACE1\"] ->\n    Filters for BACE1 disease pairs treated by Aducanumab",
+                        "title": "Drug Names"
+                      }
+                    },
+                    "required": []
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "answer",
+                  "description": "Submit your final answer to the user. You MUST call this tool on your final answer.\nIf you mark all objectives as completed but have not yet called this tool, then\nthe answer will not be submitted. Note that this tool should only be called once, as it\nimmediately terminates the run and submits the answer.\n\nWrite an answer based on the evidence from gather_evidence results in message history.\nIf the context provides insufficient information, provide a partial answer and explain\nwhy it is partial (e.g. the question is currently an open question in the field,\nyou were unable to obtain certain papers, etc.).\n\nFor each part of your answer, indicate which sources most support it via citation IDs at\nthe end of sentences, like (pqac-0000ABCD).\nYou are only allowed to cite available context IDs, indicated in previous messages by \"Context IDs that may be cited:\".\n## Valid citation examples, only use comma/space delimited parentheticals:\n\n- (pqac-0000ABCD, pqac-0000EFGH)\n- (pqac-0000IJKL)\n\n## Invalid citation examples:\n\n- (pqac-0000ABCD and pqac-0000EFGH)\n- (pqac-0000ABCD;pqac-0000EFGH)\n- (pqac-0000ABCD-pqac-0000EFGH)\n- pqac-0000ABCD and pqac-0000EFGH\n- Example's work pqac-0000ABCD\n- (pages pqac-0000ABCD)\n- ![description](pqac-0000ABCD)\n- ()\n\nDo not concatenate citation ids, just use them as-is.\n\nWhen writing your answer, embed artifacts if relevant artifacts have been previously\ncreated by the `create_artifact` tool. To embed an artifact, simply include this in your\nanswer, on its own line and without any additional formatting (i.e. no backticks, code fences,\nquotes, additional tags, etc.).\nAlways provide at least some introductory sentence or paragraph before referring to an artifact,\nso that the artifact is properly contextualized.\nHere is an example reference to an artifact with ID \"artifact-XY\":\n<artifact id=\"artifact-XY\"/>\n\nValid artifact IDs are indicated in previous messages by 'Artifact IDs that may be injected into the answer:'.\n\n\nDouble-check your answer:\n\n1. Evidence Match: Re-read the specific evidence snippets you're citing. Does your\n   answer actually match what they say? Don't rely on memory from 20+ messages ago.\n\n2. For Comparative Questions (\"which X has greatest/maximum/highest Y\"):\n   - Did you examine ALL options mentioned in the evidence?\n   - Did you explicitly compare their values?\n   - Example: If evidence mentions \"Pancreatic: 0.92, Liver: 0.85, Lung: 0.78\",\n     verify you compared all three, not just two.\n\n3. For Specific Value Questions (\"How many\", \"What is the\", specific terms):\n   - Does the exact value you're stating appear in the evidence?\n   - Are you extracting from the right context (not noise like page numbers)?\n\n4. Sanity Check: Read your answer. Does it directly address what was asked?\n\nDon't use Markdown image syntax like ![...](...) to reference media in your answer,\nbecause media get automatically linked by the system based on your answer's citations.\n\nWrite in the style of a scientific article, with concise sentences and\ncoherent paragraphs. This answer will be used directly,\nso do not add any extraneous information.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "answer": {
+                        "description": "valid answer, cited with citation IDs.",
+                        "title": "Answer",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "answer"
+                    ]
+                  }
+                }
+              }
+            ],
+            "messages": [
+              {
+                "role": "user",
+                "content": "Use the tools to answer the question: I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.\n\nStart by making a plan, and update the plan as you go. Your answer will be returned to the user when all plan objectives are completed. Be thorough and ensure your evidence matches the user's question.",
+                "info": null
+              },
+              {
+                "role": "assistant",
+                "content": "\n\nI'll create a comprehensive plan to address this multi-part question about SEM-EDS standards-based quantification.",
+                "function_call": null,
+                "tool_calls": [
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+                    "id": "toolu_016qD7jWzhrDrjZBuisuwM3M",
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+                      "name": "create_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Plan registered and formatted correctly, with some modifications:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "create_plan",
+                "tool_call_id": "toolu_016qD7jWzhrDrjZBuisuwM3M",
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+                  "end_ts": 4092.090283959
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+              {
+                "role": "assistant",
+                "content": "Let me begin with parallel searches across multiple topics:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_012niF3hCcCELZiFsH81WLEJ",
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+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"in-progress\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_012niF3hCcCELZiFsH81WLEJ",
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+                      "arguments": "{\"query\": \"EMSA MAS MSA spectrum file format specification EDS microanalysis\"}",
+                      "name": "paper_search"
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+                    "id": "toolu_016Qhr9dS26wxR1YtxHjvMco",
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+                      "arguments": "{\"query\": \"DTSA-II NIST standards-based k-ratio quantification EDS Ritchie\"}",
+                      "name": "paper_search"
+                    }
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+                  {
+                    "id": "toolu_01D5Nvbe43QYfNMbJkfm89c8",
+                    "type": "function",
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+                      "arguments": "{\"query\": \"Newbury Ritchie low voltage SEM-EDS quantification k-ratio protocol\"}",
+                      "name": "paper_search"
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+                    "id": "toolu_016rf7SVgyqxtxmhj8EFjKYD",
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+                      "arguments": "{\"query\": \"EDS detector response silicon drift detector peak tailing incomplete charge collection low energy\"}",
+                      "name": "paper_search"
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+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Reliable Surface Analysis Data of Nanomaterials in Support of Risk Assessment Based on Minimum Information Requirements\nValid Text Names:\n'radnik2021reliablesurfaceanalysis pages 1-2', 'radnik2021reliablesurfaceanalysis pages 2-4', 'radnik2021reliablesurfaceanalysis pages 4-5', 'radnik2021reliablesurfaceanalysis pages 5-7', 'radnik2021reliablesurfaceanalysis pages 7-9', 'radnik2021reliablesurfaceanalysis pages 9-11', 'radnik2021reliablesurfaceanalysis pages 11-12', 'radnik2021reliablesurfaceanalysis pages 12-15', 'radnik2021reliablesurfaceanalysis pages 15-17', 'radnik2021reliablesurfaceanalysis pages 17-18', 'radnik2021reliablesurfaceanalysis pages 18-20', 'radnik2021reliablesurfaceanalysis pages 20-20'\n\nBibTex:\n@article{radnik2021reliablesurfaceanalysis,\n    author = \"Radnik, J\u00f6rg and Kersting, Reinhard and Hagenhoff, Birgit and Bennet, Francesca and Ciornii, Dmitri and Nymark, Penny and Grafstr\u00f6m, Roland and Hodoroaba, Vasile-Dan\",\n    title = \"Reliable Surface Analysis Data of Nanomaterials in Support of Risk Assessment Based on Minimum Information Requirements\",\n    year = \"2021\",\n    journal = \"Nanomaterials\",\n    volume = \"11\",\n    pages = \"639\",\n    month = \"Mar\",\n    doi = \"10.3390/nano11030639\",\n    url = \"https://doi.org/10.3390/nano11030639\",\n    publisher = \"MDPI AG\",\n    issue = \"3\",\n    issn = \"2079-4991\"\n}\n\n\nAbstract:\nThe minimum information requirements needed to guarantee high-quality surface analysis data of nanomaterials are described with the aim to provide reliable and traceable information about size, shape, elemental composition and surface chemistry for risk assessment approaches. The widespread surface analysis methods electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) were considered. The complete analysis sequence from sample preparation, over measurements, to data analysis and data format for reporting and archiving is outlined. All selected methods are used in surface analysis since many years so that many aspects of the analysis (including (meta)data formats) are already standardized. As a practical analysis use case, two coated TiO2 reference nanoparticulate samples, which are available on the Joint Research Centre (JRC) repository, were selected. The added value of the complementary analysis is highlighted based on the minimum information requirements, which are well-defined for the analysis methods selected. The present paper is supposed to serve primarily as a source of understanding of the high standardization level already available for the high-quality data in surface analysis of nanomaterials as reliable input for the nanosafety community.\n\nRelevant Snippet:\n\u2026 EDS spectra of the two particulate samples prepared as dry powder on a silicon substrate were taken at 10 kV, see Figure 4. The analysis surfaces were selected roughly similarly, so \u2026\n\n\n---\n\n## 2. Critical Issues in Scanning Electron Microscope Metrology\nValid Text Names:\n'postek1994criticalissuesin pages 1-2', 'postek1994criticalissuesin pages 2-3', 'postek1994criticalissuesin pages 3-6', 'postek1994criticalissuesin pages 6-7', 'postek1994criticalissuesin pages 7-8', 'postek1994criticalissuesin pages 8-10', 'postek1994criticalissuesin pages 10-11', 'postek1994criticalissuesin pages 11-13', 'postek1994criticalissuesin pages 13-15', 'postek1994criticalissuesin pages 15-16', 'postek1994criticalissuesin pages 16-18', 'postek1994criticalissuesin pages 18-19', 'postek1994criticalissuesin pages 19-20', 'postek1994criticalissuesin pages 20-24', 'postek1994criticalissuesin pages 24-26', 'postek1994criticalissuesin pages 26-28', 'postek1994criticalissuesin pages 28-28', 'postek1994criticalissuesin pages 28-30', 'postek1994criticalissuesin pages 30-30', 'postek1994criticalissuesin pages 30-31', 'postek1994criticalissuesin pages 31-31'\n\nBibTex:\n@article{postek1994criticalissuesin,\n    author = \"Postek, M.T.\",\n    title = \"Critical Issues in Scanning Electron Microscope Metrology\",\n    year = \"1994\",\n    journal = \"Journal of Research of the National Institute of Standards and Technology\",\n    volume = \"99\",\n    pages = \"641-671\",\n    month = \"Sep\",\n    doi = \"10.6028/jres.099.059\",\n    url = \"https://doi.org/10.6028/jres.099.059\",\n    publisher = \"National Institute of Standards and Technology (NIST)\",\n    issue = \"5\",\n    issn = \"1044-677X\"\n}\n\n\nAbstract:\nDuring the manufacturing of present-day integrated circuits, certain measurements must be made of the submicrometer structures composing the device with a high degree of repeatability. Optical microscopy, scanning electron microscopy, and the various forms of scanning probe microscopies are major microscopical techniques used for this submicrometer metrology. New techniques applied to scanning electron microscopy have improved some of the limitations of this technique and time will permit even further improvements. This paper reviews the current state of scanning electron microscope (SEM) metrology in light of many of these recent improvements.\n\nRelevant Snippet:\n\u2026 coupled to an xray microanalysis system. Today, many desktop \u2026 microscope, Proc EMSA GW Bailey, ed. (1968) pp. 359-360. \u2026 detection in electron microscopy and spectroscopy, part 1, \u2026\n\n\n---\n\n## 3. Chemical Microscopy\nValid Text Names:\n'cooke1996chemicalmicroscopy pages 3-4', 'cooke1996chemicalmicroscopy pages 6-7', 'cooke1996chemicalmicroscopy pages 7-8', 'cooke1996chemicalmicroscopy pages 12-13', 'cooke1996chemicalmicroscopy pages 15-16', 'cooke1996chemicalmicroscopy pages 16-17', 'cooke1996chemicalmicroscopy pages 18-19', 'cooke1996chemicalmicroscopy pages 20-21', 'cooke1996chemicalmicroscopy pages 22-23', 'cooke1996chemicalmicroscopy pages 24-25', 'cooke1996chemicalmicroscopy pages 25-26', 'cooke1996chemicalmicroscopy pages 26-27', 'cooke1996chemicalmicroscopy pages 28-29', 'cooke1996chemicalmicroscopy pages 30-31', 'cooke1996chemicalmicroscopy pages 32-33', 'cooke1996chemicalmicroscopy pages 34-35', 'cooke1996chemicalmicroscopy pages 36-37', 'cooke1996chemicalmicroscopy pages 37-37', 'cooke1996chemicalmicroscopy pages 38-39', 'cooke1996chemicalmicroscopy pages 41-42', 'cooke1996chemicalmicroscopy pages 41-41', 'cooke1996chemicalmicroscopy pages 42-43', 'cooke1996chemicalmicroscopy pages 44-44', 'cooke1996chemicalmicroscopy pages 44-45', 'cooke1996chemicalmicroscopy pages 45-46'\n\nBibTex:\n@article{cooke1996chemicalmicroscopy,\n    author = \"Cooke, Peter M.\",\n    title = \"Chemical Microscopy\",\n    volume = \"68\",\n    issn = \"0003-2700\",\n    url = \"https://doi.org/10.1021/a1960011t\",\n    doi = \"10.1021/a1960011t\",\n    number = \"12\",\n    journal = \"Analytical Chemistry\",\n    publisher = \"American Chemical Society (ACS)\",\n    year = \"1996\",\n    month = \"Jan\",\n    pages = \"333-378\",\n    issue = \"12\"\n}\n\n\nRelevant Snippet:\n\u2026 MAS at Loyola Marymount University. It has been highly recommended to microbeam scientists and SEM operators that use ED \u2026 toacoustic spectroscopy, and FT-Raman spectroscopy \u2026\n\n\nUnobtainable Papers:\nJohn J Friel and Richard B Mott. Energy-dispersive spectrometry from then until now: a chronology of innovation. Microscopy and Microanalysis, 4:559-566, Dec 1998. URL: https://doi.org/10.1017/s1431927698980539, doi:10.1017/s1431927698980539.\nMasashi Watanabe. Practical aspects and advanced applications of xeds. ArXiv, pages 467-503, Jan 2016. URL: https://doi.org/10.1007/978-3-319-26651-0\\_17, doi:10.1007/978-3-319-26651-0\\_17.\nJohn Henry J. Scott, Scott A. Wight, and Barbara B. Thorne. Xml for microanalysis: emsa/mas spectrum file format 2.0? Microscopy and Microanalysis, 8:646-647, Aug 2002. URL: https://doi.org/10.1017/s1431927602105782, doi:10.1017/s1431927602105782.\nMasashi Watanabe. Practical Aspects and Advanced Applications of XEDS, pages 729-775. Springer Nature Switzerland, Jan 2026. URL: https://doi.org/10.1007/978-3-031-80789-3\\_24, doi:10.1007/978-3-031-80789-3\\_24.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_01Q6QzfmUJTUaE37F9rwTvBx",
+                "info": {
+                  "start_ts": 4116.718020368,
+                  "end_ts": 4145.733581443
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Using the EDS Clues: Peak Fitting Residual Spectrum and Analytical Total\nValid Text Names:\n'newbury2019usingtheeds pages 1-2'\n\nBibTex:\n@article{newbury2019usingtheeds,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Using the EDS Clues: Peak Fitting Residual Spectrum and Analytical Total\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"446-447\",\n    month = \"Aug\",\n    doi = \"10.1017/s1431927619002964\",\n    url = \"https://doi.org/10.1017/s1431927619002964\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"S2\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nElectron-excited X-ray microanalysis with energy dispersive X-ray spectrometry (EDS) can provide comprehensive elemental analysis for all elements, except for H and He which do not produce X-rays. However, the poorer spectral resolution, ~125 eV full peak width at half peak maximum (FWHM) as compared to ~8 eV for wavelength dispersive spectrometry (WDS) at Mn K-L2,3(5890 eV), leads to frequent peak interference situations in EDS spectra. When interferences occur between the available analytical characteristic X-ray peaks, it is possible that one of the constituents will not be recognized during qualitative analysis (X-ray peak assignment), even for interferences of major-upon-major constituents (where \u201cmajor\u201d is arbitrarily defined as a mass concentration Ci > 0.1; \u201cminor\u201d is 0.01 \u2264 Ci \u2264 0.1, and trace is Ci < 0.01). For interference involving major-upon-minor or major-upon-trace constituents, it is much more likely that the minor or trace constituent will not be recognized. To detect such hidden peaks, the EDS analytical software should construct the \u201cresidual spectrum\u201d that remains after peak fitting of the complete X-ray families of the known constituents to extract characteristic X-ray intensities necessary for the subsequent quantitative analysis. Moreover, if this quantitative analysis is performed by following the standards-based k-ratio protocol with matrix corrections (for electron scattering, X-ray absorption, and secondary X-ray fluorescence) originated by Castaing, then the raw analytical total, i.e., the sum of all constituents including any element such as oxygen calculated by the method of assumed stoichiometry, can also suggest the possibility of missing constituents through deviation below unity [1,2]. The following example illustrates the use of these tools for the analysis of NIST SRM 481 Au-Ag alloys (nominal 20Au-80Ag). The surface being analyzed was metallographically prepared in the early 1970s and stored in a desiccator. In Figure 1 (upper), the Au M-family and Ag L-family appear to account for all the X-ray peaks in this energy range. Quantitative analysis with pure element standards and NIST DTSA-II reveals anomalously low analytical totals with the Ag L-family and either the Au L3-M4,5 (0.9040) or the Au M-family (0.8382). Note that if the normalized concentrations are used, the relative deviation from expected value (RDEV) calculated as: RDEV=[(Measured-True)/True] x 100% is modest for analysis with Ag L3-M4,5 (-0.79%) and Au L3-M4,5 (2.7%), although the result for Au has a large RDEV value for analysis with Ag L3-M4,5 (3.4%) and the Au M-family (-11.8%). Close inspection of the peak fitting residual spectrum shown in Figure 1 (lower) reveals the reason for the low totals: S and Cl are present within a surface tarnish layer, but the S K-family is hidden under the Au M-family, while the Cl K-family is hidden under the Ag L-family. Including these elements in the analysis reveals S (0.0162) and Cl (0.0105) and increases the Ag and Au concentrations due to improved fitting, raising the analytical total to 0.9945 for analysis with Ag L-family and Au L3-M4,5, and to 0.9730 for analysis with the Au Mfamily. When analyzed at low beam energy (5 keV), the tarnish layer comprises a larger fraction of the sampling depth, and the S and Cl K-family peaks become much more obvious, as shown in Figure 2. Quantitative analysis at E0=5 keV yields an analytical total of 0.9961 and an Ag/Au ratio of 8.3 compared to 3.5 expected from the SRM values. Much higher levels of S (0.0949) and Cl (0.0905) are found. The Ag content of the surface layer is likely enriched relative to Au due to the formation of Ag sulfide and chloride in the tarnish layer. Trace Cu (0.0082), likely deposited on the surface during the original polishing by transfer from a nearby co-mounted Cu standard, is also detected in the tarnish layer.\n\nRelevant Snippet:\n\u2026 is performed by following the standards-based k-ratio protocol with matrix corrections (for \u2026 Quantitative analysis with pure element standards and NIST DTSA-II reveals anomalously low \u2026\n\n\nUnobtainable Papers:\nDale E Newbury and Nicholas W M Ritchie. Energy-dispersive x-ray spectrum simulation with nist dtsa-ii: comparing simulated and measured electron-excited spectra. Dec 2022. URL: https://doi.org/10.1017/s1431927622012272, doi:10.1017/s1431927622012272.\nNicholas W.M. Ritchie. Standards-based quantification in dtsa-ii\u2014part i. Microscopy Today, 19:30-36, Aug 2011. URL: https://doi.org/10.1017/s155192951100085x, doi:10.1017/s155192951100085x.\nN. Ritchie, Andrew A. Herzing, and V. Oleshko. Quantification of stem-in-sem energy dispersive x-ray spectra using bulk standards. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29:1921-1930, Nov 2023. URL: https://doi.org/10.1093/micmic/ozad109, doi:10.1093/micmic/ozad109.\nDale Newbury and Nicholas Ritchie. Quantitative electron-excited x-ray microanalysis with low energy l-peaks. Microscopy and Microanalysis, 26:44-49, Aug 2020. URL: https://doi.org/10.1017/s1431927620013215, doi:10.1017/s1431927620013215.\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis at low beam energy: almost always an adventure! \u2020. Microscopy and Microanalysis, 22:735-753, Aug 2016. URL: https://doi.org/10.1017/s1431927616011521, doi:10.1017/s1431927616011521.\nDale E Newbury and Nicholas WM Ritchie. Quantitative electron-excited x-ray microanalysis with low-energy l-shell x-ray peaks measured with energy-dispersive spectrometry. Microscopy and Microanalysis, 27:1375-1408, Dec 2021. URL: https://doi.org/10.1017/s1431927621012617, doi:10.1017/s1431927621012617.\nN. Ritchie, Jeffrey M. Davis, and D. Newbury. Dtsa-ii: a new tool for simulating and quantifying eds spectra - application to difficult overlaps. Microscopy and Microanalysis, 14(S2):1176-1177, Aug 2008. URL: https://doi.org/10.1017/s143192760808361x, doi:10.1017/s143192760808361x.\nNicholas W. M. Ritchie, Michael J. Mengason, and Dale E. Newbury. Standard bundles simplify standards-based quantification in nist dtsa-ii. Microscopy and Microanalysis, 23:220-221, Jul 2017. URL: https://doi.org/10.1017/s1431927617001787, doi:10.1017/s1431927617001787.\nMichael Mengason and Nicholas Ritchie. Overcoming peak overlaps in titanium- and vanadium-bearing materials with multiple linear least squares fitting. Microscopy and Microanalysis, 23(3):491-500, Mar 2017. URL: https://doi.org/10.1017/s1431927617000265, doi:10.1017/s1431927617000265.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\nValid Text Names:\n'goldstein2018quantitativeanalysisthe pages 1-4', 'goldstein2018quantitativeanalysisthe pages 4-6', 'goldstein2018quantitativeanalysisthe pages 6-8', 'goldstein2018quantitativeanalysisthe pages 8-9', 'goldstein2018quantitativeanalysisthe pages 9-11', 'goldstein2018quantitativeanalysisthe pages 11-12', 'goldstein2018quantitativeanalysisthe pages 12-14', 'goldstein2018quantitativeanalysisthe pages 14-16', 'goldstein2018quantitativeanalysisthe pages 16-18', 'goldstein2018quantitativeanalysisthe pages 18-22', 'goldstein2018quantitativeanalysisthe pages 18-18', 'goldstein2018quantitativeanalysisthe pages 22-23', 'goldstein2018quantitativeanalysisthe pages 23-24', 'goldstein2018quantitativeanalysisthe pages 24-26', 'goldstein2018quantitativeanalysisthe pages 26-28', 'goldstein2018quantitativeanalysisthe pages 28-29', 'goldstein2018quantitativeanalysisthe pages 29-30', 'goldstein2018quantitativeanalysisthe pages 30-31', 'goldstein2018quantitativeanalysisthe pages 31-31'\n\nBibTex:\n@article{goldstein2018quantitativeanalysisthe,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"309-339\",\n    doi = \"10.1007/978-1-4939-6676-9\\_20\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_20\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nThis module discusses the procedure used to perform a rigorous quantitative elemental microanalysis by SEM/EDS following the k-ratio/matrix correction protocol using the NIST DTSA-II software engine for bulk specimens. Bulk specimens have dimensions that are sufficiently large to contain the full range of the direct electron-excited X-ray production (typically 0.5\u201310 \u03bcm) as well as the range of secondary X-ray fluorescence induced by the propagation of the characteristic and continuum X-rays (typically 10\u2013100 \u03bcm).\n\nRelevant Snippet:\n\u2026 This chapter discusses the procedure used to perform a rigorous quantitative elemental microanalysis by SEM/EDS following the k-ratio/matrix correction protocol using the NIST DTSA-\u2026\n\n\n---\n\n## 2. Quantitative SEM/EDS, Step 1: What Constitutes a Sufficiently Flat Specimen?\nValid Text Names:\n'newbury2013quantitativesemedsstep pages 1-2'\n\nBibTex:\n@article{newbury2013quantitativesemedsstep,\n    author = \"Newbury, D.E. and Ritchie, N.W.\",\n    title = \"Quantitative SEM/EDS, Step 1: What Constitutes a Sufficiently Flat Specimen?\",\n    year = \"2013\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"19\",\n    pages = \"1244-1245\",\n    month = \"Aug\",\n    doi = \"10.1017/s1431927613008210\",\n    url = \"https://doi.org/10.1017/s1431927613008210\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"S2\",\n    issn = \"1431-9276\"\n}\n\n\nRelevant Snippet:\n\u2026 -8370 The most rigorous quantitative electron-excited x-ray \u2026 spectrometry (SEM/EDS) follows the k ratio protocol: measure \u2026 By utilizing the k ratio protocol, SEM/EDS has been shown to \u2026\n\n\n---\n\n## 3. Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\nValid Text Names:\n'newbury2019electronexcitedxraymicroanalysis pages 1-2', 'newbury2019electronexcitedxraymicroanalysis pages 2-3', 'newbury2019electronexcitedxraymicroanalysis pages 3-4', 'newbury2019electronexcitedxraymicroanalysis pages 4-5', 'newbury2019electronexcitedxraymicroanalysis pages 5-6', 'newbury2019electronexcitedxraymicroanalysis pages 6-8', 'newbury2019electronexcitedxraymicroanalysis pages 8-10', 'newbury2019electronexcitedxraymicroanalysis pages 10-13', 'newbury2019electronexcitedxraymicroanalysis pages 13-15', 'newbury2019electronexcitedxraymicroanalysis pages 15-16', 'newbury2019electronexcitedxraymicroanalysis pages 16-18', 'newbury2019electronexcitedxraymicroanalysis pages 18-20', 'newbury2019electronexcitedxraymicroanalysis pages 20-22', 'newbury2019electronexcitedxraymicroanalysis pages 22-26', 'newbury2019electronexcitedxraymicroanalysis pages 26-28', 'newbury2019electronexcitedxraymicroanalysis pages 28-29', 'newbury2019electronexcitedxraymicroanalysis pages 29-30', 'newbury2019electronexcitedxraymicroanalysis pages 29-29', 'newbury2019electronexcitedxraymicroanalysis pages 30-31'\n\nBibTex:\n@article{newbury2019electronexcitedxraymicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W.M.\",\n    title = \"Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"1075-1105\",\n    month = \"Oct\",\n    doi = \"10.1017/s143192761901482x\",\n    url = \"https://doi.org/10.1017/s143192761901482x\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"05\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nAbstract 2018 marked the 50th anniversary of the introduction of energy dispersive X-ray spectrometry (EDS) with semiconductor detectors to electron-excited X-ray microanalysis. Initially useful for qualitative analysis, EDS has developed into a fully quantitative analytical tool that can match wavelength dispersive spectrometry for accuracy in the determination of major (mass concentration C > 0.1) and minor (0.01 \u2264 C \u2264 0.1) constituents, and useful accuracy can extend well into the trace (0.001 < C < 0.01) constituent range even when severe peak interference occurs. Accurate analysis is possible for low atomic number elements (B, C, N, O, and F), and at low beam energy, which can optimize lateral and depth spatial resolution. By recording a full EDS spectrum at each picture element of a scan, comprehensive quantitative compositional mapping can also be performed.\n\nRelevant Snippet:\n\u2026 of quantitative analysis that followed the Castaing k-ratio/matrix corrections protocol (eg, \u2026 a new level of electron-excited elemental X-ray microanalysis (Newbury & Ritchie, 2015a). \u2026\n\n\n---\n\n## 4. Testing the accuracy of low-beam-energy electron-excited X-ray microanalysis with energy-dispersive spectrometry\nValid Text Names:\n'newbury2024testingtheaccuracy pages 1-3', 'newbury2024testingtheaccuracy pages 3-4', 'newbury2024testingtheaccuracy pages 4-6', 'newbury2024testingtheaccuracy pages 6-8', 'newbury2024testingtheaccuracy pages 8-9', 'newbury2024testingtheaccuracy pages 9-11', 'newbury2024testingtheaccuracy pages 11-12', 'newbury2024testingtheaccuracy pages 12-14', 'newbury2024testingtheaccuracy pages 14-16', 'newbury2024testingtheaccuracy pages 16-18', 'newbury2024testingtheaccuracy pages 18-22', 'newbury2024testingtheaccuracy pages 22-24', 'newbury2024testingtheaccuracy pages 24-24'\n\nBibTex:\n@article{newbury2024testingtheaccuracy,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Testing the accuracy of low-beam-energy electron-excited X-ray microanalysis with energy-dispersive spectrometry\",\n    year = \"2024\",\n    journal = \"Journal of Materials Science\",\n    volume = \"59\",\n    pages = \"19088-19111\",\n    month = \"Oct\",\n    doi = \"10.1007/s10853-024-10285-4\",\n    url = \"https://doi.org/10.1007/s10853-024-10285-4\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"40\",\n    issn = \"0022-2461\"\n}\n\n\nAbstract:\nThe accuracy of electron-excited X-ray microanalysis with energy-dispersive spectrometry (EDS) has been tested in the low beam energy range, specifically at an incident beam energy of 5 keV, which is the lowest beam energy for which a useful characteristic X-ray peak can be excited for all elements of the periodic table, excepting H and He. Elemental analysis results are reported for certified reference materials (CRM), stoichiometric compounds, minerals, and metal alloys of independently known or measured composition which had microscopic homogeneity suitable for microanalysis. Two-hundred sixty-three concentration measurements for 39 elements in 113 materials were determined following the k-ratio protocol and using the EDS analytical software NIST DTSA-II. The accuracy of the results, as characterized by the relative deviation from expected value (RDEV) metric, was such that more than 98% of the results were found to be captured within a range of \u00b15% RDEV, while 82% of the results fell in the range -2% to 2% RDEV.\n\nRelevant Snippet:\n\u2026 k-ratio protocol and using the EDS analytical software NIST \u2026 Analysis followed the standards-based measurement protocol\u2026 as that provided by the NIST DTSA-II software platform [3]. \u2026\n\n\n---\n\n## 5. Quantitative Analysis: From k-ratio to Composition\nValid Text Names:\n'goldstein2018quantitativeanalysisfrom pages 1-3', 'goldstein2018quantitativeanalysisfrom pages 3-4', 'goldstein2018quantitativeanalysisfrom pages 4-5', 'goldstein2018quantitativeanalysisfrom pages 5-6', 'goldstein2018quantitativeanalysisfrom pages 6-7', 'goldstein2018quantitativeanalysisfrom pages 7-9', 'goldstein2018quantitativeanalysisfrom pages 9-10', 'goldstein2018quantitativeanalysisfrom pages 10-11', 'goldstein2018quantitativeanalysisfrom pages 11-12', 'goldstein2018quantitativeanalysisfrom pages 12-14', 'goldstein2018quantitativeanalysisfrom pages 14-15', 'goldstein2018quantitativeanalysisfrom pages 15-17', 'goldstein2018quantitativeanalysisfrom pages 17-18', 'goldstein2018quantitativeanalysisfrom pages 18-19'\n\nBibTex:\n@article{goldstein2018quantitativeanalysisfrom,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Quantitative Analysis: From k-ratio to Composition\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"289-307\",\n    month = \"Nov\",\n    doi = \"10.1007/978-1-4939-6676-9\\_19\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_19\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nA k-ratio is the ratio of a pair of characteristic X-ray line intensities, I, measured under similar experimental conditions for the unknown (unk) and standard (std): \n \n$$ k={I}_{unk}/{I}_{std} $$ \n \nThe measured intensities can be associated with a single characteristic X-ray line (as is typically the case for wavelength spectrometers) or associated with a family of characteristic X-ray lines (as is typically the case for energy dispersive spectrometers.) The numerator of the k-ratio is typically the intensity measured from an unknown sample and the denominator is typically the intensity measured from a standard material\u2014a material of known composition.\n\nRelevant Snippet:\n\u2026 Table 19.2, which gives the results of an SEM- EDS analysis of a YBa2Cu3O7-X single crystal by the k-ratio/standards protocol (NIST DTSA) compared to standardless \u2026\n\n\n---\n\n## 6. Measurement uncertainties of energy dispersive X-ray spectroscopy in the scanning electron microscope (SEM-EDX/EDS)\nValid Text Names:\n'tong2026measurementuncertaintiesof pages 1-8', 'tong2026measurementuncertaintiesof pages 8-11', 'tong2026measurementuncertaintiesof pages 11-12', 'tong2026measurementuncertaintiesof pages 12-15', 'tong2026measurementuncertaintiesof pages 15-18', 'tong2026measurementuncertaintiesof pages 18-21', 'tong2026measurementuncertaintiesof pages 21-24', 'tong2026measurementuncertaintiesof pages 24-26'\n\nBibTex:\n@article{tong2026measurementuncertaintiesof,\n    author = \"Tong, V. and Mingard, K.\",\n    title = \"Measurement uncertainties of energy dispersive X-ray spectroscopy in the scanning electron microscope (SEM-EDX/EDS)\",\n    year = \"2026\",\n    journal = \"Unknown journal\",\n    month = \"Mar\",\n    doi = \"10.47120/npl.mat135\",\n    url = \"https://doi.org/10.47120/npl.mat135\",\n    publisher = \"National Physical Laboratory\"\n}\n\n\nRelevant Snippet:\n\u2026 microscope (SEM-EDX or SEM-EDS \u2013 the terms are generally \u2026 [1] DE Newbury and NWM Ritchie, \u2018Performing elemental \u2026 - k-ratio standards database optimised for 10 kV - Qualitative \u2026\n\n\n---\n\n## 7. Chemical characterisation is rough: the impact of topography and measurement parameters on energy-dispersive X-ray spectroscopy in biominerals\nValid Text Names:\n'shirley2022chemicalcharacterisationis pages 1-2', 'shirley2022chemicalcharacterisationis pages 2-5', 'shirley2022chemicalcharacterisationis pages 5-7', 'shirley2022chemicalcharacterisationis pages 7-9', 'shirley2022chemicalcharacterisationis pages 9-12', 'shirley2022chemicalcharacterisationis pages 12-14', 'shirley2022chemicalcharacterisationis pages 14-15', 'shirley2022chemicalcharacterisationis pages 15-15'\n\nBibTex:\n@article{shirley2022chemicalcharacterisationis,\n    author = \"Shirley, Bryan and Jarochowska, Emilia\",\n    title = \"Chemical characterisation is rough: the impact of topography and measurement parameters on energy-dispersive X-ray spectroscopy in biominerals\",\n    year = \"2022\",\n    journal = \"Facies\",\n    volume = \"68\",\n    month = \"Mar\",\n    doi = \"10.1007/s10347-022-00645-4\",\n    url = \"https://doi.org/10.1007/s10347-022-00645-4\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"2\",\n    issn = \"0172-9179\"\n}\n\n\nAbstract:\nEnergy dispersive X-ray microscopy (EDX) is a widely available, inexpensive method of characterizing the in-situ elemental composition of samples in Earth and life sciences. Common protocols and textbooks focussing on material sciences address EDX analysis of metallic samples that can be polished perfectly, whereas geoscientists often investigate specimens with prominent topography and composed of light, difficult to resolve elements. This is further compounded by the scarcity of literature surrounding the methodology of SEM\u2013EDX in the field of palaeontology, leading to common misinterpretations and artefacts during data acquisition. Here, the common errors in elemental composition obtained with EDX arising from surface topography and from parameters subject to user decisions are quantified. As a model, fossil bioapatite (conodonts) and abiotic Durango apatite are used. It is shown that even microscale topography can distort measured composition by up to 34%, whereas topographic features such as tilt with respect to the electron beam lead to differences of up to 85%. Working distance was not the most important parameter affecting the results and led to differences in composition of up to 13%, whereas the choice of standard and its levelling with the sample surface led to inaccuracy reaching 33%. EDX results can be also affected by beam damage and the effects of acceleration voltage on sample acquisition and resolution are quantified. An estimate is provided of the severity of errors associated with samples which cannot satisfy preparation requirements for EDX fully, such as holotypes, and with user decisions. Using a palaeontological example, recommendations are offered for the best parameters and the relative importance of error sources are assessed.\n\nRelevant Snippet:\n\u2026 \u201csemi-quantitative\u201d (Newbury et al. 1995; Newbury and Ritchie 2014). \u2026 a low voltage for EDX has a number of limitations; using low \u2026 through standardization following the k ratio protocol. \u2026\n\n\n---\n\n## 8. Enhanced quantification for 3D SEM\u2013EDS: Using the full set of available X-ray lines\nValid Text Names:\n'burdet2015enhancedquantificationfor pages 1-2', 'burdet2015enhancedquantificationfor pages 2-3', 'burdet2015enhancedquantificationfor pages 3-4', 'burdet2015enhancedquantificationfor pages 4-5', 'burdet2015enhancedquantificationfor pages 5-8', 'burdet2015enhancedquantificationfor pages 8-9', 'burdet2015enhancedquantificationfor pages 8-8', 'burdet2015enhancedquantificationfor pages 9-10'\n\nBibTex:\n@article{burdet2015enhancedquantificationfor,\n    author = \"Burdet, Pierre and Croxall, S.A. and Midgley, P.A.\",\n    title = \"Enhanced quantification for 3D SEM\u2013EDS: Using the full set of available X-ray lines\",\n    year = \"2015\",\n    journal = \"Ultramicroscopy\",\n    volume = \"148\",\n    pages = \"158-167\",\n    month = \"Jan\",\n    doi = \"10.1016/j.ultramic.2014.10.010\",\n    url = \"https://doi.org/10.1016/j.ultramic.2014.10.010\",\n    publisher = \"Elsevier BV\",\n    issn = \"0304-3991\"\n}\n\n\nRelevant Snippet:\n\u2026 k-ratio:(1) k - ratio A = I u n k , A I s t d , A , where I is the intensity, A is an element, unk is the unknown, and std is the standard. In a first step to obtain the k-ratio\u2026 iterative procedure until a \u2026\n\n\nUnobtainable Papers:\nD.E. Newbury and N.W. Ritchie. How to do really bad sem/eds quantitative analysis, and never even notice! Microscopy and Microanalysis, 18:1004-1005, Jul 2012. URL: https://doi.org/10.1017/s1431927612006873, doi:10.1017/s1431927612006873.\nDale E. Newbury and Nicholas W. M. Ritchie. Rigorous quantitative elemental microanalysis by scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds) with spectrum processing by nist dtsa-ii. SPIE Proceedings, 9236:92360H, Sep 2014. URL: https://doi.org/10.1117/12.2065842, doi:10.1117/12.2065842.\nAlexis T. Riche, Peter McSwiggen, Kayleigh Harvey, Shelby Bowden, Rachel Bergin, Spencer M. Scott, Bryan J. Foley, and Kyle M. Samperton. Mixed element microparticle characterization by electron probe microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, Mar 2025. URL: https://doi.org/10.1093/mam/ozaf022, doi:10.1093/mam/ozaf022.\nDale E. Newbury and Nicholas W. M. Ritchie. Faults and foibles of quantitative scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds). SPIE Proceedings, 8378:837803, May 2012. URL: https://doi.org/10.1117/12.912770, doi:10.1117/12.912770.\nDale E. Newbury* and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds) quantitative? Scanning, 35 3:141-68, May 2013. URL: https://doi.org/10.1002/sca.21041, doi:10.1002/sca.21041.\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W.M. Ritchie, John Henry J. Scott, and David C. Joy. Scanning electron microscopy and x-ray microanalysis. Scanning Electron Microscopy and X-Ray Microanalysis, Jan 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9, doi:10.1007/978-1-4939-6676-9.\nAaron Shugar, Michael Notis, Dale Newbury, and Nicholas Ritchie. Investigating a moche cast copper artifact for its manufacturing technology. MRS Proceedings, 1656:95-109, Aug 2017. URL: https://doi.org/10.1557/opl.2014.822, doi:10.1557/opl.2014.822.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)\nValid Text Names:\n'newbury2015performingelementalmicroanalysis pages 1-2', 'newbury2015performingelementalmicroanalysis pages 2-4', 'newbury2015performingelementalmicroanalysis pages 4-5', 'newbury2015performingelementalmicroanalysis pages 5-6', 'newbury2015performingelementalmicroanalysis pages 6-7', 'newbury2015performingelementalmicroanalysis pages 7-9', 'newbury2015performingelementalmicroanalysis pages 9-11', 'newbury2015performingelementalmicroanalysis pages 11-13', 'newbury2015performingelementalmicroanalysis pages 13-15', 'newbury2015performingelementalmicroanalysis pages 15-17', 'newbury2015performingelementalmicroanalysis pages 17-20', 'newbury2015performingelementalmicroanalysis pages 20-21', 'newbury2015performingelementalmicroanalysis pages 21-23', 'newbury2015performingelementalmicroanalysis pages 23-25', 'newbury2015performingelementalmicroanalysis pages 25-26', 'newbury2015performingelementalmicroanalysis pages 26-26'\n\nBibTex:\n@article{newbury2015performingelementalmicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)\",\n    year = \"2015\",\n    journal = \"Journal of Materials Science\",\n    volume = \"50\",\n    pages = \"493-518\",\n    month = \"Nov\",\n    doi = \"10.1007/s10853-014-8685-2\",\n    url = \"https://doi.org/10.1007/s10853-014-8685-2\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"2\",\n    issn = \"0022-2461\"\n}\n\n\nAbstract:\nElectron-excited X-ray microanalysis performed in the scanning electron microscope with energy-dispersive X-ray spectrometry (EDS) is a core technique for characterization of the microstructure of materials. The recent advances in EDS performance with the silicon drift detector (SDD) enable accuracy and precision equivalent to that of the high spectral resolution wavelength-dispersive spectrometer employed on the electron probe microanalyzer platform. SDD-EDS throughput, resolution, and stability provide practical operating conditions for measurement of high-count spectra that form the basis for peak fitting procedures that recover the characteristic peak intensities even for elemental combination where severe peak overlaps occur, such PbS, MoS2, BaTiO3, SrWO4, and WSi2. Accurate analyses are also demonstrated for interferences involving large concentration ratios: a major constituent on a minor constituent (Ba at 0.4299 mass fraction on Ti at 0.0180) and a major constituent on a trace constituent (Ba at 0.2194 on Ce at 0.00407; Si at 0.1145 on Ta at 0.0041). Accurate analyses of low atomic number elements, C, N, O, and F, are demonstrated. Measurement of trace constituents with limits of detection below 0.001 mass fraction (1000\u00a0ppm) is possible within a practical measurement time of 500\u00a0s.\n\nRelevant Snippet:\n\u2026 of quantitative analysis was based upon their experience with the WDS k-ratio protocol. The \u2026 Unless the specimen geometry is carefully controlled, SEM/EDS analysis is subject to errors \u2026\n\n\nUnobtainable Papers:\nM. MARTINI, J.W. MAYER, and K.R. ZANIO. Drift velocity and trapping in semiconductors\u2014transient charge technique. ArXiv, 3:181-261, Jan 1972. URL: https://doi.org/10.1016/b978-0-12-002903-7.50010-2, doi:10.1016/b978-0-12-002903-7.50010-2.\nFrancesco Ceraudo, Giovanni Della Casa, Giuseppe Bertuccio, Walter Bonvicini, Riccardo Campana, Daniela Cirrincione, Ettore Del Monte, Yuri Evangelista, Marco Feroci, Francesco Ficorella, Mauro Fiorini, Marco Grassi, Piero Malcovati, Filippo Mele, Giancarlo Pepponi, Alexandre Rachevski, Irina Rashevskaya, Gianluigi Zampa, Nicola Zampa, and Nicola Zorzi. Imaging and spectroscopic performances of the silicon drift detector of the wide field monitor. Space Telescopes and Instrumentation 2024: Ultraviolet to Gamma Ray, 13093:130936U-130936U-9, Aug 2024. URL: https://doi.org/10.1117/12.3020204, doi:10.1117/12.3020204.\nNicholas W.M. Ritchie, Dale E. Newbury, and Jeffrey M. Davis. Eds measurements of x-ray intensity at wds precision and accuracy using a silicon drift detector. Microscopy and Microanalysis, 18:892-904, Jul 2012. URL: https://doi.org/10.1017/s1431927612001109, doi:10.1017/s1431927612001109.\nDale E. Newbury. Electron-excited energy dispersive x-ray spectrometry at high speed and at high resolution: silicon drift detectors and microcalorimeters. Microscopy and Microanalysis, 12:527-537, Oct 2006. URL: https://doi.org/10.1017/s1431927606060673, doi:10.1017/s1431927606060673.\nVasile-Dan Hodoroaba and Mathias Procop. A method to test the performance of an energy-dispersive x-ray spectrometer (eds). Microscopy and Microanalysis, 20:1556-1564, Jul 2014. URL: https://doi.org/10.1017/s1431927614001652, doi:10.1017/s1431927614001652.\nG. Calzolai, S. Tapinassi, M. Chiari, M. Giannoni, S. Nava, G. Pazzi, and F. Lucarelli. Silicon drift detector response function for pixe spectra fitting. Feb 2018. URL: https://doi.org/10.1016/j.nimb.2017.09.010, doi:10.1016/j.nimb.2017.09.010.\nDale E. Newbury and Nicholas W. M. Ritchie. Elemental mapping of microstructures by scanning electron microscopy-energy dispersive x-ray spectrometry (sem-eds): extraordinary advances with the silicon drift detector (sdd). Journal of Analytical Atomic Spectrometry, 28:973-988, Jun 2013. URL: https://doi.org/10.1039/c3ja50026h, doi:10.1039/c3ja50026h.\nPJ Statham. X\u2010ray microanalysis with si (li) detectors. Unknown journal, 1981. URL: https://doi.org/10.1111/j.1365-2818.1981.tb01276, doi:10.1111/j.1365-2818.1981.tb01276.\nAndrea Vacchi. Silicon Drift Detectors, pages 609-661. Springer Nature Singapore, Jan 2024. URL: https://doi.org/10.1007/978-981-19-6960-7\\_18, doi:10.1007/978-981-19-6960-7\\_18.\nM. Miliucci, A. Scordo, D. Sirghi, A. Amirkhani, A. Baniahmad, M. Bazzi, D. Bosnar, M. Bragadireanu, M. Carminati, M. Cargnelli, A. Clozza, C. Curceanu, L. De Paolis, R R Del Grande, C. Fiorini, C. Guaraldo, M. Iliescu, M. Iwasaki, P. Levi Sandri, J. Marton, P. Moskal, F. Napolitano, S. Nied\u017awiecki, K. Piscicchia, F. Sgaramella, H. Shi, M. Silarski, F. Sirghi, M. Skurzok, A. Spallone, M. T\u00fcchler, O. V\u00e1zquez Doce, and J. Zmeskal. Silicon drift detectors system for high-precision light kaonic atoms spectroscopy. Measurement Science and Technology, 32:095501, May 2021. URL: https://doi.org/10.1088/1361-6501/abeea9, doi:10.1088/1361-6501/abeea9.\nM. Miliucci, M. Iliescu, F. Sgaramella, M. Bazzi, D. Bosnar, M. Bragadireanu, M. Carminati, M. Cargnelli, A. Clozza, C. Curceanu, G. Deda, L. De Paolis, R R Del Grande, C. Fiorini, C. Guaraldo, M. Iwasaki, P. King, P. Levi Sandri, J. Marton, P. Moskal, F. Napolitano, S. Nied\u017awiecki, K. Piscicchia, A. Scordo, H. Shi, M. Silarski, D. Sirghi, F. Sirghi, M. Skurzok, A. Spallone, M. T\u00fcchler, O. V\u00e1zquez Doce, and J. Zmeskal. Large area silicon drift detectors system for high precision timed x-ray spectroscopy. Jun 2022. URL: https://doi.org/10.1088/1361-6501/ac777a, doi:10.1088/1361-6501/ac777a.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Good, I have many relevant papers. Let me now search for more specific topics and start gathering evidence:",
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+                      "arguments": "{\"query\": \"EDS standard spectrum transferability detector response cross-instrument k-ratio Statham Fiori\"}",
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+                      "arguments": "{\"query\": \"EPMA electron probe microanalysis standards certified reference materials magnesium aluminium silicon\"}",
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+                    "id": "toolu_011WZDp8fnpXdE1hZ7xmFDjG",
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+                      "arguments": "{\"query\": \"AlSi10Mg additive manufacturing SEM-EDS composition quantification laser powder bed fusion\"}",
+                      "name": "paper_search"
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+              {
+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
+                "name": "paper_search",
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+                "content": "Retrieved Papers:\n## 1. X-ray Spectrometry.\nValid Text Names:\n'tsuji2010xrayspectrometry. pages 1-2', 'tsuji2010xrayspectrometry. pages 2-3', 'tsuji2010xrayspectrometry. pages 3-4', 'tsuji2010xrayspectrometry. pages 4-5', 'tsuji2010xrayspectrometry. pages 5-6', 'tsuji2010xrayspectrometry. pages 6-7', 'tsuji2010xrayspectrometry. pages 7-8', 'tsuji2010xrayspectrometry. pages 8-9', 'tsuji2010xrayspectrometry. pages 9-10', 'tsuji2010xrayspectrometry. pages 12-13', 'tsuji2010xrayspectrometry. pages 14-15', 'tsuji2010xrayspectrometry. pages 15-16', 'tsuji2010xrayspectrometry. pages 16-18', 'tsuji2010xrayspectrometry. pages 19-20', 'tsuji2010xrayspectrometry. pages 20-21', 'tsuji2010xrayspectrometry. pages 21-23', 'tsuji2010xrayspectrometry. pages 25-27', 'tsuji2010xrayspectrometry. pages 27-28', 'tsuji2010xrayspectrometry. pages 28-29', 'tsuji2010xrayspectrometry. pages 29-30', 'tsuji2010xrayspectrometry. pages 30-31', 'tsuji2010xrayspectrometry. pages 31-32', 'tsuji2010xrayspectrometry. pages 35-36', 'tsuji2010xrayspectrometry. pages 36-36', 'tsuji2010xrayspectrometry. pages 38-38'\n\nBibTex:\n@article{tsuji2010xrayspectrometry.,\n    author = \"Tsuji, Kouichi and Nakano, Kazuhiko and Takahashi, Yoshio and Hayashi, Kouichi and Ro, Chul-Un\",\n    title = \"X-ray Spectrometry.\",\n    year = \"2010\",\n    journal = \"Analytical chemistry\",\n    volume = \"82 12\",\n    pages = \"4950-87\",\n    doi = \"10.1021/ac101069d\",\n    url = \"https://doi.org/10.1021/ac101069d\",\n    month = \"May\",\n    publisher = \"American Chemical Society (ACS)\",\n    issue = \"12\",\n    issn = \"0003-2700\"\n}\n\n\nRelevant Snippet:\n\u2026 DTSA-II was developed in Java for a high level of platform independence and available free from the NIST \u2026 Scott and Ritchie (111) demonstrated that NISTMonte for the MC simulations \u2026\n\n\nUnobtainable Papers:\nNicholas W.M. Ritchie. Using dtsa-ii to simulate and interpret energy dispersive spectra from particles. Microscopy and Microanalysis, 16:248-258, Apr 2010. URL: https://doi.org/10.1017/s1431927610000243, doi:10.1017/s1431927610000243.\nP T Pinard and S Richter. Improving the quantification at high spatial resolution using a field emission electron microprobe. IOP Conference Series: Materials Science and Engineering, 55:012016, Mar 2014. URL: https://doi.org/10.1088/1757-899x/55/1/012016, doi:10.1088/1757-899x/55/1/012016.\nNicholas W. M. Ritchie. Efficient simulation of secondary fluorescence via nist dtsa-ii monte carlo. Microscopy and Microanalysis, 23:618-633, Mar 2017. URL: https://doi.org/10.1017/s1431927617000307, doi:10.1017/s1431927617000307.\nJuan P.N. Cruz, Carlos M. Garz\u00f3n, Johan K. Nore\u00f1a, Fabian Pineda, Juan. S. Cachaya, and Abel A.C. Recco. Accuracy of a reference-free monte carlo approach for sem-eds thickness assessment of tin coatings onto diverse substrates. Micron, 154:103204, Mar 2022. URL: https://doi.org/10.1016/j.micron.2021.103204, doi:10.1016/j.micron.2021.103204.\nDale E. Newbury and Nicholas W. M. Ritchie. Simulating electron-excited energy dispersive x-ray spectra with the nist dtsa-ii open-source software platform. MRS Advances, 7:892-898, Jun 2022. URL: https://doi.org/10.1557/s43580-022-00300-8, doi:10.1557/s43580-022-00300-8.\nNicholas W.M. Ritchie. Spectrum simulation in dtsa-ii. Microscopy and Microanalysis, 15:454-468, Sep 2009. URL: https://doi.org/10.1017/s1431927609990407, doi:10.1017/s1431927609990407.\nD. E. Pukhov. A comparison of the peak-to-background method and an empirical correction of the results in the energy-dispersive electron probe quantitative analysis of powder materials. Journal of Analytical Chemistry, 78:652-662, May 2023. URL: https://doi.org/10.1134/s1061934823050118, doi:10.1134/s1061934823050118.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=19 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Phase identification of microfeatures using EPMA methods, especially high-resolution X-ray spectroscopy\nValid Text Names:\n'love2001phaseidentificationof pages 1-2', 'love2001phaseidentificationof pages 2-3', 'love2001phaseidentificationof pages 3-6', 'love2001phaseidentificationof pages 6-7', 'love2001phaseidentificationof pages 7-11', 'love2001phaseidentificationof pages 11-14', 'love2001phaseidentificationof pages 14-14'\n\nBibTex:\n@article{love2001phaseidentificationof,\n    author = \"Love, G and Scott, V.D\",\n    title = \"Phase identification of microfeatures using EPMA methods, especially high-resolution X-ray spectroscopy\",\n    year = \"2001\",\n    journal = \"Micron\",\n    volume = \"32 2\",\n    pages = \"115-28\",\n    month = \"Feb\",\n    doi = \"10.1016/s0968-4328(00)00004-4\",\n    url = \"https://doi.org/10.1016/s0968-4328(00)00004-4\",\n    publisher = \"Elsevier BV\",\n    issue = \"2\",\n    issn = \"0968-4328\"\n}\n\n\nRelevant Snippet:\n\u2026 with negligible silicon and only a small amount of aluminium. \u2026 composite of magnesium alloy reinforced with silicon carbide \u2026 effects; standards of silicon carbide and silica were prepared \u2026\n\n\nUnobtainable Papers:\nAndy Fisher, Phill S. Goodall, Michael W. Hinds, Simon M. Nelms, and Denise M. Penny. Atomic spectrometry update . industrial analysis : metals , chemicals and advanced materials. Journal of Analytical Atomic Spectrometry, 18:1497, Jan 2005. URL: https://doi.org/10.1039/c2ja90058k, doi:10.1039/c2ja90058k.\nS. Timmerman, S. Matveev, M.U. Gress, and G.R. Davies. A methodology for wavelength dispersive electron probe microanalysis of unpolished silicate minerals. Journal of Geochemical Exploration, 159:243-251, Dec 2015. URL: https://doi.org/10.1016/j.gexplo.2015.09.016, doi:10.1016/j.gexplo.2015.09.016.\nNirmalya Karar and Vipin Jain. Alloys as Certified Reference Materials (CRMs), pages 697-730. Springer Nature Singapore, Jan 2023. URL: https://doi.org/10.1007/978-981-99-2074-7\\_33, doi:10.1007/978-981-99-2074-7\\_33.\nJustyna Kostrzewa, Jacek Anyszkiewicz, Tadeusz Gorewoda, Ewa Jamroz, Kjell Blandhol, Alf Yngve Guldhav, Magdalena Knapik, Jadwiga Charasi\u0144ska, and Agata Jak\u00f3bik-Kolon. Development of new series of certified reference materials for ferrosilicon magnesium alloys. Processes, 12:1017, May 2024. URL: https://doi.org/10.3390/pr12051017, doi:10.3390/pr12051017.\nYuanze Wang, Dayi Yang, Hongshi Zhao, Chao Liu, Feng He, Yingliang Tian, and Zhiyong Zhao. Synergistic enhancement of transparent magnesium\u2013aluminium\u2013silicon glass-ceramic containing alkali-free nanocrystalline phase: effects of crystallisation and ion exchange. Jun 2026. URL: https://doi.org/10.1016/j.jeurceramsoc.2025.118060, doi:10.1016/j.jeurceramsoc.2025.118060.\nR. B. Marinenko and D. H. Blackburn. Glasses for microanalysis : new nbs (u.s.a.) standard reference materials. Le Journal De Physique Colloques, 45:C2-769-C2-774, Feb 1984. URL: https://doi.org/10.1051/jphyscol:19842177, doi:10.1051/jphyscol:19842177.\nKurt F.J. Heinrich and Dale E. Newbury. Electron Probe X-Ray Microanalysis, pages 516-535. ASM International, Jan 1986. URL: https://doi.org/10.31399/asm.hb.v10.a0001768, doi:10.31399/asm.hb.v10.a0001768.\nXiangfa Liu, Jinguo Qiao, Yuying Wu, Xiangjun Liu, and Xiufang Bian. Epma analysis of calcium-rich compounds in near eutectic al\u2013si alloys. Journal of Alloys and Compounds, 388:83-90, Feb 2005. URL: https://doi.org/10.1016/j.jallcom.2004.07.012, doi:10.1016/j.jallcom.2004.07.012.\nV. D. Scott and G. Love. Epma using low-energy (0.1-1.0 kev) x-rays-an historical perspective. Journal of Analytical Atomic Spectrometry, 14:367-376, Jan 1999. URL: https://doi.org/10.1039/a806766j, doi:10.1039/a806766j.\nR. B. Marinenko. Standards for electron probe microanalysis. ArXiv, pages 251-260, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_14, doi:10.1007/978-1-4899-2617-3\\_14.\nOlga Yu. Belozerova, Mikhail A. Mikhailov, and Tamara V. Demina. Investigation of synthesized be-bearing silicate glass as laboratory reference sample at x-ray electron probe microanalysis of silicates. Spectrochimica Acta Part B: Atomic Spectroscopy, 127:34-41, Jan 2017. URL: https://doi.org/10.1016/j.sab.2016.11.007, doi:10.1016/j.sab.2016.11.007.\nM. Lovell, W. D. Ehmann, W. Markesbery, S. Melethil, C. Swyt, and P. Zatta. Standardization in biological analyses of aluminum: what are the needs? Journal of toxicology and environmental health, 48 6:637-48, Aug 1996. URL: https://doi.org/10.1080/009841096161113, doi:10.1080/009841096161113.\nValentina G. Batanova, Alexander V. Sobolev, and Dmitry V. Kuzmin. Trace element analysis of olivine: high precision analytical method for jeol jxa-8230 electron probe microanalyser. Chemical Geology, 419:149-157, Dec 2015. URL: https://doi.org/10.1016/j.chemgeo.2015.10.042, doi:10.1016/j.chemgeo.2015.10.042.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=19 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Influence of silicon morphology on direct current plasma electrolytic oxidation process in AlSi10Mg alloy produced with laser powder bed fusion\nValid Text Names:\n'pezzato2022influenceofsilicon pages 1-2', 'pezzato2022influenceofsilicon pages 2-3', 'pezzato2022influenceofsilicon pages 3-4', 'pezzato2022influenceofsilicon pages 4-5', 'pezzato2022influenceofsilicon pages 5-8', 'pezzato2022influenceofsilicon pages 8-10', 'pezzato2022influenceofsilicon pages 10-13', 'pezzato2022influenceofsilicon pages 13-15', 'pezzato2022influenceofsilicon pages 15-16', 'pezzato2022influenceofsilicon pages 16-17', 'pezzato2022influenceofsilicon pages 17-17'\n\nBibTex:\n@article{pezzato2022influenceofsilicon,\n    author = \"Pezzato, L. and Gennari, C. and Franceschi, M. and Brunelli, K.\",\n    title = \"Influence of silicon morphology on direct current plasma electrolytic oxidation process in AlSi10Mg alloy produced with laser powder bed fusion\",\n    year = \"2022\",\n    journal = \"Scientific Reports\",\n    volume = \"12\",\n    month = \"Aug\",\n    doi = \"10.1038/s41598-022-18176-x\",\n    url = \"https://doi.org/10.1038/s41598-022-18176-x\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"1\",\n    issn = \"2045-2322\"\n}\n\n\nAbstract:\nIn this work, plasma electrolytic oxidation (PEO) process was applied on AlSi10Mg samples, produced with laser powder bed fusion (L-PBF), in the as printed condition and after different heat treatments, and, for comparison, on as-cast samples of AlSi10Mg. PEO process was performed in direct-current mode using high current densities and short time in a basic silicate electrolyte. For the first time, the effects of silicon morphology in L-PBF AlSi10Mg samples, in as printed condition and after different heat treatments, on the obtained PEO coating were investigated in terms of microstructure and corrosion properties. The microstructure of the substrate was characterized with optical and electron microscopy observations (optical microscopy OM, scanning electron microscopy SEM, and transmission electron microscopy TEM) and with X-ray diffraction (XRD). The analysis showed that heat treatments of annealing and solution treating modified the morphology and distribution of silicon in the samples obtained through L-PBF. The PEO coated samples were characterized with SEM, both on the surface and in the cross-section, and compositional analysis were performed with energy dispersive spectroscopy (EDS) analysis and elemental mapping. The coatings were also analyzed with XRD and the corrosion properties evaluated through electrochemical impedance spectroscopy (EIS) tests. Also microhardness tests were performed on the substrates and on the coatings. The microstructure of the coatings was strongly influenced by the silicon distribution. In particular, a non-uniform distribution of silicon and the presence of iron-rich intermetallic (obtained in the as-cast and solution treated samples) induced the formation of more porous and thinner coatings in comparison with the ones obtained in the as printed and annealed samples. The not-uniform silicon distribution produced a not-homogenous distribution of silicon into the coatings. The particular cellular structure of the as printed sample induced the formation of a coating with a higher amorphous fraction, in comparison with the ones produced on the other samples. The higher thickness and lower porosity of the coatings obtained on the annealed and as printed samples resulted in an increase of the corrosion resistance.\n\nRelevant Snippet:\n\u2026 coated samples were analyzed by SEM\u2013EDS to evaluate the \u2026 Analysis of PEO coatings. PEO coatings were produced \u2026 prepared by laser powder bed fusion additive manufacturing and \u2026\n\n\n---\n\n## 2. Gold, Silver, and Electrum Electroless Plating on Additively Manufactured Laser Powder-Bed Fusion AlSi10Mg Parts: A Review\nValid Text Names:\n'ashkenazi2021goldsilverand pages 1-2', 'ashkenazi2021goldsilverand pages 2-3', 'ashkenazi2021goldsilverand pages 3-6', 'ashkenazi2021goldsilverand pages 6-8', 'ashkenazi2021goldsilverand pages 8-10', 'ashkenazi2021goldsilverand pages 10-13', 'ashkenazi2021goldsilverand pages 13-17', 'ashkenazi2021goldsilverand pages 17-21', 'ashkenazi2021goldsilverand pages 21-23', 'ashkenazi2021goldsilverand pages 23-25', 'ashkenazi2021goldsilverand pages 25-26', 'ashkenazi2021goldsilverand pages 26-28'\n\nBibTex:\n@article{ashkenazi2021goldsilverand,\n    author = \"Ashkenazi, Dana and Inberg, Alexandra and Shacham-Diamand, Yosi and Stern, Adin\",\n    title = \"Gold, Silver, and Electrum Electroless Plating on Additively Manufactured Laser Powder-Bed Fusion AlSi10Mg Parts: A Review\",\n    year = \"2021\",\n    journal = \"THE Coatings\",\n    volume = \"11\",\n    pages = \"422\",\n    month = \"Apr\",\n    doi = \"10.3390/coatings11040422\",\n    url = \"https://doi.org/10.3390/coatings11040422\",\n    publisher = \"MDPI AG\",\n    issue = \"4\",\n    issn = \"2079-6412\"\n}\n\n\nAbstract:\nAdditive manufacturing (AM) revolutionary technologies open new opportunities and challenges. They allow low-cost manufacturing of parts with complex geometries and short time-to-market of products that can be exclusively customized. Additive manufactured parts often need post-printing surface modification. This study aims to review novel environmental-friendly surface finishing process of 3D-printed AlSi10Mg parts by electroless deposition of gold, silver, and gold\u2013silver alloy (e.g., electrum) and to propose a full process methodology suitable for effective metallization. This deposition technique is simple and low cost method, allowing the metallization of both conductive and insulating materials. The AlSi10Mg parts were produced by the additive manufacturing laser powder bed fusion (AM-LPBF) process. Gold, silver, and their alloys were chosen as coatings due to their esthetic appearance, good corrosion resistance, and excellent electrical and thermal conductivity. The metals were deposited on 3D-printed disk-shaped specimens at 80 and 90 \u00b0C using a dedicated surface activation method where special functionalization of the printed AlSi10Mg was performed to assure a uniform catalytic surface yielding a good adhesion of the deposited metal to the substrate. Various methods were used to examine the coating quality, including light microscopy, optical profilometry, XRD, X-ray fluorescence, SEM\u2013energy-dispersive spectroscopy (EDS), focused ion beam (FIB)-SEM, and XPS analyses. The results indicate that the developed coatings yield satisfactory quality, and the suggested surface finishing process can be used for many AM products and applications.\n\nRelevant Snippet:\n\u2026 Additive manufacturing has been used for various materials, \u2026 SEM-EDS analysis revealed that the AlSi10Mg disk-shaped \u2026 and the chemical composition of the AlSi10Mg powder. Next, \u2026\n\n\n---\n\n## 3. Effect of Build Orientation and Heat Treatment on Erosion Behavior of Al10SiMg Fabricated Using Laser Powder Bed Fusion\nValid Text Names:\n'angolkar2023effectofbuild pages 1-2', 'angolkar2023effectofbuild pages 2-4', 'angolkar2023effectofbuild pages 4-6', 'angolkar2023effectofbuild pages 6-7', 'angolkar2023effectofbuild pages 7-9', 'angolkar2023effectofbuild pages 9-11', 'angolkar2023effectofbuild pages 11-14', 'angolkar2023effectofbuild pages 14-16', 'angolkar2023effectofbuild pages 16-17', 'angolkar2023effectofbuild pages 17-18', 'angolkar2023effectofbuild pages 18-18'\n\nBibTex:\n@article{angolkar2023effectofbuild,\n    author = \"Angolkar, Pooja and Hussain, M. Manzoor\",\n    title = \"Effect of Build Orientation and Heat Treatment on Erosion Behavior of Al10SiMg Fabricated Using Laser Powder Bed Fusion\",\n    year = \"2023\",\n    journal = \"Tribology in Industry\",\n    volume = \"45\",\n    pages = \"561-578\",\n    month = \"Dec\",\n    doi = \"10.24874/ti.1470.04.23.06\",\n    url = \"https://doi.org/10.24874/ti.1470.04.23.06\",\n    publisher = \"Faculty of Engineering, University of Kragujevac\",\n    issue = \"4\",\n    issn = \"0354-8996\"\n}\n\n\nAbstract:\nLaser Powder Bed Fusion (LPBF) is a form of additive manufacturing that can directly make metal components and has begun to be employed in a variety of industrial situations. Moreover, the erosion characteristics of SLM-produced items have been documented relatively infrequently. In the current work, the erosion behavior of a heat-treated Al-Si-10% Mg alloy generated via laser powder bed fusion (LPBF) has been investigated. The samples were printed in three directions (horizontal (0o), vertical (90o), and inclined (45o) on the build platform using the Direct Metal Laser Sintering (DMLS) system (EOS M 290) machine. Al%Si-10%Mg samples were given treatment (T5, T6). Optical and scanning electron microscopes (SEM) were used to examine the microstructure under both printed and heat-treated conditions. Energy Dispersive Spectroscopy (EDS) and X-ray Diffraction (XRD) were used to investigate the alloy's elemental composition and compound production. The erosion test was executed in each of the three orientations, plus heat-treated samples and as-printed samples. The selected input parameters were impingement angle and flow velocity. The erosion rate was examined and contrasted across orientations for printed and heat-treated conditions to establish the best orientation. The post-eroded surface was analysed using SEM, EDS, and XRD to evaluate possible erosion processes. The key findings were: T5 heat-treated samples sustain well and have the least mass loss; Horizontal (0\u00b0) oriented samples undergo less erosion compared to other orientations; T6 heat-treated samples show maximum erosion on printed samples, and hence it is not recommended. T5 heat treatment is proven to be superior in providing high erosion resistance, followed by printed and T6 heat-treatment, respectively. The heat treatment effects are more significant than the orientation effects in determining the erosion resistance of the Al10SiMg alloy. The erosion mechanisms, such as ploughing, melting, and cratering, were identified.\n\nRelevant Snippet:\n\u2026 of the most popular commercial additive manufacturing (AM) processes is laser Powder Bed \u2026 and analysis are necessary to precisely characterise the erosion behaviour of AlSi10Mg \u2026\n\n\n---\n\n## 4. Manufacturability and microstructure of AlSi10Mg/SiC composites with different volume fractions of SiC using laser powder bed fusion\nValid Text Names:\n'conzelmann2026manufacturabilityandmicrostructure pages 1-2', 'conzelmann2026manufacturabilityandmicrostructure pages 2-4', 'conzelmann2026manufacturabilityandmicrostructure pages 4-6', 'conzelmann2026manufacturabilityandmicrostructure pages 6-9', 'conzelmann2026manufacturabilityandmicrostructure pages 9-12', 'conzelmann2026manufacturabilityandmicrostructure pages 12-13', 'conzelmann2026manufacturabilityandmicrostructure pages 13-14', 'conzelmann2026manufacturabilityandmicrostructure pages 14-15', 'conzelmann2026manufacturabilityandmicrostructure pages 15-15'\n\nBibTex:\n@article{conzelmann2026manufacturabilityandmicrostructure,\n    author = \"Conzelmann, Achim and Seifert, Hans J\u00fcrgen and Mozaffari-Jovein, Hadi\",\n    title = \"Manufacturability and microstructure of AlSi10Mg/SiC composites with different volume fractions of SiC using laser powder bed fusion\",\n    year = \"2026\",\n    journal = \"The International Journal of Advanced Manufacturing Technology\",\n    volume = \"142\",\n    pages = \"2215-2229\",\n    month = \"Dec\",\n    doi = \"10.1007/s00170-025-17075-5\",\n    url = \"https://doi.org/10.1007/s00170-025-17075-5\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"5-6\",\n    issn = \"0268-3768\"\n}\n\n\nAbstract:\n<jats:title>Abstract</jats:title>\n                  <jats:p>\n                    In the present study commercially available AlSi10Mg and SiC powders were mixed in a tumble mixer with resulting compositions of 5, 15 and 25 vol% SiC and processed using laser powder bed fusion. Different process parameters were used to manufacture samples which were characterized by various properties, such as porosity, microstructure and occurring phases to evaluate the manufacturability of the powder mixtures. The samples showed increasing porosity with lowered volumetric energy density and increasing SiC content. Relative densities of about 93.0% (25 vol% SiC), 94.5% (15 vol% SiC) and 98.5% (5 vol% SiC) respectively could be achieved. In addition, the correlation between the used energy density and the retained SiC particles in the samples was investigated. The quantity of retained SiC particles correlates negatively with the achievable density for all compositions, making compromises between these two properties necessary depending on the desired application. It is shown that SiC can get dissolved due to the high absorption of the laser energy resulting in the formation of primary silicon crystals as well as Al\n                    <jats:sub>4</jats:sub>\n                    C\n                    <jats:sub>3</jats:sub>\n                    and Al\n                    <jats:sub>4</jats:sub>\n                    SiC\n                    <jats:sub>4</jats:sub>\n                    phases. Microstructure characterizations using AFM revealed the influence of the SiC fraction on the eutectic structure and the formation of the new phases. Finally, EDS and TOF-SIMS analysis showed that the formed Al\n                    <jats:sub>4</jats:sub>\n                    C\n                    <jats:sub>3</jats:sub>\n                    phase can react with the humidity of ambient air at the surface, leading to localized cracks due to AlOOH formation.\n                  </jats:p>\n\nRelevant Snippet:\n\u2026 available AlSi10Mg and SiC powders were mixed in a tumble mixer with resulting compositions \u2026 Further analysis of the laser interaction with SiC particles was conducted using pure SiC \u2026\n\n\nUnobtainable Papers:\nIndrajeet Katti, Duyao Zhang, Dong Qiu, Matthias Weiss, Joy H. Forsmark, and Mark Easton. The effect of the iso\u2010thermal heat treatment on the microstructure and properties of powder bed fusion\u2013laser beam alsi10mg alloy. Advanced Engineering Materials, May 2024. URL: https://doi.org/10.1002/adem.202400202, doi:10.1002/adem.202400202.\nIbrahim H. ZainElabdeen, Rehan Umer, Wesley J. Cantwell, James Weston, and Kamran A. Khan. Microstructure and elevated temperature mechanical properties of bimetal part fabricated by laser powder bed fusion of alsi10mg on rolled aa6061-t651. Aug 2025. URL: https://doi.org/10.1016/j.matdes.2025.114327, doi:10.1016/j.matdes.2025.114327.\nRabia Urkun and Dil\u015fad Akg\u00fcm\u00fc\u015f G\u00f6k. Alsi10mg honeycomb lattices produced by laser powder bed fusion: mechanical, thermal, and microstructural performances. Journal of Sandwich Structures &amp; Materials, Jun 2025. URL: https://doi.org/10.1177/10996362251355388, doi:10.1177/10996362251355388.\nG. Di Egidio, C. Martini, J. B\u00f6rjesson, E. Ghassemali, L. Ceschini, and A. Morri. Dry sliding behavior of alsi10mg alloy produced by laser-based powder bed fusion: influence of heat treatment and microstructure. Mar 2023. URL: https://doi.org/10.1016/j.wear.2022.204602, doi:10.1016/j.wear.2022.204602.\nElisa Padovano, Claudio Badini, Anna Pantarelli, Flavia Gili, and Fabio D\u2019Aiuto. A comparative study of the effects of thermal treatments on alsi10mg produced by laser powder bed fusion. Journal of Alloys and Compounds, 831:154822, Aug 2020. URL: https://doi.org/10.1016/j.jallcom.2020.154822, doi:10.1016/j.jallcom.2020.154822.\nPeidong He, Richard F. Webster, Jamie J. Kruzic, and Xiaopeng Li. Microstructural evolution and mechanical properties of co-modified alsi10mg alloy fabricated via in-situ alloying in laser powder bed fusion. Materials &amp; Design, 268:116580, Aug 2026. URL: https://doi.org/10.1016/j.matdes.2026.116580, doi:10.1016/j.matdes.2026.116580.\nJiyuan Zhang, Yong Yang, Qiuju Zheng, Shiwei Wu, Wenhou Wei, and Shoufeng Yang. Effect of nitrogen concentration on microstructure and mechanical properties of alsi10mg matrix composites fabricated by laser powder bed fusion. Virtual and Physical Prototyping, Jan 2026. URL: https://doi.org/10.1080/17452759.2025.2609346, doi:10.1080/17452759.2025.2609346.\nM. Srinivas, D. Pandey, TS Prasad, S. Purushothaman, and M. Sankar. Comparative tribological studies of additive manufactured as-built and chemically polished alsi10mg alloy surfaces. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 239:789-806, Aug 2025. URL: https://doi.org/10.1177/13506501241276243, doi:10.1177/13506501241276243.\nHan Liu, Minheng Ye, Zuoyan Ye, Lili Wang, Guowei Wang, Xianfeng Shen, Ping Xu, and Chao Wang. High-quality surface smoothening of laser powder bed fusion additive manufacturing alsi10mg via intermittent electrochemical polishing. Aug 2022. URL: https://doi.org/10.1016/j.surfcoat.2022.128608, doi:10.1016/j.surfcoat.2022.128608.\nJunchao Yi, Xiaowei Zhang, Guozheng Liu, Jeremy Heng Rao, and Han Liu. Microstructure and dynamic microhardness of additively manufactured (tib2+tic)/alsi10mg composites with alsi10mg and b4c coated ti powder. Journal of Alloys and Compounds, 939:168718, Apr 2023. URL: https://doi.org/10.1016/j.jallcom.2023.168718, doi:10.1016/j.jallcom.2023.168718.\nZhen Zhang, Zhanyong Zhao, Xiaofeng Li, Beibei Wang, and Peikang Bai. Effect of direct aging on corrosion behavior of alsi10mg alloy fabricated by laser powder bed fusion. Acta Metallurgica Sinica (English Letters), 37:266-282, Nov 2024. URL: https://doi.org/10.1007/s40195-023-01628-2, doi:10.1007/s40195-023-01628-2.\nAmir Hadadzadeh, Babak Shalchi Amirkhiz, Sajad Shakerin, Josh Kelly, Jian Li, and Mohsen Mohammadi. Microstructural investigation and mechanical behavior of a two-material component fabricated through selective laser melting of alsi10mg on an al-cu-ni-fe-mg cast alloy substrate. Additive Manufacturing, 31:100937, Jan 2020. URL: https://doi.org/10.1016/j.addma.2019.100937, doi:10.1016/j.addma.2019.100937.\nNancy Huang, Qixiang Luo, Dean L. Bartles, Timothy W. Simpson, and Allison M. Beese. Effect of heat treatment on microstructure and mechanical properties of alsi10mg fabricated using laser powder bed fusion. Mar 2024. URL: https://doi.org/10.1016/j.msea.2024.146228, doi:10.1016/j.msea.2024.146228.\nL. Pezzato, M. Dabal\u00e0, Silvia Gross, and K. Brunelli. Effect of microstructure and porosity of alsi10mg alloy produced by selective laser melting on the corrosion properties of plasma electrolytic oxidation coatings. Surface & Coatings Technology, 404:126477, Dec 2020. URL: https://doi.org/10.1016/j.surfcoat.2020.126477, doi:10.1016/j.surfcoat.2020.126477.\nT. M. Nandakishor, T. Stoll, and E.A. J\u00e4gle. Coupled thermodynamic and microstructural mechanisms governing interfacial cracking in hybrid pbf-lb/m of alsi10mg onto aa2017 substrate. Jul 2026. URL: https://doi.org/10.1016/j.matchar.2026.116502, doi:10.1016/j.matchar.2026.116502.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=19 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Now let me gather evidence from the most relevant papers and search for more specific topics:",
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+                      "arguments": "{\"question\": \"What metadata must accompany an EDS standard spectrum for k-ratio quantification? What are the requirements listed in Goldstein et al. for standards in SEM-EDS quantification?\"}",
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+                      "arguments": "{\"query\": \"NIST standard reference materials SRM microanalysis electron probe 481 482 470 K-glass\"}",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000000\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 11-13'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt lists the metadata and requirements that must accompany EDS standard spectra for rigorous k-ratio quantification. Standard spectra must be measured and archived with known, reproducible beam energy and electron dose (beam current \u00d7 detector live time), and with documented EDS operating conditions (time constant/resolution, detector-to-specimen distance and detector active area/solid angle, detector take-off and azimuthal angles, and specimen tilt\u2014preferably zero). A calibrated beam-current measurement (Faraday cup + digital picoammeter) is required for a fully rigorous protocol, and a conservative beam current that yields roughly 10% detector deadtime is recommended to minimize pulse coincidence. Sample and standard surface condition must be controlled: highly polished, not chemically etched, and for low-energy lines surface roughness should be <50 nm rms. Standards may be co-mounted or prepared on separate mounts; they must have accurately known composition and be homogeneous at the micrometer scale. Finally, archived standard spectra can be reused only if a quality-assurance check confirms the unknown was measured under the same documented conditions (beam energy, dose, and EDS parameters), and high-count, stable peak-shape spectra are needed for robust peak fitting (MLLS) in severe overlap situations.\n\n\n---\n\n## pqac-00000001\n\nFrom text 'tong2026measurementuncertaintiesof pages 21-24'.\n\nV. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.\n\nThe excerpt lists the experimental requirements and metadata that should accompany an EDS standard spectrum used for k-ratio (standards-based) quantification. Key metadata/requirements include: identity and composition of the standard (single pure-element standard for each element; chemically similar standards where possible), flat polished sample/standard surface and homogeneity through the interaction volume, SEM accelerating voltage (electron energy \u2265 1.8 \u00d7 the X\u2011ray peak energy for elements of interest), sample orientation (surface normal to beam and ~35\u00b0 to the EDX detector), energy-scale calibration details (e.g., per ISO 22309:2011 using Al and Cu standards), beam current and detector-geometry calibration (e.g., \u2018Quant Optimisation\u2019 in Aztec), and a stable electron beam current. Also important are factory-supplied matrix correction data from comparable elemental standards and acquiring standards under the same experimental session to cancel dependence on beam current, geometry and chamber contamination. The excerpt does not contain the text of Goldstein et al. or their explicit checklist, so requirements specifically attributed to Goldstein et al. are not present here.\n\n\n---\n\n## pqac-00000002\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 2-4'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt specifies the experimental metadata that must accompany EDS standards used for k\u2011ratio/matrix quantification: the specimen surface condition (highly polished; avoid chemical etching because it produces topography that alters X\u2011ray intensities), the beam energy, the known dose (beam current and detector live time), the beam incidence angle, the detector elevation or \"take\u2011off\" angle, and detector efficiency (e.g., constant detector\u2011to\u2011target distance to keep solid angle constant). It also emphasizes that standards should be archived and recalled as needed (stability of EDS), and that certified reference materials (e.g., NIST SRMs) and materials confirmed to be homogeneous on the micrometer scale are appropriate standards. The excerpt does not present a separate, explicit list attributed to Goldstein et al.; the listed metadata and standard requirements above are those provided in this text.\n\n\n---\n\n## pqac-00000003\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 2-3'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe provided excerpt does not give an explicit checklist of metadata that must accompany an EDS standard spectrum for k\u2011ratio quantification, but it does cite key requirements for standards (Goldstein et al., 1975) used in a standards\u2011based k\u2011ratio protocol with matrix corrections. Those requirements include: (1) the standard's overall (bulk) composition must be measured by independent methods; (2) microscopic homogeneity must be established (by EPMA in the cited work); and (3) when pure elements are incompatible with vacuum or suffer electron\u2011beam damage, stoichiometric compounds (e.g., CaF2, GaP, FeS2 for S) are used instead. The text defines the \u201ctrue value\u201d as the concentration known from independent analysis and uses the relative deviation (RDEV) from expected values as the figure of merit for EPMA results. While instrument/measurement metadata (beam energy, detector type, acquisition conditions) are discussed elsewhere in the paper (e.g., analytical beam energy choices), the excerpt itself does not enumerate a formal metadata package that must accompany an EDS standard spectrum for k\u2011ratio quantification.\n\n\n---\n\n## pqac-00000004\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 9-11'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt documents examples of k-ratio protocol use and gives several experimental/metadata items shown alongside EDS standard spectra. Example spectra and k-ratio analysis were collected at a specified beam energy (E0 = 20 keV) using SDD-EDS (a four-detector array) with measured deadtime varying from 2% to 77%. The text emphasizes detector-related metadata (detector type: SDD-EDS; operating temperature ~-20 \u00b0C) and demonstrates that peak shapes and calibration remain stable over large input count rate ranges, which is important for reliable k-ratio fitting. For non-conductive standards and unknowns, the excerpt states a specimen must be coated and grounded, recommending a carbon coating 8\u201310 nm thick, and warns that differences in coating thickness between unknown and standards can introduce significant error (especially at low beam energies). The excerpt refers to Table 5 for k-ratio protocol analysis but does not reproduce a complete checklist of metadata or the requirements from Goldstein et al.; those Goldstein-specific requirements are not present on these pages.\n\n\n---\n\n## pqac-00000005\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 1-2'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt explains the k-ratio quantification principle: k = Iunknown/Istandard, where the characteristic X-ray peak intensity must be measured under identical conditions (\"measured under identical conditions of beam energy, known dose, and detector efficiency for both\") so detector efficiency and other instrumental factors cancel. It also states that standards need not closely match unknown composition and gives acceptable standard types: pure elements and stoichiometric compounds for elements that are gaseous in vacuum, highly reactive, beam-sensitive, or low melting (examples: MgO for O; KCl for K and Cl; FeS2 for S; GaP for Ga and P). The conversion from k-ratios to concentrations uses matrix correction factors Ci/Cstd = k i Z A F c, with Z, A, F, and c defined as corrections for electron scattering/energy loss, X-ray self-absorption, and secondary X-ray emission/continuum. The excerpt does not provide a detailed checklist of metadata fields that must accompany an EDS standard spectrum nor the explicit Goldstein et al. requirements; it provides only these operational and standard-selection points relevant to k-ratio measurement.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=19 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. SEM-EDS nanoanalysis of mineral composite materials: A Monte Carlo approach\nValid Text Names:\n'moro2021semedsnanoanalysisof pages 1-6', 'moro2021semedsnanoanalysisof pages 6-9', 'moro2021semedsnanoanalysisof pages 9-13', 'moro2021semedsnanoanalysisof pages 13-18', 'moro2021semedsnanoanalysisof pages 18-24', 'moro2021semedsnanoanalysisof pages 24-27', 'moro2021semedsnanoanalysisof pages 27-27'\n\nBibTex:\n@misc{moro2021semedsnanoanalysisof,\n    author = \"Moro, Daniele and Ulian, Gianfranco and Valdr\u00e8, Giovanni\",\n    title = \"SEM-EDS nanoanalysis of mineral composite materials: A Monte Carlo approach\",\n    year = \"2021\",\n    journal = \"Composite Structures\",\n    volume = \"259\",\n    pages = \"113227\",\n    month = \"Mar\",\n    doi = \"10.1016/j.compstruct.2020.113227\",\n    url = \"https://doi.org/10.1016/j.compstruct.2020.113227\",\n    publisher = \"Elsevier BV\",\n    issn = \"0263-8223\"\n}\n\n\nRelevant Snippet:\n\u2026 and Berger\u2019s tabulated partial and total cross-sections for \u2026 to-detector distance was set to 45 mm, the detector elevation \u2026 , because of the excitation of silicon belonging to the quartz matrix\u2026\n\n\nUnobtainable Papers:\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Dtsa-ii eds software. ArXiv, pages 235-264, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_17, doi:10.1007/978-1-4939-6676-9\\_17.\nDaniele Moro, Gianfranco Ulian, and Giovanni Valdr\u00e8. Fibre-reinforced geopolymer composites micro-nanochemistry by sem-eds simulations. Journal of Composites Science, 5:214, Aug 2021. URL: https://doi.org/10.3390/jcs5080214, doi:10.3390/jcs5080214.\nAdrien Teurtrie, Nathana\u00ebl Perraudin, Thomas Holvoet, Hui Chen, Duncan T.L. Alexander, Guillaume Obozinski, and C\u00e9cile H\u00e9bert. Espm: a python library for the simulation of stem-edxs datasets. Ultramicroscopy, 249:113719, Mar 2023. URL: https://doi.org/10.1016/j.ultramic.2023.113719, doi:10.1016/j.ultramic.2023.113719.\nMathias Procop and Ralf Terborg. Measurement and calculation of x-ray production efficiencies for copper, zirconium, and tungsten. Dec 2022. URL: https://doi.org/10.1017/s1431927622012351, doi:10.1017/s1431927622012351.\nNicholas W.M. Ritchie, Dale E. Newbury, and Abigail P. Lindstrom. Compton scattering artifacts in electron excited x-ray spectra measured with a silicon drift detector. Microscopy and Microanalysis, 17:903-910, Nov 2011. URL: https://doi.org/10.1017/s1431927611012189, doi:10.1017/s1431927611012189.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=20 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=19 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                      "arguments": "{\"query\": \"Newbury Ritchie low beam energy 5 keV EDS quantification accuracy light elements\"}",
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+                    "id": "toolu_0149CeGrCA7aqnBbiWjDaKmk",
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+                      "arguments": "{\"query\": \"NIST DTSA-II simulated spectrum detector response model accuracy comparison measured spectrum\"}",
+                      "name": "paper_search"
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+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Exploring the limits of EDS microanalysis: rare earth element analyses\nValid Text Names:\n'ritchie2018exploringthelimits pages 1-4', 'ritchie2018exploringthelimits pages 4-5', 'ritchie2018exploringthelimits pages 5-7', 'ritchie2018exploringthelimits pages 7-9', 'ritchie2018exploringthelimits pages 9-11', 'ritchie2018exploringthelimits pages 11-11'\n\nBibTex:\n@article{ritchie2018exploringthelimits,\n    author = \"Ritchie, N W M and Newbury, D E and Lowers, H and Mengason, M\",\n    title = \"Exploring the limits of EDS microanalysis: rare earth element analyses\",\n    year = \"2018\",\n    journal = \"IOP Conference Series: Materials Science and Engineering\",\n    volume = \"304\",\n    pages = \"012013\",\n    month = \"Aug\",\n    doi = \"10.1088/1757-899x/304/1/012013\",\n    url = \"https://doi.org/10.1088/1757-899x/304/1/012013\",\n    publisher = \"IOP Publishing\",\n    issn = \"1757-8981\"\n}\n\n\nAbstract:\nIt is a great time to be a microanalyst. After a few decades of incremental progress in energy-dispersive X-ray spectrometry (EDS), the last decade has seen the accuracy and precision surge forward. Today, the question is not whether EDS is generally useful but to identify the types of problems for which wavelength-dispersive X-ray spectrometry remains the better choice. The full extent of EDS\u2019s capabilities has surprised many. Low Z, low energy, and trace element detection have been demonstrated even in the presence of extreme peak interferences. In this paper, we will summarise the state-of-the-art and investigate a challenging problem domain, the analysis of minerals bearing multiple rare-earth elements.\n\nRelevant Snippet:\n\u2026 like major element interferences, light elements, trace elements, and low beam energy \u2026 both the 1 keV to 2.5 keV range and the 5 keV to 10 keV range suggests that all significant \u2026\n\n\n---\n\n## 2. Comprehensive Quantitative Elemental Microanalysis with Electron-Excited Energy Dispersive X-ray Spectrometry (EDS): 50 Years Young and Getting Better Every Day!\nValid Text Names:\n'newbury2018comprehensivequantitativeelemental pages 1-2'\n\nBibTex:\n@article{newbury2018comprehensivequantitativeelemental,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Comprehensive Quantitative Elemental Microanalysis with Electron-Excited Energy Dispersive X-ray Spectrometry (EDS): 50 Years Young and Getting Better Every Day!\",\n    year = \"2018\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"24\",\n    pages = \"712-713\",\n    month = \"Aug\",\n    doi = \"10.1017/s1431927618004051\",\n    url = \"https://doi.org/10.1017/s1431927618004051\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"S1\",\n    issn = \"1431-9276\"\n}\n\n\nRelevant Snippet:\n\u2026 that EDS requires a factor of 10 to 250 lower dose (beam \u2026 the same count precision, depending on the photon energy being \u2026 Low beam energy microanalysis (1 keV \u2264 E0 \u2264 5 keV) \u2026\n\n\n---\n\n## 3. Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\nValid Text Names:\n'goldstein2018energydispersivexray pages 1-2', 'goldstein2018energydispersivexray pages 2-4', 'goldstein2018energydispersivexray pages 4-6', 'goldstein2018energydispersivexray pages 6-7', 'goldstein2018energydispersivexray pages 7-9', 'goldstein2018energydispersivexray pages 9-10', 'goldstein2018energydispersivexray pages 10-11', 'goldstein2018energydispersivexray pages 11-14', 'goldstein2018energydispersivexray pages 14-15', 'goldstein2018energydispersivexray pages 15-16', 'goldstein2018energydispersivexray pages 16-18', 'goldstein2018energydispersivexray pages 18-20', 'goldstein2018energydispersivexray pages 20-22', 'goldstein2018energydispersivexray pages 22-25', 'goldstein2018energydispersivexray pages 25-26'\n\nBibTex:\n@article{goldstein2018energydispersivexray,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"209-234\",\n    doi = \"10.1007/978-1-4939-6676-9\\_16\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_16\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nAs illustrated in Fig. 16.1, the physical basis of energy dispersive X-ray spectrometry (EDS) with a semiconductor detector begins with photoelectric absorption of an X-ray photon in the active volume of the semiconductor (Si). The entire energy of the photon is transferred to a bound inner shell atomic electron, which is ejected with kinetic energy equal to the photon energy minus the shell ionization energy (binding energy), 1.838 keV for the Si K-shell and 0.098 keV for the Si L-shell. The ejected photoelectron undergoes inelastic scattering within the Si crystal. One of the consequences of the energy loss is the promotion of bound outer shell valence electrons to the conduction band of the semiconductor, leaving behind positively charged \u201choles\u201d in the valence band. In the conduction band, the free electrons can move in response to a potential applied between the entrance surface electrode and the back surface electrode across the thickness of the Si crystal, while the positive holes in the conduction band drift in the opposite direction, resulting in the collection of electrons at the anode on the back surface of the EDS detector. This charge generation process requires approximately 3.6 eV per electron hole pair, so that the number of charge carriers is proportional to the original photon energy, Ep: \n \n$$ n={E}_p/3.6\\ eV $$ \n \nFor a Mn K-L3 photon with an energy of 5.895 keV, approximately 1638 electron\u2013hole pairs are created, comprising a charge of 2.6 \u00d7 10\u221216 coulombs. Because the detector can respond to any photon energy from a threshold of approximately 50 eV to 30 keV or more, the process has been named \u201cenergy dispersive,\u201d although in the spectrometry sense there is no actual dispersion such as occurs in a diffraction element spectrometer.\n\nRelevant Snippet:\n\u2026 energy of 1.559 keV, a modest beam energy of 15 keV provides \u2026 and as a result the precision of quantitative analysis is also \u2026 of microparticles, low beam energy analysis, or another \u2026\n\n\nUnobtainable Papers:\nK. SCOTT and N.W.M. RITCHIE. Analysis of 3d elemental mapping artefacts in biological specimens using monte carlo simulation. Journal of Microscopy, 233:331-339, Feb 2009. URL: https://doi.org/10.1111/j.1365-2818.2009.03124.x, doi:10.1111/j.1365-2818.2009.03124.x.\nDale E. Newbury and Nicholas W. M. Ritchie. Quantitative x-ray microanalysis of low atomic number elements by sem/sdd-eds with nist dtsa ii: carbides and nitrides and oxides, oh my! Microscopy and Microanalysis, 20:702-703, Aug 2014. URL: https://doi.org/10.1017/s1431927614005236, doi:10.1017/s1431927614005236.\nPhilippe T Pinard, Simon Burgess, John Qing Zhang, and Peter J Statham. Characterization and customization of individual eds detectors to improve x-ray microanalysis of light elements. Microscopy and Microanalysis, Jul 2024. URL: https://doi.org/10.1093/mam/ozae044.096, doi:10.1093/mam/ozae044.096.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=25 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Harnessing Automated SEM-EDS and Machine Learning to Unlock High-Throughput Compositional Characterization of Powder Materials\nValid Text Names:\n'giunto2025harnessingautomatedsemeds pages 1-4', 'giunto2025harnessingautomatedsemeds pages 4-6', 'giunto2025harnessingautomatedsemeds pages 6-7', 'giunto2025harnessingautomatedsemeds pages 7-10', 'giunto2025harnessingautomatedsemeds pages 10-12', 'giunto2025harnessingautomatedsemeds pages 12-14', 'giunto2025harnessingautomatedsemeds pages 14-16', 'giunto2025harnessingautomatedsemeds pages 16-18', 'giunto2025harnessingautomatedsemeds pages 18-20', 'giunto2025harnessingautomatedsemeds pages 20-22', 'giunto2025harnessingautomatedsemeds pages 22-23', 'giunto2025harnessingautomatedsemeds pages 23-25', 'giunto2025harnessingautomatedsemeds pages 25-28', 'giunto2025harnessingautomatedsemeds pages 28-29', 'giunto2025harnessingautomatedsemeds pages 29-32', 'giunto2025harnessingautomatedsemeds pages 32-36', 'giunto2025harnessingautomatedsemeds pages 36-37'\n\nBibTex:\n@article{giunto2025harnessingautomatedsemeds,\n    author = \"Giunto, Andrea and Fei, Yuxing and Nevatia, Pragnay and Rendy, Bernardus and Szymanski, Nathan and Ceder, Gerbrand\",\n    title = \"Harnessing Automated SEM-EDS and Machine Learning to Unlock High-Throughput Compositional Characterization of Powder Materials\",\n    year = \"2025\",\n    journal = \"Unknown journal\",\n    month = \"Oct\",\n    doi = \"10.21203/rs.3.rs-7837297/v1\",\n    url = \"https://doi.org/10.21203/rs.3.rs-7837297/v1\",\n    publisher = \"Springer Science and Business Media LLC\"\n}\n\n\nAbstract:\n<title>Abstract</title>\n                <p>Compositional characterization is essential for understanding and optimizing material performance. For powder-based materials, ubiquitous across diverse technologies, accurately resolving the composition of individual phases at high throughput remains an unsolved challenge. This bottleneck slows material research and is particularly acute for autonomous laboratories, where large numbers of samples are synthesized and AI decision-making algorithms demand low-uncertainty data. Here, we integrate measurement automation, data filtering, and unsupervised machine learning to deliver a fully automated framework for high-throughput, phase-resolved compositional analysis of as-deposited powders using scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS). Our approach, implemented in the Python-based software AutoEMXSp, overcomes geometry-induced artifacts from irregular particle morphologies and enables accurate compositional quantification using only one experimental standard per element\u2014including light elements conventionally difficult to quantify in powders. Validated across 74 powder samples with elements spanning nitrogen to bismuth, AutoEMXSp consistently estimates compositions within 5\u201310% of their expected values and resolves minor or intermixed phases with high confidence. By delivering a robust, operator-free, high-throughput framework, this work paves the way for integration of powder compositional characterization into autonomous laboratory platforms, accelerating the pace of materials discovery and development.</p>\n\nRelevant Snippet:\n\u2026 -based EDS quantification with a single set of experimen- 57 \u2026 overestimation of continuum X-rays at low energies 117 (E < \u2026 for detector incomplete charge collection (ICC), peak shapes \u2026\n\n\nUnobtainable Papers:\nDavid B. Williams and C. Barry Carter. X-ray spectra and images. ArXiv, pages 605-623, Jan 2009. URL: https://doi.org/10.1007/978-0-387-76501-3\\_33, doi:10.1007/978-0-387-76501-3\\_33.\nPeter J Statham. Measuring performance of energy-dispersive x-ray systems. Microscopy and Microanalysis, 4:605-615, Dec 1998. URL: https://doi.org/10.1017/s1431927698980588, doi:10.1017/s1431927698980588.\nC. E. LYMAN, J. I. GOLDSTEIN, D. B. WILLIAMS, D. W. ACKLAND, S. VON HARRACH, A. W. NICHOLLS, and P. J. STATHAM. High\u2010performance x\u2010ray detection in a new analytical electron microscope. Journal of Microscopy, 176(2):85-98, Nov 1994. URL: https://doi.org/10.1111/j.1365-2818.1994.tb03503.x, doi:10.1111/j.1365-2818.1994.tb03503.x.\nLucia Spasevski, Simon Burgess, Philippe T Pinard, John Qing Zhang, and Katherine MacArthur. Advances in individual detector characterization and key parameters that affect modern eds performance. Microscopy and Microanalysis, Jul 2025. URL: https://doi.org/10.1093/mam/ozaf048.241, doi:10.1093/mam/ozaf048.241.\nDavid B. Williams and C. Barry Carter. X-ray Spectrometry, pages 581-603. Springer US, Jan 2009. URL: https://doi.org/10.1007/978-0-387-76501-3\\_32, doi:10.1007/978-0-387-76501-3\\_32.\nAT Ellis. Energy-dispersive x-ray fluorescence analysis using x-ray tube excitation. ArXiv, pages 212-251, Nov 2002. URL: https://doi.org/10.1201/9780203908709-3, doi:10.1201/9780203908709-3.\nLucia Spasevski, Simon Burgess, Philippe Pinard, John Qing Zhang, and Katherine MacArthur. Challenges in measuring low concentration of overlapping elements with eds and need for verification with standard materials. Jul 2026. URL: https://doi.org/10.1093/mam/ozaf048.260, doi:10.1093/mam/ozaf048.260.\nNicolas Brodusch, Karim Zaghib, and Raynald Gauvin. Improvement of the energy resolution of energy dispersive spectrometers (eds) using richardson\u2013lucy deconvolution. Ultramicroscopy, 209:112886, Feb 2020. URL: https://doi.org/10.1016/j.ultramic.2019.112886, doi:10.1016/j.ultramic.2019.112886.\nPeter J. Statham. Recent developments in instrumentation for x-ray microanalysis. ArXiv, pages 1-9, Jan 1998. URL: https://doi.org/10.1007/978-3-7091-7506-4\\_1, doi:10.1007/978-3-7091-7506-4\\_1.\nPeter J. Statham. Pile-up correction for improved accuracy and speed of x-ray analysis. Microchimica Acta, 155:289-294, Apr 2006. URL: https://doi.org/10.1007/s00604-006-0558-1, doi:10.1007/s00604-006-0558-1.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=25 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (SEM/EDS) quantitative? Effect of specimen shape\nValid Text Names:\n'newbury2011isscanningelectron pages 1-2', 'newbury2011isscanningelectron pages 2-3', 'newbury2011isscanningelectron pages 3-7', 'newbury2011isscanningelectron pages 7-10', 'newbury2011isscanningelectron pages 10-13', 'newbury2011isscanningelectron pages 13-16', 'newbury2011isscanningelectron pages 16-16'\n\nBibTex:\n@article{newbury2011isscanningelectron,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Is scanning electron microscopy/energy dispersive x-ray spectroscopy (SEM/EDS) quantitative? Effect of specimen shape\",\n    year = \"2011\",\n    journal = \"SPIE Proceedings\",\n    volume = \"8036\",\n    pages = \"803602\",\n    month = \"May\",\n    doi = \"10.1117/12.881040\",\n    url = \"https://doi.org/10.1117/12.881040\",\n    publisher = \"SPIE\",\n    issn = \"0277-786X\"\n}\n\n\nRelevant Snippet:\n\u2026 count spectra of unknowns and standards, the most accurate \u2026 solution is to simulate the bulk reference spectrum from an \u2026 tool such as NIST DTSAII which calculates the spectrum on a \u2026\n\n\nUnobtainable Papers:\nNicholas W. M. Ritchie. Manipulating spectra with dtsa-ii. Microscopy Today, 19:34-39, Apr 2011. URL: https://doi.org/10.1017/s1551929511000290, doi:10.1017/s1551929511000290.\nNicholas W. M. Ritchie. Getting started with nist* dtsa-ii. Microscopy Today, 19:26-31, Jan 2011. URL: https://doi.org/10.1017/s155192951000132x, doi:10.1017/s155192951000132x.\nDale E. Newbury and Nicholas W. M. Ritchie. Measurement of trace constituents by electron-excited x-ray microanalysis with energy-dispersive spectrometry. Microscopy and Microanalysis, 22:520-535, May 2016. URL: https://doi.org/10.1017/s1431927616000738, doi:10.1017/s1431927616000738.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=25 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000006\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 20-21'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt shows DTSA-II simulated-standard analysis of NIST microanalysis glass K2496 (Table 11) producing concentrations very close to the as-synthesized values (example: 0.3230 vs 0.3197, 0.2291 vs 0.2256, 0.0180 vs 0.0176, 0.4299 vs 0.4371) with small relative errors (e.g., -1.0, -1.5, -2.4, 1.7 %) and small precision metrics (r relative (%) ~0.08\u20131.8 %). The authors emphasize an SDD-EDS measurement strategy (10 keV beam, deadtime \u224810 %, dose \u224810^7 counts) that yields high-count spectra and low detection limits; they recommend conservative counting to keep deadtime \u227210 % to avoid coincidence artifacts. The excerpt illustrates spectral interference issues (BaL\u03b1 vs TiK\u03b1 \u0394=41 eV; BaL\u03b23 vs TiK\u03b2 \u0394=4 eV) and shows that residual fitting can reveal low-level peaks masked by overlaps. Thus DTSA-II simulated spectra can give accurate quantification in well-controlled, high-count SDD-EDS measurements and can represent minor constituents within a few percent. The excerpt does not describe in detail how DTSA-II models detector effects such as incomplete charge collection, dead layer, or window transmission, nor does it fully enumerate failure modes beyond noted peak overlaps and deadtime/coincidence artifacts.\n\n\n---\n\n## pqac-00000007\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 11-13'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt shows that NIST DTSA-II, when used to process high-count, stable spectra and applied within a rigorous k-ratio protocol, can produce k-ratio determinations comparable to WDS and yield results within the EPMA/WDS error envelope (see Table 5 for sulfides at E0 = 20 keV). Achieving this performance requires strict measurement reproducibility: known beam energy, dose (electron current \u00d7 detector live time), fixed EDS parameters, and careful beam-current measurement (Faraday cup + picoammeter). A conservative operating strategy\u2014selecting beam current to give ~10% detector deadtime\u2014minimizes pulse coincidence, which becomes problematic above ~15% deadtime. High-count spectra with stable peak shape enable MLLS fitting to extract characteristic intensities even in severe peak overlap. The excerpt also notes practical failure modes for simulated/archived standards: standards must be homogeneous at the micrometer scale; sample surfaces must be highly polished (low topography, scratches < ~50 nm rms for low-energy X-rays); and at low beam energies (E0 \u2264 ~5 keV) differences in coating thickness between unknown and standards can introduce significant errors. The excerpt does not describe how DTSA-II models detector physics such as incomplete charge collection, detector dead layers, or window transmission.\n\n\n---\n\n## pqac-00000008\n\nFrom text 'newbury2011isscanningelectron pages 13-16'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\nThe excerpt states that NIST DTSA-II can be used to simulate a bulk reference EDS spectrum from an estimated composition using first-principles physics to yield absolute intensities. An example (bulk K411, E0 = 20 keV) compared measured and simulated spectra with no scaling; the summed characteristic peak plus background intensities differed by +1.2% (Fe K\u03b1) up to +19% (Mg K) in that case. The authors note that a simulated reference is useful when a flat, bulk reference of the same composition is unavailable, but requires an estimate of the composition (a first normalized analysis can serve as that estimate). The excerpt warns that anomalous absorption\u2014especially in the low-photon-energy region\u2014can cause large deviations from the ideal spectrum (notably for microscopic shards and irregular geometries), and that application of standard k-value/matrix corrections followed by normalization to such spectra can produce unacceptably large errors. The passage does not provide details on how DTSA-II implements detector-response effects such as incomplete charge collection, detector dead layer, or window transmission.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008]\n\nStatus: Paper Count=25 | Relevant Papers=4 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=9 | Current Cost=$0.0670 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000009\n\nFrom text 'tsuji2010xrayspectrometry. pages 9-10'.\n\nKouichi Tsuji, Kazuhiko Nakano, Yoshio Takahashi, Kouichi Hayashi, and Chul-Un Ro. X-ray spectrometry. Analytical chemistry, 82 12:4950-87, May 2010. URL: https://doi.org/10.1021/ac101069d, doi:10.1021/ac101069d. This article has 78 citations and is from a highest quality peer-reviewed journal.\n\nThe excerpt emphasizes that detailed, instrument-specific detector characterization is critical for FP-based XRF/EDS quantification. Key detector properties that must be known include absolute efficiency, energy resolution, and the precise shape of the detector response function. Scholze and Procop modelled EDS spectral response accounting for detector statistical and electronic noise, incomplete charge collection (which causes peak tailing), escape effects, and fluorescence from the front contact or dead layer\u2014all processes that alter peak shapes and continuum, particularly at low energies. An FP method that explicitly includes the energy-broadening response was used to predict peak-area ratios (KR fluorescence vs. scattered peaks), and the detector response curve was adjusted by matching theory to experiment. New SDDs with thin windows and improved electronics change throughput and low-energy sensitivity, and geometry/solid-angle differences further affect detected intensities. Taken together, these points indicate that uncorrected transfer of EDS standard spectra between different instruments/detectors is problematic unless detector-to-detector differences (resolution, window/dead layer absorption, incomplete charge collection, escape, response shape, and geometry) are modeled or empirically calibrated.\n\n\n---\n\n## pqac-00000010\n\nFrom text 'ritchie2018exploringthelimits pages 1-4'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nRelevant points from the excerpt for assessing transferability of EDS standard spectra and detector-to-detector effects on k-ratios (especially <2 keV): 1) EDS quantitation depends on integrating intensity over the same channel ranges on unknowns and standards: \"In the case of EDS, the intensity should be integrated over the same range of channels on the unknown and the standard.\" This implies standards and unknowns must be measured under consistent channel/binning and spectral-resolution conditions. 2) Detector physical differences matter: improvements and changes in \"dead layers trimmed,\" \"leakage currents\" and window materials affect low-energy X-ray transmission (\"These new window technologies permitted lower energy X-rays to reach the detector.\" and \"Some even, Li-K X-rays\"). 3) Resolution and peak shape affect peak integration and peak-to-background: \"Detector resolutions have improved.\"; \"The peak-to-background ratio on an EDS is determined by the ranges of channels used to estimate the continuum and peak intensity.\"; and the central FWHM holds \u224876% of peak intensity. 4) Limits of detection and k-ratios are constrained by the continuum vs signal: \"Ultimately, limits of detection are constrained by the magnitude of the background (continuum) level relative to the signal (characteristic) level.\" 5) By implication, differences in resolution, window transmission, dead layer and electronic performance between detectors will change observed peak shapes, background and low-energy sensitivity and thus will affect k-ratios for light elements below ~2 keV unless corrected or measured under matched conditions.\n\n\n---\n\n## pqac-00000011\n\nFrom text 'goldstein2018energydispersivexray pages 1-2'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\nThe excerpt describes the fundamental EDS detection physics and the principal measurement artifact relevant to low-energy X-rays. Photoelectric absorption in Si produces electron\u2013hole pairs (about 3.6 eV per pair), so the number of charge carriers (and statistical fluctuations) scales with photon energy. The EDS system builds a histogram of photon energies and has a usable energy range from about 0.05 keV to ~30 keV depending on detector design. The main artifact is peak broadening (the EDS resolution function): even sharply defined X-ray lines are broadened by statistical and detector contributions, and the measured FWHM is an energy-dependent function (a referenced equation is provided). The text contrasts older Si(Li) detectors with modern silicon drift detectors (SDD-EDS), implying detector design changes the detection characteristics. The table of contents also lists low-energy artifacts (Si-escape peak, Si absorption edge, internal fluorescence) that can affect spectra below a few keV. Together, these points indicate that detector-to-detector differences in resolution, efficiency and design will influence the measured peak shapes and low-energy response, which are the factors that would affect quantitative ratios for light elements.\n\n\n---\n\n## pqac-00000012\n\nFrom text 'newbury2011isscanningelectron pages 13-16'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\nThe excerpt describes using a \"remote-standards standardless\" approach in which a library of standard measurements made on another instrument supplies standard intensities; calculated corrections are applied for beam energy and spectrometer efficiency differences between instruments. However, no dose calibration is attempted, so the raw analytical total from such transferred standards has no validity and normalization is required\u2014thereby removing indicators of geometric or other deviations. The authors emphasize that the low-photon-energy region is particularly sensitive to anomalous absorption and spectrum-shape deviations; a measured-vs-simulated example for bulk K411 at 20 keV showed discrepancies ranging from +1.2% (FeK\u03b1) to +19% (MgK), illustrating larger uncertainties at low energies. Because a flat-bulk reference of the exact composition is often unavailable, the authors recommend simulating a bulk reference spectrum (e.g., with NIST DTSA-II) and using x-ray spectrum imaging (XSI) to locate favorable regions on rough specimens for analysis. The excerpt discusses spectrometer efficiency corrections but does not explicitly detail the separate effects of detector resolution, window, dead layer, or incomplete charge collection on k-ratios below 2 keV.\n\n\n---\n\n## pqac-00000013\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 11-13'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt states that SDD-EDS stability allows use of previously measured, stored standard spectra, provided a quality-assurance protocol confirms the unknown is measured under the same conditions as the archived standards (beam energy, dose, and EDS parameters). It emphasizes that spectra for unknowns and standards must be acquired under known, reproducible conditions including beam energy, electron dose/dead time, fixed time constant (resolution), detector-to-specimen distance (solid angle), detector take-off/azimuthal angles, and specimen tilt. A Faraday cup/digital picoammeter for beam current measurement is recommended for a rigorous k-ratio protocol. The authors recommend operating to yield ~10% detector deadtime to minimize pulse-coincidence (sum) peaks, noting coincidence grows significantly above ~15% deadtime; coincidence can still affect low-Z element peaks at high count rates. High-count spectra with stable peak shape and position improve MLLS peak fitting and thus k-ratio determination. The excerpt does not provide quantitative data on how detector-to-detector variations (resolution, window, dead layer, incomplete charge collection) specifically affect k-ratios for light elements below ~2 keV, so no direct numeric effects are given here.\n\n\n---\n\n## pqac-00000014\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 16-18'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses using a \u2018\u2018remote standards\u2019\u2019 approach and calibration transfer to address limitations of purely first\u2011principles (standardless) EDS quantification. It states that the remote standards method, tied to measurements of real materials, is inherently more accurate than first\u2011principles approaches. A practical calibration\u2011transfer technique mentioned is using a \u2018\u2018golden detector\u2019\u2019 (calibrated at a beamline) plus a carefully chosen reference material to transfer the calibration from that detector to other instruments (Alvisi et al., 2006). The text also notes that vendors often do not fully document their standardless implementations, leaving users uncertain about how numerical concentrations are derived. The paper includes low\u2011voltage (E0 = 5 keV) analyses and spectra (e.g., borides with B K\u2011L2,3 peak and YBa2Cu3O7 at 5 keV, and an EDS spectrum of BaCl2 at 5 keV), indicating attention to light\u2011element measurements at low energies. While the excerpt does not provide quantitative k\u2011ratio shifts caused by detector\u2011to\u2011detector differences (resolution, window, dead layer, incomplete charge collection), it implies such differences must be corrected via transferred calibration/standards to obtain accurate low\u2011energy (below ~2 keV) analyses.\n\n\n---\n\n## pqac-00000015\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 9-11'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt describes differences between silicon drift detectors (SDD-EDS) and older Si(Li)-EDS: SDDs operate around -20 \u00b0C (Peltier cooled) versus -190 \u00b0C for Si(Li), and their modified structure yields higher throughput and larger solid angle. Crucially, SDD-EDS shows nearly constant resolution (peak shape) and calibration (peak stability) across a wide range of input count rates, so peak shape and position used for fitting remain stable from major to trace peaks. This consistency allows assembling clusters of SDD detectors without significant degradation of the combined output. The figures and captions also illustrate spectral identification issues, e.g., misidentification of Pb M-family peaks in different materials and the close superposition of Mn K- and L-family peaks after scaling. While the text emphasizes improved stability and detector clustering for SDDs, it does not directly state how standard spectra transfer between different instruments or quantify detector-to-detector effects (window, dead layer, incomplete charge collection) on k-ratios for light elements below 2 keV.\n\n\n---\n\n## pqac-00000016\n\nFrom text 'ritchie2018exploringthelimits pages 4-5'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThe excerpt explains that in EDS the signals from multiple X-ray lines are integrated into a single measured peak and that each contributing line has slightly different matrix correction factors. For EDS this leads to a weighted matrix correction [ZAF]EDS computed from the individual transition weights (Wi) and their single-transition [ZAF]i values. Using complex or matrix-matched standards can reduce sensitivity to poorly known parameters because the ratio [ZAF]unk/[ZAF]std approaches unity. To handle peak interferences, DTSA-II uses additional spectra called peak-shape references \u201cwhich can be calibrated relative to the standard and fit to the unknown,\u201d and a \u201cStandard Bundle that sums standards and integrates the necessary peak-shape references.\u201d The text also notes that REE have complex L-line structures (tens of lines over a range of energies), which complicates WDS background placement but provides structure beneficial for EDS. Multiple acquisitions and summed standards are recommended to improve quality and reveal metrology issues. The authors\u2019 measurements used a multi-detector SDD setup (four independent 30 mm2 PulseTor SDDs), indicating multi-detector configurations are in practice.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016]\n\nStatus: Paper Count=25 | Relevant Papers=7 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=17 | Current Cost=$0.1059 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000017\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 17-20'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt emphasizes iterative, peak-fitting\u2013based analysis for detecting and quantifying trace elements in the presence of major-element interference. Peak fitting must include possible interfering peaks (example: TiKa/TiKb appearing in residuals when omitted); residual spectra should be inspected after stripping fitted peaks to reveal minor/trace constituents hidden beneath larger peaks. Residuals can also be used to estimate limits of detection, and detection limits may be lowered by accumulating more counts. Low-energy X-ray peaks are affected by chemical-shift and peak-shape \u2018\u2018chemical effects,\u2019\u2019 and EDS has significantly poorer spectral resolution than WDS, making interference correction more challenging for low-energy (low-Z) analyses. The text shows use of matrix-appropriate references and standards (e.g., \"Si and W as references and standards\" and \"using as standards elemental Mn and Ta, with sanbornite (BaSi2O5) for Si and Ba\") and examples where oxygen was set by stoichiometry. Together these points support strategies for low-kV EDS quantification: careful peak fitting including interfering major-element peaks, iterative re-analysis guided by residuals, increasing counts to improve detection limits, and using appropriate standards/matrix references.\n\n\n---\n\n## pqac-00000018\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 13-15'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nRelevant points for low-voltage (\u22485 keV) EDS quantification of trace Mg in an Al matrix: the incident beam energy must exceed the shell excitation energy (ideally by \u22651.25\u00d7), and 5 keV is effectively the lowest E0 that still excites at least one characteristic X-ray family for most elements. At E0 \u22645 keV, more elements become inaccessible and low-energy analysis increases the influence of surface layers and carbon contamination, which can change X-ray absorption. Trace measurements (C < 0.01) commonly involve peaks close to the continuum background and subject to overlap from much more intense major-element peaks; when a trace peak is buried under a major peak, the measurement challenge is substantially increased. Limits of detection (CDL) can be estimated from counts using CDL = [3NB1/2/(NS \u2212 NB)]CS, and practical LODs on suitably long counts can reach ~0.0002\u20130.0005 mass fraction (200\u2013500 ppm) depending on element and matrix. Mutual interferences can often be addressed with careful peak fitting. These points imply that for Mg-in-Al at 5 keV one should expect significant Al\u2013Mg overlap issues, require rigorous peak fitting and standards appropriate for low-kV geometry and surface/contamination effects, and use long counts to approach ppm-level detection.\n\n\n---\n\n## pqac-00000019\n\nFrom text 'tong2026measurementuncertaintiesof pages 8-11'.\n\nV. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.\n\nRelevant points for low\u2011kV (5 keV) EDS quantification of trace Mg in an Al matrix: EDX detectors typically have energy resolution \u2265100 eV so peaks are broad; ambiguity only occurs for peaks within ~30 eV but broad tails and fitting can still cause interference between nearby lines. Quantitative analysis requires sufficient electron overvoltage (ISO 22309:2011 recommends \u22651.8) and primary energy must exceed the X-ray energy. Detector efficiency varies strongly with X-ray energy and detector/window configuration, so elemental standards are needed for full quantification to cancel detector response differences. All quantitative work requires subtraction of Bremsstrahlung background; background fitting methods differ between software and a poor fit signals high uncertainty. Matrix (ZAF) corrections are required to account for electron backscattering, X-ray absorption and secondary fluorescence. Low\u2011energy detection is also affected by detector windows (Be absorbs <1 keV); windowless detectors are preferable but not always available. Operators must check and correct detector artefacts (sum/escape peaks) and ensure standards and acquisition conditions are appropriate for low\u2011kV analysis.\n\n\n---\n\n## pqac-00000020\n\nFrom text 'ritchie2018exploringthelimits pages 1-4'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThe excerpt discusses EDS detection limits, peak-to-background considerations, and metrology relevant to low-voltage EDS trace analysis. Limits of detection are fundamentally set by the continuum (background) relative to the characteristic signal; the same detection-limit formalism applies to EDS and WDS, but for EDS the measured intensities must be integrated over identical channel ranges on standard and unknown. Peak-to-background on EDS depends on the channel ranges used to estimate continuum and peak; optimal practice is to integrate the central FWHM (\u224876% of peak) and use equivalent ranges of continuum above and below. Modern SDDs have greatly improved throughput, resolution, and low-energy response (enabling detection down to Be-K and even Li-K), and for many measurements SDDs can match or exceed WDS in accuracy and precision. However, SDDs still generally have inferior peak-to-background ratios compared with WDS, limiting the lowest trace detection. Careful metrology and sample preparation (polish, conductive path, beam/sample geometry and working distance control) are emphasized, and standards should be measured and integrated over the same channel ranges as the unknown.\n\n\n---\n\n## pqac-00000021\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 16-18'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses quantitative EDS work performed at low beam energy (E0 = 5 keV) and highlights practical issues and methods relevant to low-kV analysis. Several tables and spectra are reported for analyses at 5 keV (e.g., borides, carbides, YBa2Cu3O7 and BaCl2 spectra), illustrating that low-energy spectra include extended low-energy families (for example, an \u201cextended Ba M-family\u201d), and that analyses used K-L2,3 or L-/M-family peaks depending on element and voltage. The text contrasts first-principles (standardless) analysis with a \u201cremote standards\u201d approach, stating that the remote standards method is tied to measurements of real materials and is inherently more accurate. It also notes a practical calibration transfer technique using a \u201cgolden detector\u201d calibrated at a beamline and a reference material. Finally, uncertainties were evaluated using NIST DTSA-II (reported as combined uncertainties), and tables give mean concentrations, RDEV, and replicate sigmas, conveying achievable precision at 5 keV. These points bear on detection limits, peak overlap and deconvolution, and standard selection for low-kV Mg-in-Al measurements.\n\n\n---\n\n## pqac-00000022\n\nFrom text 'goldstein2018quantitativeanalysisthe pages 1-4'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\nThe excerpt lays out practical requirements relevant to low-kV SEM/EDS quantification. It emphasizes that the k-ratio/matrix-correction method assumes a homogeneous bulk specimen (interaction volume ~0.5\u201310 \u03bcm; secondary fluorescence up to 10\u2013100 \u03bcm) and that specimen and standards must be measured under identical conditions (beam energy, electron dose, EDS parameters, target orientation, take-off angle). Surface preparation is critical: a highly polished, flat surface with roughness <100 nm rms (and <50 nm rms for measurements of photons <1 keV) is required; chemical polishing should be avoided and ion milling can alter near-surface composition. For spectral quality and peak fitting, consistent EDS parameters are essential; a 5 eV/channel energy width is recommended to adequately span peaks including those below 1 keV, and spectra should cover from ~100 eV up to the Duane\u2013Hunt limit. These points inform choices for low-energy (e.g., 5 keV) analyses, standard selection, peak-fitting resolution, and the need to control sample preparation and measurement geometry to minimize artifacts and allow meaningful k-ratio/matrix corrections.\n\n\n---\n\n## pqac-00000023\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 7-9'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt highlights peak overlap and misidentification risks relevant to attempting low-kV (e.g., 5 keV) EDS quantification of trace Mg in an Al matrix. Table 4 shows Mg K\u03b1 (1.253 keV) and Al K\u03b1 (1.487 keV) lie in nearby energy bands, a situation prone to peak interference. Automatic peak-identification can mislabel peaks (e.g., BrL\u03b1 misidentified as AlK\u03b1) and such errors occur more frequently for minor/trace constituents. The authors recommend careful analyst review of tentative assignments, using software tools to explore alternative identifications, sequential peak identification with peak fitting and residual inspection, and adjusting beam energy when appropriate \u2014 either decreasing to reduce self-absorption or increasing to excite additional shells for confirmation. They also emphasize the value of standards-based k-ratio/matrix corrections (vs. standardless analysis), since standardless normalization can obscure clues (raw analytical total) that reveal dubious analyses. Overall, the text supports using peak fitting/residual checks, careful standard selection and standards-based quantification, beam-energy optimization, and cautious interpretation when quantifying trace Mg in an Al matrix at low beam energies.\n\n\n---\n\n## pqac-00000024\n\nFrom text 'ritchie2018exploringthelimits pages 4-5'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nRelevant points for low-kV EDS quantification (e.g., trace Mg in an Al matrix) from the excerpt: meticulous sample preparation and consistent measurement conditions are essential for accurate EDS results. Quantification uses the k-ratio method with matrix (ZAF) corrections that account for atomic number (Z), absorption (A) and secondary fluorescence (F); Z and A are typically computed from \u03c6(\u03c1z)-models. For EDS, multiple X-ray transitions are summed in an integrated peak and each transition has its own correction, so an overall weighted [ZAF]EDS must be applied. Standard selection matters: simple standards are easier but can increase dependence on poorly known parameters (e.g., mass absorption coefficients), while matrix-matched (complex) standards reduce matrix-correction dependence because [ZAF]unk/[ZAF]std approaches unity. Peak overlaps/interferences can be handled using peak-shape reference spectra (e.g., DTSA-II peak-shape references) and careful spectral fitting. Improving detection limits and precision is aided by collecting multiple spectra (N \u2248 5\u201310) of shorter live time, inter-comparing/rejecting outliers, and summing for better statistics. The excerpt also notes that complex line structure can be beneficial for EDS and gives an example dataset collected with SDD detectors (30 mm2) at 20 keV and 0.9 nA.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024]\n\nStatus: Paper Count=25 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=25 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re\u2010Usability: A Position Paper From the Nanosafety Community\nValid Text Names:\n'dumit2025challengesandfuture pages 2-2', 'dumit2025challengesandfuture pages 2-3', 'dumit2025challengesandfuture pages 3-3', 'dumit2025challengesandfuture pages 4-5', 'dumit2025challengesandfuture pages 5-5', 'dumit2025challengesandfuture pages 6-6', 'dumit2025challengesandfuture pages 6-7', 'dumit2025challengesandfuture pages 7-7', 'dumit2025challengesandfuture pages 8-8', 'dumit2025challengesandfuture pages 9-10', 'dumit2025challengesandfuture pages 9-9', 'dumit2025challengesandfuture pages 11-11', 'dumit2025challengesandfuture pages 12-12', 'dumit2025challengesandfuture pages 13-14', 'dumit2025challengesandfuture pages 14-14', 'dumit2025challengesandfuture pages 14-15', 'dumit2025challengesandfuture pages 15-15', 'dumit2025challengesandfuture pages 16-16', 'dumit2025challengesandfuture pages 17-17', 'dumit2025challengesandfuture pages 18-18'\n\nBibTex:\n@article{dumit2026challengesandfuture,\n    author = \"Dumit, Ver\u00f3nica I. and Furxhi, Irini and Nymark, Penny and Afantitis, Antreas and Ammar, Ammar and Amorim, Monica J. B. and Antunes, Dalila and Avramova, Svetlana and Battistelli, Chiara L. and Basei, Gianpietro and Bossa, Cecilia and Cimpan, Emil and Cimpan, Mihaela Roxana and Ciornii, Dmitri and Costa, Anna and Delpivo, Camilla and Dusinska, Maria and Fonseca, Ana Sofia and Friedrichs, Steffi and Hodoroaba, Vasile\u2010Dan and Hristozov, Danail and Isigonis, Panagiotis and Jeliazkova, Nina and Kochev, Nikolay and Kranjc, Eva and Maier, Dieter and Melagraki, Georgia and Papadiamantis, Anastasios G. and Puzyn, Tomasz and Rauscher, Hubert and Reilly, Katie and Jim\u00e9nez, Araceli S\u00e1nchez and Scott\u2010Fordsmand, Janeck J. and Shandilya, Neeraj and Shin, Hyun Kil and Tancheva, Gergana and van Rijn, Jeaphianne P. M. and Willighagen, Egon L. and Wyrzykowska, Ewelina and Bakker, Martine I. and Drobne, Damjana and Exner, Thomas E. and Himly, Martin and Lynch, Iseult\",\n    title = \"Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re\u2010Usability: A Position Paper From the Nanosafety Community\",\n    year = \"2026\",\n    journal = \"Advanced Sustainable Systems\",\n    volume = \"10\",\n    month = \"Dec\",\n    doi = \"10.1002/adsu.202500567\",\n    url = \"https://doi.org/10.1002/adsu.202500567\",\n    publisher = \"Wiley\",\n    issue = \"4\",\n    issn = \"2366-7486\"\n}\n\n\nAbstract:\n<jats:title>Abstract</jats:title>\n                  <jats:p>Ensuring data quality, completeness, and interoperability is crucial for progressing safety research, Safe\u2010and\u2010Sustainable\u2010by\u2010Design approaches, and regulatory approval of nanoscale and advanced materials. While the FAIR (Findable, Accessible, Interoperable, and Re\u2010usable) principles aim to promote data re\u2010use, they do not address data quality, essential for data re\u2010use for advancing sustainable and safe innovation. Effective quality assurance procedures require (meta)data to conform to community\u2010agreed standards. Nanosafety data offer a key reference point for developing best practices in data management for advanced materials, as their large\u2010scale generation coincided with the emergence of dedicated data quality criteria and concepts such as FAIR data. This work highlights frameworks, methodologies, and tools that address the challenges associated with the multidisciplinary nature of nanomaterial safety data. Existing approaches to evaluating the reliability, relevance, and completeness of data are considered in light of their potential for integration into harmonized standards and adaptation to advance material requirements. The goal here is to emphasize the importance of automated tools to reduce manual labor in making (meta)data FAIR, enabling trusted data re\u2010use and fostering safer, more sustainable innovation of advanced materials. Awareness and prioritization of these challenges are critical for building robust data infrastructures.</jats:p>\n\nRelevant Snippet:\n\u2026 The ISO standard 22029 Microbeam Analysis \u2013 EMSA/MAS file \u2026 -dimensional data file specification (HMSA)\u201d and \u201cTag image file format for Scanning Electron Microscopy\u201d have just \u2026\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024]\n\nStatus: Paper Count=26 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=25 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+                  "end_ts": 4489.069146065
+                }
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+              {
+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024]\n\nStatus: Paper Count=25 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=25 | Current Cost=$0.1554 | Disease-Target Evidence=0",
+                "name": "paper_search",
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+              {
+                "role": "assistant",
+                "content": "Let me now read some key texts directly for more specific information, and search for more papers:",
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+                    "id": "toolu_0123AygpAFvhxJmdFs7eBgmu",
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+                      "arguments": "{\"text_name_list\": [\"goldstein2018energydispersivexray pages 14-15\", \"goldstein2018energydispersivexray pages 15-16\", \"goldstein2018energydispersivexray pages 16-18\"]}",
+                      "name": "read_text"
+                    }
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+                    "id": "toolu_014GirKCBh19AkcdktvHnq5g",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Newbury Ritchie 2024 testing accuracy low beam energy 5 keV EDS certified reference materials RDEV\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_0156y4WhR8RXvWw2GXc17fKg",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"public EDS spectrum database library EMSA format microanalysis download repository\"}",
+                      "name": "paper_search"
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+                "content": "## 1. goldstein2018energydispersivexray pages 16-18 (Context ID: pqac-00000025)\n\n                                                                   \u201cImport \u2192 Raw\u201d tools to create a \u201cstack\u201d as shown in                   Detector                                                       .\u2003 Fig. 16.18.\n                                                                                        3. As imported, the orientation of the stack will depend\n                                                               upon how the data in the RAW file is organized.\n                                                                              Regardless of the original orientation, you will need to\n                                                                                 pivot the data a couple times using the \u201cImage \u2192\n                                        0.0                                                    Stack \u2192 Reslice\u201d tool. First, to identify the range of\n                                                                           channels that represent the Cu L-family and Cu K-L2,3\n                                                                                             intensities. Second, to align the spectrum data with           4\n               mm                                              the Z dimension so that the \u201cImage \u2192 Stack \u2192\n                                                                                Z-project\u201d tool can be used to create plots representing\n                                                                              the intensities in the Cu L-family and Cu K-L2,3\n                             4mm                       channels.\n                                                                                        4. The initial view of the imported spectrum will\n      . .\u200a\u200a\u200aFig. 16.16\u2003 A 3D rendering of the intensity in the Cu K line over a            usually show the data as shown in .\u2003 Fig. 16.19. In16\n           4 mm by 4 mm mapped area. Created using ImageJ-Fiji                          this view it is possible to identify the range of\n\n      . .\u200a\u200a\u200aFig. 16.17\u2003 A plot of two diag\u00ad\n            onal traverses extracted from the          300\n         3D rendering. The blue dots are                                                                                    Perp\n            perpendicular to the detector axis                                                                                                        Parallel\n                                             250          and red are parallel. Created using\n             ImageJ-Fiji\n                                             200\n\n\n                                             150                                                                                                                                                                        Intensity\n                                             100\n\n\n                                              50\n\n\n                                               0\n                                                 0           1           2           3           4           5           6\n\n                                                  mm                                                                                                       225                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n      channels to sum together for the Cu L-family and Cu   16.3.5  Count Rate Linearity\n       K-L2,3 lines. The Cu K-L2,3 lines are often quite dim.\n    5.  Using the \u201cImage \u2192 Stack \u2192 Reslice\u201d tool (see       One of the most important circuits in an X-ray pulse proces-\n       .\u2003 Fig. 16.20) rotate the stack until it looks like          sor accounts for the time during which the pulse processor is\n       .\u2003 Fig. 16.21                                       busy processing X-ray events. When the pulse processor is\n    6. Use the \u201cImage \u2192 Stack \u2192 Z-project\u201d twice            processing an X-ray, it is unavailable to process new incoming\n       (.\u2003 Fig. 16.22) to extract the range of channels           X-rays. This time is called \u201cdead-time.\u201d In contrast, the time\n       identified in .\u2003 Fig. 16.19 as associated with the Cu     during which the processor is not busy and is available is called\n       L-family and Cu K-L2,3 lines.                              \u201clive-time.\u201d The sum of \u201clive-time\u201d and \u201cdead-time\u201d is called\n    7. Convert the gray-scale image to a thermal scale using   \u201creal-time\u201d \u2013 the time you would measure using a wall clock.\n      \u201cImage \u2192 Lookup Tables \u2192 Thermal.\u201d                   For calculating the effective probe dose, live-time is the\n    8. Convert the image to a plot using \u201cAnalyze \u2192            critical parameter. The effective probe dose consists of those\n       Surface Plot\u201d                                           electrons which could produce measurable X-rays. So the\n    9.  Extract traverses from the image using the straight      effective probe dose equals the live-time times the probe cur-\n        line tool to define the traverse and then the \u201cAnalyze    rent. The effective probe dose is always less than the real\n   \u2192 Plot Profile\u201d tool to extract and plot the data.       probe dose, which is the product of the real time and the\n\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.18\u2003  Importing a RAW formatted spectrum image into\nImageJ-Fiji                                . .\u200a\u200aFig. 16.20\u2003  \u201cReslice\u201d tool used to rotate the stack\n\n\n\n\n       Cu L-family                                                               Cu K-L2,3\n\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.19\u2003 The spectrum image perspective as imported into ImageJ-Fiji. The bright strip is the Cu L-family while the much fainter band is\nCu K-L2,3           226    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                                                                  important because it is often hard to replicate the identical\n                                                                probe current but it is also important because different mate-\n                                                                                       rials measured with the same probe current will produce dif-\n                                                                            ferent dead times.\n                                                                    There really is no excuse for a modern X-ray detector not\n                                                                         to be linear. However, it is worth checking because the test\n                                                               can expose other potential problems like a non-linear or off-\n                                                                                set probe current meter.\n\n                                                                                           zz  Check 5: Count Rate Linearity with Effective Probe\n                                                                    Current\n                                                                  Equipment:\n                                   55 Faraday cup\n                                   55 Picoammeter\n                                   55 Flat, polished copper sample\n                                                                       Procedure:\n                                                                                       1. Mount the Faraday cup and the polished copper\n                                                                     sample on the stage at the same nominal working\n                                                                                   distance.\n                                                                                       2. Image the sample at the optimal working distance\n                                                               and a beam energy selected in the 15\u201325 keV\n                                                                            range.\n                                                                                    3.  Start a factor of 10 or more below the optimal probe\n                                                                              current. Measure and record the probe current using the\n                                                                    Faraday cup and the picoammeter.\n                                                                                    4. Collect a 60 live-time second spectrum from the copper\n                                                                        sample.\n                                                                                    5. Increase the probe current through a sequence of\n      . .\u200a\u200a\u200aFig. 16.21\u2003 The spectrum image was collected on a 128 by 128          approximately 10\u201320 steps from the initial probe current\n             pixel grid representing 4\u2009\u00d7 4 mm. After data rotation to view the x-y         to\n\n## 2. goldstein2018energydispersivexray pages 14-15 (Context ID: pqac-00000026)\n\n\n                              Y                                    distance\n                                                                                      \u03c8:\n                                                                                                    Elevation angle                                                         Actual\n                                  Z                     working                                                   Sample                                                                         distance\n\n\n\n\n                                                                                                 Sample tilt          222    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                                                                 per unit time. By spectral resolution we mean the width of\n                                                                   a characteristic peak, usually taken to be the Mn K-L2,3\n                                                             (K\u03b1) peak.\n                                                                  Higher throughput is desirable because it allows you to\n                                                                   use higher probe currents to produce more X-rays and pro-\n                                                              duce measured spectra with a larger number of measured\n                                                                         X-rays. Higher resolution is desirable because  it becomes\n                                                                             easier to distinguish characteristic peaks of similar energy.\n                                                             Both are virtues but one is achieved at the expense of the\n                                                                             other.\n                                                              The task of selecting a process time is the task of balanc-\n                                                                      ing good throughput with adequate resolution. At the best\n                                                                         resolution settings, throughput  is seriously compromised\n                                                           and as a result the precision of quantitative analysis is also\n                                                              compromised. At the highest throughput settings, resolution\n      . .\u200a\u200a\u200aFig. 16.14\u2003  Using a cell phone inclinometer to measure the eleva-                                                                                              is compromised and it becomes much more difficult to dis-             tion angle\n                                                                        tinguish interfering peaks.\n                                                                              Fortunately, resolution degrades relatively slowly while\n           correction. The elevation angle (usually sloppily called the  throughput increases quickly. Moderate pulse process times\n           \u201ctake-off angle\u201d) is often a configuration option that may be   tend to degrade the ultimate resolution by a few percent,\n           available to you to modify or may require a service engineer.   while increasing throughput by much larger factors. Every\n          Usually you can check the elevation angle by opening a spec-  vendor is different but typically a moderate pulse process\n         trum data file in a text editor. Most spectrum files are ASCII   time will produce both adequate resolution and excellent\n            text files and the vendors write a line containing the elevation   throughput.\n          or nominal take-off angle.                                 While some modern SDD are capable of ultimate resolu-\n           Compare the value produced by the software with the   tions of 122\u2013128 eV, compromising the resolution to 130\u2013\n           physical position of your detector relative to the beam axis.  135 eV  will produce an excellent compromise between\n          Sometimes, the correct instrument specific value of the take-\u00ad  resolution and throughput. Even a resolution of 140\u2013150 eV\n            off angle will be handwritten in the EDS vendor\u2019s documenta-   at high throughputs can produce  excellent  quantitative\n            tion. Other times, you can extract the angle from instrument   results because the precision of spectrum fitting is more\n            specific schematic diagrams from the SEM or EDS vendors.  determined by the number of measured X-rays than the\n           Regardless, it is a good idea to verify the elevation angle using   spectral resolution.\n          a protractor or a smart phone. Many smart phones contain\n          inclinometers which are accurate to within a degree and \u201cbub-                                                                                           zz  Check 2: Selecting a Process Time\n           ble level apps\u201d are available to turn the phone into a digital                                   55 Ensure that your EDS detector electronics are set to a           inclinometer. First, test the accuracy of the cell phone incli-                                                                    moderate process time that produces a good         nometer using a 30-60-90 triangle or similar reference shape.16                                                                    throughput with a resolution within 5 eV of the best         Then use the cell phone to measure the angle of the snout rela-                                                                                   resolution. Record this parameter in your electronic            tive to the angle of the column and calculate the elevation                                                                    notebook for future reference.           angle. .\u2003 Figure 16.14 shows that a cell phone measures the                                   55 Do not use an \u201cadaptive process time\u201d for           elevation angle of this detector to within half a degree (90\u00b0\u2013                                                                           standards-based quantitative analysis. Adaptive           54.5\u00b0 = 35.5\u00b0 ~ 35\u00b0 nominal value). Achieving similar accu-                                                                             process times allow the resolution to change with          racy with a protractor and a bubble level is difficult.                                                                       throughput making spectrum fitting challenging and\n                                                                                            less accurate.\n          16.3.2  Process Time\n                                                           The optimization of throughput is also confounded by an\n         The \u201cprocess time\u201d (also called the \u201cthroughput setting,\u201d   another practical limitation\u2014coincident X-rays or pulse-\u00ad\n          the \u201cdetector time constant,\u201d the \u201cresolution setting\u201d or  pileup\u2014and will be addressed in a later section.\n          other names) determines how much time the detector elec-\n           tronics dedicates to processing each incoming X-ray. A\n          longer  \u201cprocess  time\u201d  tends  to produce  lower X-ray   16.3.3  Optimal Working Distance\n         throughput but higher spectral resolution. Shorter \u201cpro-\n           cess times\u201d tend to produce higher X-ray throughput but   Nominally, the optimal working distance should be specified\n          lower spectral resolution. By throughput, we mean the   in instrument schematics. However,  it is worth checking\n       maximum number of X-rays that the detector can measure   because it may vary slightly or there may be a mistake in                                                                                                       223                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\ndesign or manufacturing. From the detector geometry sec-   detector element there is usually a window and an electron\ntion, we know that the optimal working distance is the dis-   trap. Most windows are ultrathin layers of polymer or sili-\ntance at which the axis along the detector snout intersects  con nitride mounted on a grid for mechanical strength.\nwith the electron beam axis (see .\u2003 Fig. 16.13). This working  Examples of two support grids are given in .\u2003 Fig. 16.15.\ndistance should also produce the largest flux of X-rays and be  While the grid may have an open area fraction of 75\u201380\u2009%,\nthe distance which is least sensitive to slight errors in vertical   the  silicon or carbon  grid  bars  are  often very  thick\npositioning.                                                  (0.38 mm) to enhance mechanical rigidity under the strain\n                                     \n\n## 3. goldstein2018energydispersivexray pages 15-16 (Context ID: pqac-00000027)\n\nat the optimal working distance is the dis-   trap. Most windows are ultrathin layers of polymer or sili-\ntance at which the axis along the detector snout intersects  con nitride mounted on a grid for mechanical strength.\nwith the electron beam axis (see .\u2003 Fig. 16.13). This working  Examples of two support grids are given in .\u2003 Fig. 16.15.\ndistance should also produce the largest flux of X-rays and be  While the grid may have an open area fraction of 75\u201380\u2009%,\nthe distance which is least sensitive to slight errors in vertical   the  silicon or carbon  grid  bars  are  often very  thick\npositioning.                                                  (0.38 mm) to enhance mechanical rigidity under the strain\n                                                               of up to one atmosphere of differential pressure. Off-axis\nzz  Check 3: Measuring the Optimal Working Distance       the grid bars can occlude the direct transmission of X-rays\n    1.  Select a sample like a piece of copper and mount it     from the sample to the detector element. Furthermore, the\n       perpendicular to the electron beam axis.             magnetic electron trap can also occlude X-rays from off-\n    2.  Select a beam energy of 15\u201325 keV and a moderate      axis. As a result, an EDS detector is more sensitive to X-rays\n      probe current to produce\u2009~\u200920% dead time.           produced on the snout axis than slightly off the axis. The\n    3. Move the stage\u2019s vertical axis to place the sample        result is a position dependent efficiency which peaks on\n       close to the objective lens pole piece. Be careful not     axis and decreases as the source of the X-rays is further\n       to run the sample into a detector.                  from axis.\n    4. Focus the image and record the working distance      A wide field-of-view X-ray spectrum image can demon-\n       reported by your SEM\u2019s software.                         strate the position sensitivity and can be used to ensure that\n    5.  Collect a 60 live-time second spectrum.                the detector snout and detector active element are oriented\n    6. Move the stage away from the objective lens pole        correctly.\n       piece in 1-mm steps.\n    7.  Repeat steps 4\u20136, taking the working distance             zz  Check 4: Collect a Wide Field X-ray Spectrum Image\n      through the nominal optimal working distance.              1. Mount a flat, polished piece of Cu in your SEM.\n    8.  Process the spectra. Extract the total number of              2. Image the Cu at the optimal working distance and at\n      counts in the energy range from about 100 eV to the         20\u201325 keV to excite both the K and L lines.\n     beam energy and plot this number against the                3. Find out how wide a field-of-view your SEM can\n      working distance.                                      image at the optimal working distance. The example\n    9. Determine the working distance which produces the           in .\u2003 Fig. 16.16 uses a 4-mm field-of-view.\n        largest number of counts. Since this working distance       4.  Collect a high count X-ray spectrum image from the\n       represents an inflection point, the slope will be              Cu. Acquiring at a moderate-to-high probe current\n     minimum and thus the sensitivity with respect to               for an hour or more at 256 \u00d7\u2009256-pixel image\n      working distance will also be minimized.                   dimensions should produce sufficiently high\n                                                                      signal-to-noise data.\n                                                                           5.  Process the data to extract and plot the raw\n16.3.4  Detector Orientation                                   intensities at each pixel in each of the Cu K-L2,3 and\n                                                Cu L-family lines.\nIn the previous section, we assumed that the principal axis of           1.  It is important to extract the raw intensities and\nthe detector snout is oriented to intersect with the electron            not the normalized intensities since we are\nbeam axis. In other words, the detector points towards the            looking for variation in the raw intensity as a\nsample. It is usually the EDS vendor\u2019s responsibility to ensure            function of position.\nthat the mounting flange has been designed to correctly ori-           2. The open source software ImageJ-Fiji (ImageJ\nent and position the detector. The next check will verify this.             plus additional tools) can be used to process\n   The active face of an EDS detector is a planar area that is           spectrum image data if it can be converted to a\nmounted perpendicular to the snout axis. In front of the       RAW format.\n\n\n\n                                AP3          AP5\n Thickness (\u00b5m)                      380           265\n Rib width (\u00b5m)                       59            45\n Opening width (\u00b5m)                  190           190             Thickness\n\n Open area %                    76%         78%\n                                                                                    Rib                     Opening\n Acceptance angle                     53\u00b0             72\u00b0                       width                    width\n\n. .\u200a\u200a\u200aFig. 16.15\u2003 Window support grid dimensions for two common window types (Source: MOXTEK)           224    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                6.  Plot the data to demonstrate the variation of the                nished intensities leading to low analytical totals\n                   intensity as a function of position. .\u2003 Figure 16.16              and sub-optimal quantitative results.\n               shows the map from a well-oriented detector plotted            3.  Typically, the Cu L-family peak is more sensi\u00adtive\n                using a thermal color scheme in which red                   due to absorption by the vacuum window support\n                 represents the highest intensity and blue represents                 grid\u2019s Si ribs. .\u2003 Figure 16.15 (source: Moxtek)\n                 zero intensity. .\u2003 Figure 16.17 shows traverses                 shows the design of two recent Moxtek support\n                 extracted from the .\u2003 Fig. 16.16 data on diagonals                  grids. The vertical sensitivity is usually minimized\n                 representing parallel to the detector axis and                  by orienting the grid ribs vertically.\n                perpendicular to the detector axis. Verify that the\n              most intense region in the intensity plots is in the\n                 center of the image area.                                       zz  Sidebar: Processing a \u201cRAW\u201d Spectrum Image with\n                7. Note the extent of the region of uniform efficiency.         ImageJ-Fiji\n                 Variation from ideal uniform sensitivity has                  1. Convert the X-ray spectrum image data into a RAW\n                consequences.                                                                    file. A RAW file is large binary representation of the\n                    1. Low magnification X-ray spectrum images will            data in the spectrum image. Each pixel in the\n                       suffer from reduced intensity towards the edges.          spectrum image consists of a spectrum encode in an\n                    2. Point mode X-ray spectrum acquisitions collected          integer binary format. The pixels are organized in a\n                        off the optical axis will also suffer from dimi\u00ad             continuous array row-by-\u00adrow. The size of the file is\n                                                                                      typically equal to (channel depth)\u2009\u00d7\u2009(row\n                                                                         dimension)\u2009\u00d7\u2009(column dimensions)\u2009\u00d7\u2009(2 or 4 bytes\n                                                                         per integer value).\n                                   255.0                                                                                        2. Import the RAW data file into ImageJ using the\n                                                                      \u201cImport \u2192 Raw\u201d tools to create a \u201cstack\u201d as shown in                   Detector                                                       .\u2003 Fig. 16.18.\n                                                                                        3. As imported, the orientation of the stack will depend\n                                                               upon how the data in the RAW file is organized.\n                                                                              Regardless of the original orientation, you will need to\n                                                                                 pivot the data a couple times using the \u201cImage \u2192\n             \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027]\n\nStatus: Paper Count=26 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=28 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024]\n\nStatus: Paper Count=26 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=25 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+              {
+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nJulien M Allaz. De-ma.ch: a web database for electron and x-ray microanalysis to assist electron microscope lab managers and users. Microscopy and Microanalysis, 30:489-500, May 2024. URL: https://doi.org/10.1093/mam/ozae051, doi:10.1093/mam/ozae051.\nNicholas W. M. Ritchie. Reproducible spectrum and hyperspectrum data analysis using nexl. Microscopy and Microanalysis, 28:478-495, Mar 2022. URL: https://doi.org/10.1017/s143192762200023x, doi:10.1017/s143192762200023x.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027]\n\nStatus: Paper Count=26 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=28 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+              {
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+                "tool_calls": [
+                  {
+                    "id": "toolu_013S7U99w9vd4NXF4wXpL7kV",
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+                      "arguments": "{\"question\": \"NIST DTSA-II accuracy at 5 keV low beam energy, RDEV results, number of measurements, how many percent fell within \\u00b15% RDEV at 5 keV?\"}",
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+                      "arguments": "{\"text_name_list\": [\"newbury2024testingtheaccuracy pages 1-3\", \"newbury2024testingtheaccuracy pages 3-4\", \"newbury2024testingtheaccuracy pages 4-6\"]}",
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+                "role": "tool",
+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000028\n\nFrom text 'newbury2024testingtheaccuracy pages 1-3'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nThe study evaluated the accuracy of low-beam-energy (E0 = 5 keV) electron-excited X-ray microanalysis using energy-dispersive spectrometry (EDS) with the NIST DTSA-II software and a standards-based k-ratio protocol. A total of 263 concentration measurements were made, covering 39 elements across 113 materials (including CRMs, stoichiometric compounds, minerals, and alloys). Accuracy was assessed using the relative deviation from expected value (RDEV) metric. Results show very high accuracy at 5 keV: more than 98% of the 263 measurements fell within \u00b15% RDEV, and 82% fell within -2% to 2% RDEV. DTSA-II also provides uncertainty budgets for reported concentrations, accounting for random and systematic contributions arising from X-ray counting statistics and matrix-correction factors, which underpins the reported confidence in these accuracy statistics.\n\n\n---\n\n## pqac-00000029\n\nFrom text 'newbury2024testingtheaccuracy pages 18-22'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt defines the accuracy metric RDEV as RDEV = [(measured value \u2212 expected value)/expected value] \u00d7 100%. Table 1 summarizes DTSA\u2011II results at a beam energy E0 = 5 keV, comprising 263 concentration measurements for 39 elements in 113 materials. Figure 3a shows the RDEV histogram for atomic concentrations derived from that table. For this 5 keV dataset, more than 98% of the results are captured within \u00b15% RDEV, with 82% within \u22122% to 2% RDEV. A separate raw totals histogram (sum of constituent mass concentrations) spans 0.8\u20131.2, with 67% of analyses in the 0.95\u20131.05 range. The paper notes the RDEV distribution at 5 keV is similar to that observed using conventional higher beam energies (\u226510 keV) when higher\u2011energy characteristic X\u2011rays are selected, and that Table 1 lists measured raw and normalized concentrations plus atomic concentrations and the computed RDEV values for each reported analysis.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029]\n\nStatus: Paper Count=26 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=30 | Current Cost=$0.1744 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "## 1. newbury2024testingtheaccuracy pages 4-6 (Context ID: pqac-00000030)\n\n    BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-\n          conc\n        Knownmass             0.7989     0.3158     0.6642     0.0669     0.9331     0.4492     0.5508     0.3236     0.6764     0.4890     0.5110     0.3112     0.6888     0.5399     0.4601     0.2264     0.7736     0.4007     0.5993     0.5797\n\n      Ele-ment    Cu O  Cr C  Fe  Ti  Ni  Si  Ni  Si  Ni B  Ti  Si  Ti N  Ti O  Ti  Al\n             Materialnumber    10  11  11  12  12  13  13  14  14  15  15  16  16  17  17  18  18  19  19  20\n\n\u2009continued             Material                     CuO_5kV         Cr2O3_5keV         Cr2O3_5keV       Fe3C_5kV       Fe3C_5kV        NiTi_5kVA       NiTi_5kV       NiSi_5kV       NiSi_5kV        NiSi2_5kV        NiSi2_5kV       TiB2_5kV       TiB2_5kV        TiSi2_5kV        TiSi2_5kV      TiN_5kV      TiN_5kV       TiO2_5kV       TiO2_5kV        Al3Ni_5kV\nTable\u202f1\u2002 Row      21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40 19092                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\n   %\n                       1.9    -2.8    -0.36    0.39   1.5    -1.5    -1.1   2.9    -0.50    -2.7   1.3    -3.2   3.2    -1.7   3.4    -2.2   3.7    -1.6   3.2        Atom-concRDEV       -0.73\n\n          Atomicconc             0.2482     0.6112     0.3888     0.5156     0.4844     0.5077     0.4923     0.6183     0.2573     0.1255     0.3244     0.6756     0.4839     0.5161     0.6554     0.3446     0.5264     0.2393     0.0757     0.1587\n          Atomicconcreference         0.2500     0.6000     0.4000     0.5175     0.4825     0.5000     0.5000     0.6250     0.2500     0.1250     0.3333     0.6667     0.5000     0.5000     0.6667     0.3333     0.5385     0.2308     0.0769     0.1538\n\n                                             2.0    -1.1    -1.1   2.9    -0.53    -3.6    0.38    -5.2   1.1    -3.5   1.5    -3.9   1.9    -3.4   1.4        Norm-concRDEV%   -0.57    2.80    -1.90    -0.12    0.62\n\n          mass\n           Normal-izedconc         0.4179     0.4195     0.5805     0.4978     0.5022     0.3487     0.6513     0.2893     0.2113     0.4994     0.0908     0.9092     0.1631     0.8369     0.2834     0.7166     0.1615     0.2916     0.1290     0.4179\n\n   %\n                 5.5   5.7    0.91   5.2   6.0   6.1   2.9    -2.1   1.9    -1.5    -6.4    -2.5    -5.3   1.1    -7.1    -2.3    -2.1   3.8    -1.5   3.3     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0087      \u00b10.0047      \u00b10.0110      \u00b10.0275      \u00b10.0571      \u00b10.0573      \u00b10.0013      \u00b10.0097      \u00b10.0015      \u00b10.0068      \u00b10.0372      \u00b10.0106      \u00b10.0649      \u00b10.0177      \u00b10.0988      \u00b10.0260      \u00b10.0118      \u00b10.0183      \u00b10.0008      \u00b10.0097\n\n     Rawmassconc         0.4432     0.4313     0.5969     0.5243     0.5289     0.3626     0.6773     0.2865     0.2092     0.4946     0.0882     0.8829     0.1630     0.8366     0.2728     0.6898     0.1646     0.2972     0.1315     0.4260\n\n        total\n     Raw            1.06    1.028    1.028    1.053    1.053    1.04    1.04     0.9904     0.9904     0.9904     0.9711     0.9711     0.9996     0.9996     0.9626     0.9626    1.019    1.019    1.019    1.019\n\n             Standard            NiTi    Al2O3    NiTi  Cr    Fe3C   GaN  Al   MgO  Si    BaCO3 B  Cr B  Cr B  Cr    BaCO3   CuS    Y2O3    BaCO3\n\n\n     keV                                                   7,511,728        7,732,677        7,732,677        5,937,198        5,937,198        3,807,755        3,807,755        7,412,983        7,412,983        7,412,983        3,257,829        3,257,829        3,084,682        3,084,682        2,954,279        2,954,279        8,181,180        8,181,180        8,181,180        8,181,180        0.1-5counts\n                                                                 BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-\n          conc\n        Knownmass             0.4203     0.4081     0.5919     0.4984     0.4991     0.3417     0.6583     0.2925     0.2054     0.5021     0.0942     0.9058     0.1721     0.8279     0.2937     0.7063     0.1681     0.2862     0.1335     0.4123\n\n      Ele-ment    Ni  Al  Ni  Cr  Fe N  Al O  Si  Ba B  Cr B  Cr B  Cr O  Cu Y  Ba\n             Materialnumber    20  21  21  22  22  23  23  24  24  24  25  25  26  26  27  27  28  28  28  28\n\n\u2009continued             Material                           Al3Ni_5kV         Al3Ni2_5kV         Al3Ni2_5kV           50Fe-50Cr_5kV           50Fe-50Cr_5kV       AlN_5keV       AlN_5keV                BaSi2O5_Sanbornite                BaSi2O5_Sanbornite                BaSi2O5_Sanbornite    Cr2B    Cr2B   CrB   CrB    CrB2    CrB2            YBa2Cu3O7_xtal            YBa2Cu3O7_xtal            YBa2Cu3O7_xtal            YBa2Cu3O7_xtal\nTable\u202f1\u2002 Row      41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60  J Mater Sci (2024) 59:19088\u201319111                                                                19093\n\n\n\n\n\n   %\n                       2.0    0.23    -0.15    -0.12    0.18    -2.0   2.0    -2.7   2.7    -1.4    0.69    -0.20    0.20    -0.40    0.40   1.4    -2.8    -1.3   1.3        Atom-concRDEV      -2.0\n\n          Atomicconc             0.4901     0.5099     0.4009     0.5991     0.5993     0.4007     0.4902     0.5098     0.4864     0.5136     0.3287     0.6713     0.4990     0.5010     0.4980     0.5020     0.6759     0.3241     0.4933     0.5067\n          Atomicconcreference         0.5000     0.5000     0.4000     0.6000     0.6000     0.4000     0.5000     0.5000     0.5000     0.5000     0.3333     0.6667     0.5000     0.5000     0.5000     0.5000     0.6667     0.3333     0.5000     0.5000\n\n                                                                    3.0    -1.9    0.24    -0.3    0.14    -0.49    0.28   1.9    -2.2    -1.4   1.3        Norm-concRDEV%   -3.5    0.44    0.28    -0.11    -0.19    0.11    -3.0    0.85    -3.2\n\n          mass\n           Normal-izedconc         0.1074     0.8926     0.2821     0.7179     0.3610     0.6390     0.2153     0.7847     0.3995     0.6005     0.1097     0.8903     0.3345     0.6655     0.3629     0.6371     0.5449      0.45516     0.4754     0.5246\n\n   %\n                                                     0.75   1.0    0.77   4.7    0.99   6.7   1.2   3.3    -2.9    -2.5   1.4   3.6   4.3    0.06   4.9   7.7                 2.4   6.6    11.8    11.3     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0317      \u00b10.0017      \u00b10.0066      \u00b10.0093      \u00b10.0035      \u00b10.0032      \u00b10.0011      \u00b10.0036      \u00b10.0045      \u00b10.0025      \u00b10.0052      \u00b10.0136      \u00b10.0020      \u00b10.0101      \u00b10.0018      \u00b10.0343      \u00b10.0024      \u00b10.0091      \u00b10.0030      \u00b10.0242\n\n     Rawmassconc         0.1139     0.9470     0.3144     0.8000     0.3644     0.6449     0.2236     0.8150     0.4167     0.5874     0.1131     0.9173     0.3258     0.6482     0.3698     0.6492     0.5577     0.4658     0.5055     0.5579\n\n        total\n     Raw               1.061    1.061    1.114    1.114    1.009    1.009     1.0386     1.0386    1.043    1.043     1.0303     1.0303    0.974    0.974     1.0191     1.0191     1.0234     1.0234    1.063    1.063\n\n             Standard   C  Mo  As  Te  Se  Bi   CuS  Cd  Se  Cd   MgO   CuS   ZnS    Cu2O   CuS  Fe   CuS    FeAl3   GaP  As\n\n\n     keV                                                   4,100,229        4,100,229        5,212,612        5,212,612        6,505,288        6,505,288        4,535,223   \n\n## 2. newbury2024testingtheaccuracy pages 1-3 (Context ID: pqac-00000031)\n\nJ Mater Sci (2024) 59:19088\u201319111\n\nComputation & theory\n\n\n\nTesting the accuracy of low\u2011beam\u2011energy\nelectron\u2011excited X\u2011ray microanalysis\nwith energy\u2011dispersive spectrometry\n\nDale E. Newbury1,*\u200a  and Nicholas W. M. Ritchie1\u200a\n\n1\u2009National Institute of Standards and Technology, Gaithersburg, MD 20899\u20118370, USA\n\n\n Received: 29 August 2024    ABSTRACT\n Accepted: 25 September 2024    The accuracy of electron-excited X-ray microanalysis with energy-dispersive spec-\n Published online:             trometry (EDS) has been tested in the low beam energy range, specifically at an\n 14 October 2024                incident beam energy of 5 keV, which is the lowest beam energy for which a use-\n                                  ful characteristic X-ray peak can be excited for all elements of the periodic table,\n This is a U.S. Government        excepting H and He. Elemental analysis results are reported for certified reference\n work and not under copyright     materials (CRM), stoichiometric compounds, minerals, and metal alloys of inde-\n                            pendently known or measured composition which had microscopic homogeneity protection in the US; foreign\n                                suitable for microanalysis. Two-hundred sixty-three concentration measurements copyright protection may ap-\n                                 for 39 elements in 113 materials were determined following the k-ratio protocol and ply, 2024\n                            using the EDS analytical software NIST DTSA-II. The accuracy of the results, as\n                              characterized by the relative deviation from expected value (RDEV) metric, was such\n                                that more than 98% of the results were found to be captured within a range of \u00b15%\n                       RDEV, while 82% of the results fell in the range -2% to 2% RDEV.\n\nIntroduction                                     Because of the strong dependence of the electron range\n                                            on the incident beam energy, R \u2248E0 1.66\u200a, the spatial\nElectron-excited X-ray microanalysis with energy-    resolution of the measurement can be significantly\ndispersive spectrometry (EDS) is a spatially resolved   improved by reducing the beam energy to the lowest\nelemental characterization technique that is widely   value compatible with achieving useful X-ray excita-\napplied in the physical, biological, and forensic sci-    tion for all elements to be measured in the specimen.\nences, technology, failure analysis, etc. [1]. \u201cConven-   As detailed in a previous paper [2], \u201clow-beam-energy\ntional\u201d analytical strategy involves selecting the inci-    microanalysis\u201d involves choosing the beam energy in\ndent beam energy, \u00adE0, to be 10 keV or higher to excite    the range \u00adE0 \u2264 5 keV. \u00adE0 = 5 keV is the lowest beam\nanalytically useful characteristic X-rays from all ele-   energy for which an analytically useful characteristic\nments of the periodic table, with the exception of H   X-ray can be excited for all elements except H and He.\nand He, which do not produce characteristic X-rays.   However, even with a choice of \u00adE0 = 5 keV, less familiar\n\n\nHandling Editor: C. Barry Carter.\n\nAddress correspondence to E-mail: dale.newbury@nist.gov\nE-mail Addresses: nicholas.ritchie@nist.gov\n\n                                                                     https://doi.org/10.1007/s10853-024-10285-4\n\n\n\n           Vol:.(1234567890) J Mater Sci (2024) 59:19088\u201319111                                                                19089\n\n\nlow photon energy characteristic X-rays must be used    energy-dispersive spectrometry for a beam energy\nfor several elements, e.g., the Ti L-family (\u2248 0.45 keV)    of \u00adE0 = 5 keV. Analysis followed the standards-based\ninstead of the Ti K-family (4.5 keV) and the Ba M-fam-    measurement protocol, in which each element in the\nily (0.6\u20131.1 keV) instead of the Ba L-family (4.467 keV).    sample is measured relative to that same element\nAs the beam energy is lowered below 5 keV, elements    present at a known concentration in a \u201cstandard\u201d,\nare progressively lost to analysis due to inadequate or    which can be a pure element, a binary stoichiometric\nno excitation [2].                               compound, or an elemental mixture such as a glass\n  When an unknown material is analyzed, the abso-    available as a CRM [1].\nlute accuracy of the analytical results cannot be known\ndue to uncertainty in the various parameters neces-\nsary to calculate the matrix correction factors. Robust\nanalytical practice requires that an uncertainty budget   Materials and methods\nbe associated with each reported elemental concen-\ntration, such as that provided by the NIST DTSA-II    All materials analyzed are listed individually in\nsoftware platform [3]. DTSA-II attaches to each con-    Table 1, summary of results. Materials and sources\ncentration value an uncertainty budget that includes    analyzed in this study include:\nthe contribution of the random component due to the\ncharacteristic X-ray measurement statistics (from the     1.  National Institute of Standards and Technology\nunknown and the standard) as well as an estimation       (NIST) Standard Reference Materials (SRM) spe-\nof the systematic components that arise from the prin-         cially developed to be homogeneous on the micro-\ncipal matrix correction corrections for electron scat-        scopic scale so as to be suitable for microanalysis\ntering and energy loss (the \u201cZ\u201d factor) and the self-        applications:\nabsorption of X-rays (the \u201cA\u201d factor). This uncertainty         (1) SRM 470 K411 glass (O-Mg-Si-Ca-Fe)\nbudget can then be used to describe a \u201cconfidence         (2) SRM 470 K412 glass (O-Mg-Al-Si-Ca-Fe)\nrange\u201d within which the true concentration value can         (3) SRM 479 (Fe-Cr-Ni Stainless Steel)\nbe expected to reside [4\u20136].                                       (4) SRM 481, Gold-Silver alloys (nominal 20, 40,\n  The general \u201daccuracy\u201d of electron-excited X-ray              60, and 80 weight percent)\nmicroanalysis can be estimated by analyzing \u201cchal-         (5) SRM 482, Gold-Copper alloys (nominal 20, 40,\nlenge specimens\u201d whose compositions are known              60, and 80 weight percent)\nfrom independent analysis so that the measured         (6) SRM 1871 K456 glass (O-Si-Pb)\nvalue can be reasonably compared to a known refer-         (7) SRM 1872 K453 glass (O-Ge-Pb)\nence value. A limited number of microanalysis-qual-         (8) SRM 1873 K458 glass (O-Si-Zn-Ba)\nified certified reference materials (CRM) are avail-         (9) SRM 1875 K496 glass (O-Mg-Al-P)\nable from national measurement institutions, such     2.  European Commission, Community Bureau of Ref-\nas the National Institute of Standards and Technol-       erence\nogy (U.S.A.). Additional challenge specimens can be         (1)  Fe3C (CRM BCR-726)\nderived from materials whose composition is sharply\nconstrained by their stoichiometric nature and which     3.  Reagent compounds, e.g., \u00adBaTiO3, PbS, \u00adMoS2\ndo not exhibit a range of solid solubility, e.g., com-        (source: Alfa Aesar, Tewksbury, MA 01876)).\npounds such as \u00adFeS2, CuS, \u00adFe2O3, etc. A second criti-     4.  Stoichiometric binary compounds, e.g., TiN, \u00adTiO2,\ncal criterion is that these challenge specimens must        \u00adCr2N, etc., with surfaces prepared for microanaly-\nalso be homogeneous on a microscopic scale, a con-         sis (source: Geller Microanalytical Laboratory,\ndition which can be confirmed by a systematic sur-        Topfield, MA 01983)\nvey of the material by \u201cpoint beam\u201d random sam-     5.  Minerals of known composition and micro-\npling or by area scanning /compositional mapping      homogeneity, e.g., albite, arsenopyrite, cal-\nto examine microstructural compositional details.         cite, chalcopyrite, cinnabar, cryolite, dolomite,\nThe current study has undertaken analysis of a wide        fluorapatite, galena, jadeite, kyanite, hematite,\nrange of challenge specimens to develop an analyti-        magnetite, pyrite, rhodonite, scheelite, willemite,\ncal history sufficient to make an estimate of the accu-        wollastonite, zircon (source: SPI (West Chester, PA,\nracy of electron-excited X-ray microanalysis with        19381-0656, USA) ) 19090                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\n   %\n                                        2.3    -4.8   4.6    -3.5    -0.16    0.98    0.86    -2.3   1.3    -1.5   1.5    -0.67   2.7    -0.36    -2.6    -1.7        Atom-concRDEV      0.37    -4.5    0.89    -4.1\n\n          Atomicconc              0.9282     0.0718     0.8297     0.1703     0.6863     0.3137     0.4538     0.5462     0.8620     0.1380     0.7385     0.2615     0.5552     0.4448     0.3175     0.6825     0.2001     0.7016     0.0984     0.4913\n          Atomicconcreference         0.9248     0.0752     0.8224     0.1776     0.6706     0.3294     0.4340     0.5660   \n\n## 3. newbury2024testingtheaccuracy pages 3-4 (Context ID: pqac-00000032)\n\n81-0656, USA) ) 19090                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\n   %\n                                        2.3    -4.8   4.6    -3.5    -0.16    0.98    0.86    -2.3   1.3    -1.5   1.5    -0.67   2.7    -0.36    -2.6    -1.7        Atom-concRDEV      0.37    -4.5    0.89    -4.1\n\n          Atomicconc              0.9282     0.0718     0.8297     0.1703     0.6863     0.3137     0.4538     0.5462     0.8620     0.1380     0.7385     0.2615     0.5552     0.4448     0.3175     0.6825     0.2001     0.7016     0.0984     0.4913\n          Atomicconcreference         0.9248     0.0752     0.8224     0.1776     0.6706     0.3294     0.4340     0.5660     0.8633     0.1367     0.7322     0.2678     0.5483     0.4517     0.3129     0.6871     0.1949     0.7041     0.1010     0.5000\n\n                 1.0    -3.9   2.0    -3.0   4.4    -2.9   6.6    -1.6    -0.26    0.86   1.3    -1.9   1.7    -1.1   1.7    -0.44   2.7    -0.31    -2.5    -2.7        Norm-concRDEV%\n\n          mass\n           Normal-izedconc         0.8067     0.1933     0.6112     0.3888     0.4138     0.5862     0.2114     0.7886     0.7738     0.2262     0.6073     0.3927     0.4061     0.5939     0.2030     0.7970     0.1879     0.7078     0.1043     0.1956\n\n   %\n                                                                                                                 8.1   5.7    -4.8                 1.7    -3.3   2.8    -2.3   4.2    -3.1   5.2    -2.9   1.1   2.2   1.5    -1.7   1.6    -1.2   2.2    0.01    11.4     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0117      \u00b10.0026      \u00b10.0175      \u00b10.0040      \u00b10.0177      \u00b10.0043      \u00b10.0122      \u00b10.0031      \u00b10.0054      \u00b10.0027      \u00b10.0068      \u00b10.0036      \u00b10.0069      \u00b10.0038      \u00b10.0047      \u00b10.0029      \u00b10.0181      \u00b10.0424      \u00b10.0108      \u00b10.0012\n\n     Rawmassconc         0.8120     0.1946     0.6160     0.3918     0.4128     0.5848     0.2086     0.7782     0.7841     0.2292     0.6084     0.3934     0.4057     0.5934     0.2040     0.8006     0.2038     0.7677     0.1131     0.1915\n\n        total\n     Raw                  1.0066     1.0066     1.0078     1.0078     0.9975     0.9975     0.9868     0.9868    1.013    1.013    1.002    1.002     0.9991     0.9991    1.005    1.005    1.085    1.085    1.085     0.9793\n\n             Standard      Cu  Au  Cu  Au  Cu  Au  Cu  Au  Ag  Au  Ag  Au  Ag  Au  Ag  Au  Cr  Fe    NiSi   MgO\n\n\n     keV                                                   6,705,457        6,705,457        6,532,544        6,532,544        6,376,277        6,376,277        6,305,887        6,305,887        4,778,550        4,778,550        5,070,877        5,070,877        5,486,996        5,486,996        6,015,553        6,015,553        6,491,256        6,491,256        6,491,256        9,844,586keV  0.1-5counts\n5\n=\n\u00adE0\nat\n                                                                 BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad                Analyticalplatform                       JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-Analysis\nfor    conc\n        Knownmass              0.7985     0.2012     0.5992     0.4010     0.3964     0.6036     0.1983     0.8015     0.7758     0.2243     0.5993     0.4003     0.3992     0.6005     0.1996     0.8005    0.183    0.710    0.107     0.2011\nResults\n       Ele-ment     Cu  Au  Cu  Au  Cu  Au  Cu  Au  Ag  Au  Ag  Au  Ag  Au  Ag  Au  Cr  Fe  Ni O\nAnalytical   Materialnumber  1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 9  10\nof\n\u2009Compilation                                                                              Au20Cu80_5kV           Au20Cu80_5kV           Au40Cu60_5kV           Au40Cu60_5kV           Au60Cu40_5kV           Au60Cu40_5kV           Au80Cu20_5kV           Au80Cu20_5kV           Au20Ag80_5kV           Au20Ag80_5kV           Au40Ag60_5kV           Au40Ag60_5kV           Au60Ag40_5kV           Au60Ag40_5kV           Au80Ag20_5kV           Au80Ag20_5kV             less_Steel_5keV             less_Steel_5keV             less_Steel_5keV             Material                      SRM482_      SRM482_      SRM482_      SRM482_      SRM482_      SRM482_      SRM482_      SRM482_      SRM481_      SRM481_      SRM481_      SRM481_      SRM481_      SRM481_      SRM481_      SRM481_           SRM479_Stain-           SRM479_Stain-           SRM479_Stain-      CuO_5kV\nTable\u202f1\u2002 Row   1 2 3 4 5 6 7 8 9  10  11  12  13  14  15  16  17  18  19  20  J Mater Sci (2024) 59:19088\u201319111                                                                19091\n\n\n\n\n\n   %\n                 1.7    0.88    -1.3    -2.5    0.83    -2.8   2.8    -0.23    0.23    -1.4   2.8    -1.1   2.3   1.1    -2.2    -0.90    0.90    -0.10    0.19    0.24        Atom-concRDEV\n\n          Atomicconc             0.5087     0.6053     0.3947     0.2438     0.7562     0.4862     0.5138     0.4988     0.5012     0.6573     0.3427     0.6591     0.3409     0.6739     0.3261     0.4955     0.5045     0.6661     0.3339     0.7518\n          Atomicconcreference         0.5000     0.6000     0.4000     0.2500     0.7500     0.5000     0.5000     0.5000     0.5000     0.6667     0.3333     0.6667     0.3333     0.6667     0.3333     0.5000     0.5000     0.6667     0.3333     0.7500\n\n                       1.5   2.3    -7.2    0.21    -3.0   2.5    -0.31    0.15    -2.1   2.1    -2.3   1.0   1.5    -1.8    -1.4    0.40    -0.17    0.12    0.41        Norm-concRDEV%   0.69\n\n          mass\n           Normal-izedconc         0.8044     0.3205     0.6795     0.0649     0.9351     0.4356     0.5644     0.3226     0.6774     0.4785     0.5215     0.3040     0.6960     0.5481     0.4519     0.2233     0.7767     0.4000     0.6000     0.5821\n\n   %\n                                                                                                                            6.5                                                                                                                        0.70    -2.6    19.0    21.1    -1.1    -0.85                       -1.4    -8.6    -7.8   2.8   6.3    15.6    22.2    -1.6    -1.2   4.2   8.6    14.8    18.6     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0032      \u00b10.0098      \u00b10.0306      \u00b10.0155      \u00b10.0044      \u00b10.0394      \u00b10.0232      \u00b10.0026      \u00b10.0151      \u00b10.0030      \u00b10.0097      \u00b10.0495      \u00b10.0251      \u00b10.0004      \u00b10.0256      \u00b10.0832      \u00b10.0763      \u00b10.0305      \u00b10.0115      \u00b10.0046\n\n     Rawmassconc         0.7878     0.2888     0.6121     0.0688     0.9916     0.5192     0.6729     0.3182     0.6681     0.5094     0.5551     0.3517     0.8171     0.5437     0.4438     0.2695     0.9375     0.3961     0.5942     0.6173\n\n        total\n     Raw                  0.9793     0.9008     0.9008    1.059    1.059    1.192    1.192     0.9857     0.9857    1.065    1.065    1.174    1.174     0.9919     0.9919    1.207    1.207     0.9903     0.9903    1.06\n\n             Standard      Cu O  Cr C  Fe  Ti  Ni  Si    NiTi  Si    NiTi B  Ti  Si  Ti   GaN    TiSi2 O  Ti  Al\n\n\n     keV                                                   9,844,586        5,268,245        5,268,245        3,585,708        3,585,708         12,088,360         12,088,360        7,329,688        7,329,688        5,908,406        5,908,406        4,130,925        4,130,925        6,011,950        6,011,950        2,518,085        2,518,085        5,391,466        5,391,466        7,511,728        0.1-5counts\n                                                                 BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-     \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032]\n\nStatus: Paper Count=26 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=33 | Current Cost=$0.1744 | Disease-Target Evidence=0",
+                "name": "read_text",
+                "tool_call_id": "toolu_01X2qzVE6cp9iUKPWBL1uVh6",
+                "info": {
+                  "start_ts": 4564.760746304,
+                  "end_ts": 4618.189018834
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Excellent. Now let me look at additional specific information and collect cited papers:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01MdPzYiwbwhaiFWoSVyBdxN",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{}",
+                      "name": "collect_cited_papers_in_evidence"
+                    }
+                  },
+                  {
+                    "id": "toolu_0158Z2mioMoToKMUGybguiH8",
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+                "content": "Artifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032]\n\nStatus: Paper Count=30 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=33 | Current Cost=$0.1744 | Disease-Target Evidence=0",
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+                "tool_call_id": "toolu_01MdPzYiwbwhaiFWoSVyBdxN",
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+                "content": "## 1. newbury2024testingtheaccuracy pages 6-8 (Context ID: pqac-00000033)\n\n  0.1139     0.9470     0.3144     0.8000     0.3644     0.6449     0.2236     0.8150     0.4167     0.5874     0.1131     0.9173     0.3258     0.6482     0.3698     0.6492     0.5577     0.4658     0.5055     0.5579\n\n        total\n     Raw               1.061    1.061    1.114    1.114    1.009    1.009     1.0386     1.0386    1.043    1.043     1.0303     1.0303    0.974    0.974     1.0191     1.0191     1.0234     1.0234    1.063    1.063\n\n             Standard   C  Mo  As  Te  Se  Bi   CuS  Cd  Se  Cd   MgO   CuS   ZnS    Cu2O   CuS  Fe   CuS    FeAl3   GaP  As\n\n\n     keV                                                   4,100,229        4,100,229        5,212,612        5,212,612        6,505,288        6,505,288        4,535,223        4,535,223        5,493,373        5,493,373        7,363,940        7,363,940        6,343,848        6,343,848        4,590,580        4,590,580        4,624,933        4,624,933        7,547,321        7,547,321        0.1-5counts\n                                                                 BrukerQuad         BrukerQuad         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         BrukerQuad         BrukerQuad         Bruker2019         Bruker2019                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-\n          conc\n        Knownmass             0.1113     0.8887     0.2813     0.7187     0.3617     0.6383     0.2219     0.7781     0.4126     0.5874     0.1118     0.8882     0.3354     0.6646     0.3647     0.6353     0.5345     0.4655     0.4820     0.5180\n\n      Ele-ment  C  Mo  As  Te  Se  Bi S  Cd  Se  Cd O  Cu S  Cu S  Fe S  Fe  Ga  As\n             Materialnumber    29  29  30  30  31  31  32  32  33  33  34  34  35  35  36  36  37  37  38  38\n\n\u2009continued             Material         MoC   MoC         As2Te3_5kV         As2Te3_5kV         Bi2Se3_5kV         Bi2Se3_5kV      CdS_5kV      CdS_5kV       CdSe_5kV       CdSe_5kV       Cu2O_5kV       Cu2O_5kV       CuS_5keV       CuS_5keV       FeS_5keV       FeS_5keV        FeS2_5keV        FeS2_5keV       GaAs_5kV       GaAs_5kV\nTable\u202f1\u2002 Row      61  62  63  64  65  66  67  68  69  70  71  72  73  74  75  76  77  78  79  80 19094                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\n   %\n                       1.5    -0.64    0.64    -1.0   2.0    0.04    -0.04    -0.92    0.92   0.4    -0.4    -1.9   1.9    0.07    -0.15   1.3    -1.3    0.83    -1.3        Atom-concRDEV      -1.5\n\n          Atomicconc             0.4924     0.5076     0.4968     0.5032     0.6601     0.3399     0.5002     0.4998     0.4954     0.5046     0.5020     0.4980     0.4903     0.5097     0.6672     0.3328     0.5067     0.4933     0.6050     0.3950\n          Atomicconcreference         0.5000     0.5000     0.5000     0.5000     0.6667     0.3333     0.5000     0.5000     0.5000     0.5000     0.5000     0.5000     0.5000     0.5000     0.6667     0.3333     0.5000     0.5000     0.6000     0.4000\n\n                                                                                          1.5    0.09    -0.11   1.6    -1.1   1.5    -0.63        Norm-concRDEV%   -2.1    0.92    -0.80    0.46    -2.0    0.89    0.03    -0.02    -1.4    0.38    0.58    -0.4    -2.4\n\n          mass\n           Normal-izedconc         0.3012     0.6988     0.3612     0.6388     0.2996     0.7004     0.3629     0.6371     0.2112     0.7888     0.2775     0.7225     0.3720     0.6280     0.5331     0.4669     0.4059     0.5941     0.3050     0.6950\n\n   %\n                       -6.5    -3.6   2.2   3.5    -7.9    -5.2    -6.8    -6.9    -0.14   1.7    0.04    -0.79    -3.1    0.69    -5.6    -5.8   1.5    -1.1   8.3   6.1     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0023      \u00b10.0043      \u00b10.0177      \u00b10.0054      \u00b10.0165      \u00b10.0165      \u00b10.0202      \u00b10.0086      \u00b10.0086      \u00b10.0159      \u00b10.0029      \u00b10.0026      \u00b10.0043      \u00b10.0022      \u00b10.0240      \u00b10.0011      \u00b10.0047      \u00b10.0023      \u00b10.0103      \u00b10.0370\n\n     Rawmassconc         0.2876     0.6673     0.3720     0.6579     0.2815     0.6581     0.3380     0.5933     0.2139     0.7989     0.2760     0.7184     0.3691     0.6232     0.5028     0.4403     0.4055     0.5936     0.3256     0.7419\n\n        total\n     Raw                  0.9549     0.9549     1.0299     1.0299     0.9395     0.9395     0.9312     0.9312     1.0128     1.0128     0.9944     0.9944     0.9923     0.9923     0.9431     0.9431     0.9991     0.9991     1.0675     1.0675\n\n             Standard                              Ca5(PO4)3F    GaAS   GaP  Sb    SiO2  Ge  Ge  Te   MgO  Ni  Se    PbTe  Te    PbSe   NiO  Si  Se  Sn   MgO  Fe\n\n\n     keV                                                   6,615,542        6,615,542        5,581,455        5,581,455        6,110,745        6,110,745        5,500,042        5,500,042        5,846,515        5,846,515        6,608,981        6,608,981        5,606,222        5,606,222        5,109,005        5,109,005        5,447,221        5,447,221        4,963,883        4,963,883        0.1-5counts\n\n                                                                 Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-\n          conc\n        Knownmass             0.3076     0.6924     0.3641     0.6359     0.3058     0.6942     0.3628     0.6372     0.2142     0.7858     0.2759     0.7241     0.3811     0.6189     0.5326     0.4674     0.3995     0.6005     0.3006     0.6994\n\n      Ele-ment  P  Ga  Ga  Sb O  Ge  Ge  Te O  Ni  Se  Pb  Te  Pb O  Si  Se  Sn O  Fe\n             Materialnumber    39  39  40  40  41  41  42  42  43  43  44  44  45  45  46  46  47  47  48  48\n\n\u2009continued             Material                        GaP_5keV       GaP_5keV        GaSb_5keV        GaSb_5keV        GeO2_5keV        GeO2_5keV       GeTe_5kV       GeTe_5kV       NiO_5keV       NiO_5keV       PbSe_5kV       PbSe_5kV       PbTe_5kV       PbTe_5kV       SiO2_5kV       SiO2_5kV       SnSe_5kV       SnSe_5kV        Fe2O3_5kV        Fe2O3_5kV\nTable\u202f1\u2002 Row      81  82  83  84  85  86  87  88  89  90  91  92  93  94  95  96  97  98  99   100  J Mater Sci (2024) 59:19088\u201319111                                                                19095\n\n\n\n\n\n   %\n                 1.2    -0.11    -2.6    0.90    -1.2   3.8    -1.1   3.6    -0.58    0.11    -3.0    1.10    0.24    -2.7    -0.01    0.21   3.3    -1.2   3.2    -1.1        Atom-concRDEV\n\n          Atomicconc             0.0858     0.9142     0.2471     0.7529     0.7500     0.2500     0.7611     0.2389     0.1532     0.8468     0.2666     0.7334     0.9197     0.0803     0.9527     0.0473     0.2744     0.7256     0.2580     0.7420\n          Atomicconcreference         0.0848     0.9152     0.2538     0.7462     0.7591     0.2409     0.7693     0.2307     0.1541     0.8459     0.2748     0.7252     0.9175     0.0825     0.9528     0.0472     0.2656     0.7344     0.2500     0.7500\n\n                 1.2    -0.05    -2.7    0.82    -2.4   2.5    -2.2   2.3    -0.65    0.05    -3.1   1.0    0.64    -2.3     -0.020    0.15   3.7    -0.84   3.6    -0.67        Norm-concRDEV%\n\n          mass\n           Normal-izedconc         0.0412     0.9588     0.2245     0.7755     0.4942     0.5058     0.5053     0.4947     0.0768     0.9232     0.2435     0.7565     0.7879     0.2121     0.8655     0.1345     0.2589     0.7411     0.1609     0.8391\n\n   %\n                                                                                     6.4   3.3   2.9   3.1    27.1    21.5   8.6   6.2                                                     0.24   5.3    -1.6   3.0   4.1   4.9   7.6    12.2                 7.1\n\n## 2. newbury2024testingtheaccuracy pages 22-24 (Context ID: pqac-00000034)\n\n  nential dependence of X-ray absorption on the path\n\n\n\n\n\nFigure 5\u2002 \u2009NiTi measured at \u00adE0 = 15 keV (red) and peak fitting residual spectrum (blue).19108                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\nFigure 6\u2002 \u2009NiTi measured at \u00adE0 = 10 keV (red) and peak fitting residual spectrum (blue).\n\n\n\n\n\nFigure 7\u2002 \u2009NiTi measured at \u00adE0 = 5 keV (red) and peak fitting residual spectrum (blue). J Mater Sci (2024) 59:19088\u201319111                                                                19109\n\n\n\n\n\nFigure 8\u2002 \u2009NiTi: a comparison of peak fitting residual spectra measured at \u00adE0 = 15 keV (red), 10 keV (blue) and 5 (keV (green); b all\npeak fitting residual spectra scaled to the region 1.1 keV \u2013 1.2 keV (yellow).\n\n                                                        of the X-ray absorption edge structure that exists\n                                              under the characteristic X-ray peaks. As the beam\n                                                 energy is reduced, the beam penetrates the sample\n                                                             less and the generated Bremsstrahlung X-rays pass\n                                               through less material and fewer are absorbed on\n                                                         either side of the absorption edge. The magnitude\n                                                         of the edge structure is a function of the magnitude\n                                                         of the absorption which will be lower due to shorter\n                                                    absorption path length at lower beam energies. The\n                                                           result is a less distinctive absorption edge structure\n                                             which is easier for the peak fitting process to han-\n                                                            dle. This absorption structure is more complex for\n                                                     the multi-edge L-family and M-family X-rays that\n                                            must be used in low-beam-energy operation. The\n                                                             effect of lowering the beam energy on the quality\n                                                         of the peak fitting is shown in Figures 5, 6, 7, and 8\n                                                           for the intermetallic compound NiTi. The \u201cpeak fit-Figure 9\u2002 \u2009Histogram of the raw analytical total (mass concentra-\n                                                        ting residual spectrum\u201d at \u00adE0 = 5 keV shows muchtion) from DTSA-II for \u00adE0 = 5 keV.\n                                                reduced structure around the absorption edge ener-\n                                                       gies for the Ti L-family and the Ni L-family com-\nlength, the absorption correction is reduced, leading    pared to the residuals at \u00adE0 = 15 keV and \u00adE0 = 10 keV.\nto reduced RDEV. A second advantage of reducing    Moreover, the residual spectrum at \u00adE0 = 5 keV shows\nthe self-absorption of X-rays by operating at low    a physically realistic X-ray continuum background\nbeam energy is the reduction in the relative height     after stripping the characteristic X-ray peaks, while\n                                                     the residual spectra at \u00adE0 = 15 keV and \u00adE0 = 10 keV19110                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\ninclude ranges of non-physical zero intensity in the    be differences in the conductive coatings applied to\nX-ray continuum. While the residual is a very use-    insulating materials. It should be noted, however,\nful tool for evaluating the spectrum fit process, it    that normalization of the raw mass concentrations\nshould always be remembered that the residual is    or calculation of atomic concentrations from the\na somewhat artificial construct. The residual rep-   raw mass concentrations compensates for the sig-\nresents an estimate of the continuum signal in the     nificant deviation of the analytical total from unity.\nunknown which is computed by subtracting, from   An additional factor that can affect low-beam-energy\nthe unknown spectrum, the characteristic intensity    analysis is the effect of electron channeling on the\nextracted from the standard spectrum multiplied by     characteristic X-ray emission, as reported by Meisen-\nthe k-ratio. The quality of the residual depends on    kothen et al. [16]. Differences between the sample\nmany factors including the quality of the modeling   and the standards in the removal of surface damage\nof the continuum (and thus the characteristic-only    that arises from mechanical polishing, which modi-\nintensity) in the standard, differential absorption     fies the degree of electron channeling, can influence\nof the various lines in the peak in the standard and    the analytical total.\nsample and bonding-induced shifts in characteristic       Finally, it must be remembered that the materi-\nX-ray energies.                                             als whose compositions were measured as challenge\n   If the same low-energy lines we selected at 5 keV    specimens to produce the RDEV histogram of Fig-\nhad been used at higher beam energies, we would    ure 3 were carefully examined to exclude those mate-\nexpect to see less accurate results. These lines can be     rials with unacceptably thick surface layers which\nused at low beam energies, where the beam does not   would significantly compromise the measured com-\npenetrate deep into the sample leading to a relatively    position. Thus, when considering the accuracy of\nsmall absorption correction despite the large mass    low-beam-energy microanalysis applied to the anal-\nabsorption coefficients typically associated with low-    ysis of practical materials, it should be noted that\nenergy X-rays. At higher beam energies where the    the reality of the sample condition that the analyst is\nbeam penetrates deeper, the absorption correction     likely to encounter on an unknown may significantly\nand the associated uncertainty are larger resulting in    compromise the accuracy that is achievable. In par-\nsignificantly poorer measurements. This is particularly     ticular, the analyst may encounter a surface layer,\ntrue for the L-lines of transition metals in which the   due to environmental reactions such as oxidation or\nL2-M2 transition is well known to show anomalously     sulfidation, whose thickness is a substantial fraction\nlarge self-absorption in pure metals [12\u201314].              of the electron range. This situation creates a com-\n  The raw analytical total, which is the sum of the    posite specimen where the interaction volume of the\nmeasured mass concentrations for all constituents,   beam effectively samples two or more different mate-\nincluding any such as oxygen calculated by the     rials. The basic assumption of the k-ratio protocol\nmethod of assumed stoichiometry, is a useful inter-     for quantitative analysis is that the excited volume\nnal consistency indicator in the conventional beam     is uniform in composition. When this condition is\nenergy analysis regime, where the raw analytical    not met, substantial error is likely to occur. Robust\ntotal typically lies within the range 0.98\u20131.02 [15].    analytical practice should include careful examina-\nA deviation in the raw analytical total significantly    tion for the possibility of such surface anomalies\nbelow 0.98 is likely to be an indication that an ele-    by measuring spectra by sequentially lowering the\nment is present in the material that is not included   beam energy from a starting value in the \u201cconven-\nin the element suite for the analysis, which can be a    tional\u201d range, \u00adE0 \u2265 10 keV, down into the low-beam-\nvaluable tool for the analyst. The histogram of raw    energy regime, \u00adE0 \u2264 5 keV, which can reveal surface\nanalytical totals observed at \u00adE0 = 5 keV in this study,    anomalies, as illustrated in Figure 1.\nas shown in Figure 9, reveals a much broader range.\nAlthough the majority of analytical totals cluster\naround unity, totals as low as 0.8 and as high as 1.2   Funding\u2003\nare encountered, despite the careful vetting of the\nmaterials for surface anomalies. The source of this   Open access funding provided by the National Insti-\nmuch broader range of analytical totals is likely to     tutes of Health. This study was funded by National\n                                                              Institute of Standards and Technology. J Mater Sci (2024) 59:19088\u201319111                                                                19111\n\n\nData availability\u2002                                                     [ 7]  Ritchie N, Filip V (2011) Semantics for high speed aut\n\n## 3. goldstein2018energydispersivexray pages 18-20 (Context ID: pqac-00000035)\n\n   current. Measure and record the probe current using the\n                                                                    Faraday cup and the picoammeter.\n                                                                                    4. Collect a 60 live-time second spectrum from the copper\n                                                                        sample.\n                                                                                    5. Increase the probe current through a sequence of\n      . .\u200a\u200a\u200aFig. 16.21\u2003 The spectrum image was collected on a 128 by 128          approximately 10\u201320 steps from the initial probe current\n             pixel grid representing 4\u2009\u00d7 4 mm. After data rotation to view the x-y         to approximately 2 times the optimal probe current.\n             plane, the first energy slice, 1 out of 1024, is shown. It appears black         Collect a 60 live-time second spectrum at each probe\n           because it contains no counts                                       current and measure and record the probe current using\n                                                                         the Faraday cup. A plot of such a measurement sequence\n                                                                                                  is shown in .\u2003 Fig. 16.23 (upper).\n                                                                                    6. Integrate the total number of counts in the range of\n                                                                      channels representing the Cu K-L2,3 characteristic peak.\n16                                                              (You don\u2019t need to background correct the integral.) Plot\n                                                                         the measured intensity divided by the probe current\n                                                                            against the measured probe current. The result should\n                                                                 be a horizontal line, as shown in .\u2003 Fig. 16.23 (lower).\n                                                                                       1.  If the line is not horizontal, the problem may be in the\n                                                                              detector or in the probe current measurement.\n                                                                                       2. The probe current measurement could be non-linear\n                                                                meaning the plot of the measured probe current to\n                                                                              true probe current is not a straight line.\n                                                                                       3.  Alternatively, the probe current may have a zero\n                                                                                              offset. The zero offset can be measured by blanking\n                                                                            the beam and recording the measured current at zero\n      . .\u200a\u200a\u200aFig. 16.22\u2003  Extracting the Cu L-family lines from the spectrum              true current. Subsequent probe current measurement\n            planes 89 to 97                                                can be offset by this value.\n\n         probe current, due to the loss of useful electrons during the\n          dead-time.                                                   16.3.6\u2002 Energy Calibration Linearity\n                   It is very important for accurate quantitative analysis that\n          the measured X-ray intensity is linear with respect to the   Consistent energy  calibration  is  critically important  for\n            effective probe dose. Twice the effective probe dose should   reproducible quantitative analysis. Pick a nominal channel\n         produce twice the measured  intensity. Not only  is  this  width (5-eV/channel will work fine in almost all cases) and                                                                                                        227                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n. .\u200a\u200a\u200aFig. 16.23\u2003 The number of\nX-rays recorded in the spectrum             3,000,000\nshould scale linearly with the                                      f(x) = 35876.1202787172x\ndose (the product of live-time                          R2 = 0.9999923818\nand probe current)                         2,500,000\n\n                                         2,000,000\n\n\n                                         1,500,000                                                                                        Counts                                                                   Det 2\n                                         1,000,000                                                                   Linear (Det 2)\n\n\n                                         500,000\n\n\n                                           0\n                                            0    10   20   30   40   50   60   70   80   90\n                                                              Probe dose (nA.s)\n\n\n                                      36,050\n\n                                      36,000\n                                      35,950\n\n                                      35,900\n\n                                      35,850                                                                                      (nA.s)\n              / 35,800\n                                      35,750                                                                Det 2                                                                                      Counts\n                                      35,700\n\n                                      35,650\n                                      35,600\n\n                                      35,550\n                                         0        0.2       0.4        0.6       0.8       1        1.2       1.4\n                                                                 Probe current (nA)\n\n\n\nuse this value for all your data acquisition. Before each day\u2019s   energy. Two points are sufficient to unambiguously calibrate\nmeasurements ensure that the detector is calibrated consis-   a linear function. The calibration (peak position) and resolu-\ntently by following the same protocol to check and, if neces-   tion (peak shape) should be constant with input count rate\nsary, recalibrate your detector.                                 (or dead-time), as shown in .\u2003 Fig. 16.24.\n  On a modern pulse processor, calibration is usually per-     To a very high degree, modern EDS detectors are linear.\nformed using the EDS vendor\u2019s software. The software will  However if you look carefully in the mid-range of energies,\nprompt you to collect a spectrum from an established mate-  you many notice the KLM markers may be misaligned by a\nrial. The software will examine the spectrum and extract the   channel or two. This is evidence that your detector is not per-\npositions of various characteristic X-ray features. The soft-   fectly linear but this need not represent a true performance\nware will then perform an internal adjustment to center these   problem.\nfeatures in the correct channels. Most modern pulse proces-      Since energy calibration is so critical but is also one of\nsors perform a continuous zero offset calibration using a  many parameters that should be measured as part of a com-\n\u201czero strobe pulse\u201d the pulse processor adds to the signal   plete EDS Quality Control (QC) program, the validation will\nstream for diagnostic purposes. Thus the only parameter  be discussed in a later section.\nthey usually adjust when performing a calibration is an elec-\ntronic gain. Usually, this involves identifying a single high\nenergy characteristic line (like the Mn K-L2,3 or the Cu K-L2,3)   16.3.7  Other Items\nand adjusting the gain until this feature is centered on the\nappropriate channel. The calibration is thus a two-point cali-   zz  Light Transparency and IR Cameras\nbration\u2014either a low energy characteristic line or the zero  Most (but not all) modern EDS detectors have a vacuum\nstrobe at low energy and a second characteristic line at high   tight window that is opaque to infrared and visible light.          228    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.24\u2003 The position and\n           widths of the characteristic peaks\n           should not vary with probe cur-\n             rent                               15 000\n\n                                                                                                                 Counts 10 000\n\n                                             5 000\n\n\n\n                                                0\n                  \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035]\n\nStatus: Paper Count=30 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=36 | Current Cost=$0.1744 | Disease-Target Evidence=0",
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+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035]\n\nStatus: Paper Count=30 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=36 | Current Cost=$0.1744 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036]\n\nStatus: Paper Count=30 | Relevant Papers=10 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=37 | Current Cost=$0.1839 | Disease-Target Evidence=0",
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+                "content": "## 1. giunto2025harnessingautomatedsemeds pages 4-6 (Context ID: pqac-00000037)\n\nnd lab-synthesized samples of known compositions spanning elements from nitrogen to bis-\n 66  muth, AutoEMXSp achieves atomic fraction measurements with relative deviations typically below 5\u201310%\n 67  and resolves minor or intermixed phases with high con\ufb01dence. This study lays the groundwork for fully\n 68  automated, high-throughput SEM-EDS compositional analysis of as-deposited powder materials, paving\n 69  the way for its integration into modern autonomous laboratories for accelerated materials discovery and\n 70  optimization.\n\n71 2 Results\n\n72  2.1 Framework for automated powder compositional analysis\n\n 73  Fully automated compositional analysis of as-deposited powders is achieved through a framework consisting\n 74  of four primary components: (1) autonomous SEM particle localization and EDS spectra acquisition, (2)\n 75  accurate EDS quanti\ufb01cation, (3) automated \ufb01ltering of unreliable measurements, and (4) machine learning-\n 76  based analysis of the resulting compositional data. This framework is implemented in a Python-based\n 77  software package, AutoEMXSp (Automated Electron Microscopy X-ray Spectroscopy), and demonstrated\n 78  on a cost-e\ufb00ective desktop SEM-EDS system (Thermo\ufb01sher Phenom XL G2). We present the AutoEMXSp\n 79  work\ufb02ow, schematized in Fig. 1 and described in detail in the Methods.\n 80    AutoEMXSp requires only two inputs (Fig. 1a): the sample position on the microscope stage, and the set\n 81  of elements present in the sample. Optionally, the user may provide candidate phase compositions, whose\n 82  presence is then evaluated by direct comparison with the measured compositions in the \ufb01nal step of the\n 83  work\ufb02ow.\n 84      1. Autonomous EDS acquisition. Operation begins once a powder sample is dispersed onto a carbon\n 85  tape (C-tape) stub and loaded into the SEM. AutoEMXSp \ufb01rst detects the C-tape region (Fig. 1b) and\n 86  subdivides it into a grid, with each tile de\ufb01ning a stage position for particle search. Particles are segmented\n 87  by intensity thresholding of SEM images and \ufb01ltered by size (Fig. 1c), favoring those larger than 2 \u00b5m to\n 88  reduce the mass e\ufb00ect illustrated in Extended Data Fig. 1. For each randomly-selected particle, up to \ufb01ve\n 89  EDS spot spectra are acquired (Fig. 1d); points are spaced su\ufb03ciently far apart to avoid X-ray generation\n\n\n                                                   2 90  volume overlap and are selected away from edges to minimize substrate signal contamination. Typically,\n 91  one hundred spectra of 50,000 counts each are collected per sample, with total acquisition times ranging\n 92  from 20 to 45 minutes.\n\n\n   AutoEMXSp           b C-tape detection          c   Particle localization\n\n     a       Stub position: (x, y)\n                                 Input\n         Elements: In, O\n\n       (Cnd. phases: In2O, In2O3)                                                                                               50 \u03bcm\n\n\n\n    g Cluster analysis              f  Filtering           e EDS          d Spot selection\n\n     O\n                                        Substrate signal\n                     p1                     contamination\n                                      Excessive X-ray\n                                                                                      wIn: 83%\n                        p2                  absorption\n                                                                  wO: 16%                                    Poor fit\n                                     High analytical                                          5 \u03bcm\n                                   In                 total error\n\n\n                h         In (at%)  O (at%)    Cnd. phases\n                                                    Phase composition      Output               p1 40.2\u00b10.5  59.8\u00b11.1 \u2192 In2O3 (CS: 98%)\n                                                                        identification\n                             p2 67.5\u00b10.8  32.5\u00b11.3 \u2192 In2O (CS: 93%)\n\n     Fig. 1: AutoEMXSp work\ufb02ow for powder compositional analysis. Operation begins after the\n     sample is loaded into the SEM. (a) The only required inputs are the SEM stub coordinates on the stage\n     and the elements present in the sample; optionally, the user may also provide candidate phase compositions\n     expected in the material. Automated EDS spectra acquisition is performed through (b) C-tape detection\n     and subdivision into frames, (c) particle segmentation and localization, and (d) selection of positions for\n    EDS spot measurements on individual particles. (e) The acquired spectra are \ufb01tted, and the composition\n      at each spot is quanti\ufb01ed in terms of elemental mass fractions wi. (f) Compositional data are \ufb01ltered, and\n     (g) analyzed using a k-means clustering algorithm to (h) identify the number and composition of phases\n      present in the sample.\n\n\n\n\n 93      2. Particle spectra quanti\ufb01cation. For each acquired EDS spectrum, AutoEMXSp quanti\ufb01es local\n 94  composition in the form of elemental mass fractions wi (Fig. 1e), using a modi\ufb01ed peak-to-background\n 95  (P/B) method to correct for geometry-induced artifacts. Conventional EDS quanti\ufb01cation of wi assumes\n 96  that measured peak intensities originate from a \u2018bulk\u2019 sample\u2014i.e., \ufb02at, su\ufb03ciently large to fully contain\n 97  the X-ray generation volume. In contrast, the P/B method exploits the fact that, to \ufb01rst order, the P/B\n 98  ratio of intensities is independent of geometry and thus approximately equal for particle and bulk samples\n 99  of identical composition [20, 27]:\n\n                                                           Pi,p100                                           \u2243Pi,b                                              (1)\n                                                       Bi,p    Bi,b\n\n101  Here, P and B denote peak and background intensities, with subscripts p and b referring to particle and\n102  bulk spectra, respectively. Rearranging Eq. (1) yields a geometry-corrected, bulk-equivalent peak intensity\n\n\n                                                   3103  (I\u2217i ) suitable for conventional quanti\ufb01cation models developed for bulk, polished samples:\n\n104                                          I\u2217i = Pi,b \u2243Pi,p  \u00b7 Bi,b                                        (2)\n                                                              Bi,p\n\n\n105  While Pi,p and Bi,p are extracted directly from the measured particle spectrum, Bi,b\u2014the background\n106  intensity for a hypothetical bulk sample of identical composition\u2014is unknown and must be estimated.\n107      Pi,p can be accurately obtained through Gaussian \ufb01tting of characteristic peaks. In contrast, extracting\n108  Bi,p is more challenging due to the often complex background shape underneath the peaks, in\ufb02uenced by\n109  X-ray absorption edges and detector artifacts\u2014particularly below 2 keV, as shown in Extended Data Fig. 2.\n110  In spectra with fewer than several hundred thousand counts, the background signal is low and su\ufb00ers from\n111  poor signal-to-noise; this makes Bi,p prone to \ufb01tting errors that propagate directly into the computed P/B\n112  ratio and ultimately to the quanti\ufb01ed elemental compositions. Accurate modeling of the background shape\n113   is therefore essential to the P/B method. To this end, AutoEMXSp employs physically and empirically\n114  grounded models that account for continuum X-ray generation [32, 33], X-ray absorption [34\u201336], electron\n115  backscattering [37], and detector response function [38]. We further introduce two key re\ufb01nements: a revised\n116  absorption model that captures the geometry-dependent X-ray path lengths within particles (Extended\n117  Data Fig. 3), and an attenuation term that avoids overestimation of continuum X-rays at low energies\n118  (E < 1 keV) for heavy elements (Extended Data Fig. 4). These re\ufb01nements enable signi\ufb01cantly more\n119  accurate determination of Bi,p in particle EDS spectra and, critically, the quanti\ufb01cation of light elements\n120  with low-energy characteristic X-rays, such as N, O and F.\n121     Another key challenge in applying the P/B method lies in the accurate estimation of Bi,b. This quantity\n122   is typically derived from an empirical model for continuum X-ray generation fB, expressed as Bi,b(E) =\n123  fB( \u00afZ, E), where fB  is a function of energy E and the sample\u2019s average atomic number \u00afZ [27, 28, 39].\n124  However, we \ufb01nd that commonly employed empirical formulations of fB, introduced in Refs. [32, 40\u201342],\n125  have been obtained neglecting the e\ufb00ect of the electron stopping power (S), which governs energy dissipation\n126  of the incident electron beam and strongly depends on \u00afZ. This omission introduces substantial errors in\n127  the estimation of Bi,b when the compositions of the standard and the measured sample di\ufb00er signi\ufb01cantly\n128  (see Extended Data Fig. 5), likely explaining why previous implementations of the P/B method relied\n129  on compositionally matched standards [24\u201326]. Instead, we incor\n\n## 2. giunto2025harnessingautomatedsemeds pages 7-10 (Context ID: pqac-00000038)\n\ny Fig. 7\n 200  and 8). Elemental frequency across all samples is shown in Fig. 3a; the benchmark compositions span 38\n 201  elements, ranging from nitrogen (Z = 7) to bismuth (Z = 83), primarily consisting of oxide, phosphate,\n 202  and silicate chemistries. For each element, standard reference P/B values were obtained from bulk polished\n 203  samples of the pure metallic form when available, or otherwise from simple binary or ternary compounds.\n 204  The accuracy of AutoEMXSp is quanti\ufb01ed using the relative deviation from expected value (RDEV ) of the\n 205  measured elemental atomic fraction (ni):\n\n                                                         ni \u2212ni,nominal\n 206                         RDEV =                                                       (3)\n                                                               ni,nominal\n\n\n                                                    5                   a      Single-phase wulfenite (PbMoO4)\n\n\n\n\n\n                                       PbMoO4\n\n\n\n                    Pb (at%) Mo (at%) O (at%) dRMS(at%) Cnd.   CScnd\n                         16.9\u00b11.2  16.1\u00b10.8  67.0\u00b11.5    2.1  PbMoO4  0.97\n\n\n                 b                Intermixed\n                                NaAlSiO4 + LiMn1.5Ni0.5O4\n\n\n\n\n                                 NaAlSiO4\n                                                           LiMn1.5Ni0.5O4\n\n\n\n\n\n                           Si (w%)  Mn (w%) O (w%) dRMS(w%)  Mixture   CSmix\n                         11.8\u00b13.3  22.6\u00b19.0  37.6\u00b12.5  10.8   NaAlSiO4 +  0.83\n                                                                              LiMn1.5Ni0.5O4\nFig. 2: Examples of AutoEMXSp compositional analyses. 3D plots of AutoEMXSp compositional\nmeasurements for (a) a single-phase wulfenite mineral (PbMoO4) and (b) a (sub)micron-scale two-phase\nmixture of NaAlSiO4 and LiMn1.5Ni0.5O4 [46]. Axes represent elemental (a) atomic or (b) mass fractions of\nthe plotted compositions (green dots = valid compositions; black triangles = discarded compositions). Clus-\nter centroids, indicating the average composition within each cluster, are marked by red crosses. The light\nred uncertainty ellipsoid represents the standard deviations of elemental fractions (\u03c3i), with principal axes\nlengths equal to 2\u03c3i. The tables summarize the measured compositions and the RMS of point-to-centroid\ndistances (dRMS), along with the corresponding phase or phase mixture identi\ufb01ed by AutoEMXSp, and the\nassociated con\ufb01dence scores (CScnd for single candidate phases, CSmix for two-phase mixtures). In (b), a\nsubset of three elemental mass fractions is displayed, su\ufb03cient to illustrate the large standard deviations\ncharacteristic of mixed-phase measurements. Full measurements are reported in Supplementary Fig. 3a.\nDiscarded compositions are omitted from this panel for clarity. The 2D projection onto the Si-Mn plane\nfacilitates visualization of the compositional measurements in a two-phase mixture as a linear combination\nof the two parent phase compositions.\n\n\n\n\n\n                                              6207  where ni,nominal represents the atomic fraction extracted from the nominal compound stoichiometry. Each\n208  acquired spectrum thus yields multiple RDEV values\u2014one per element detected. With the P/B method,\n209  composition measurement errors may stem from imprecise \ufb01tting, substrate signal contamination, and\n210  inherent limitations of the P/B approximation.\n211      Fig. 3b reports the distribution of 8226 RDEV values obtained from all 2483 individual spectra retained\n212  after AutoEMXSp \ufb01ltering, showing that 61.3% (84.4%) of the measured ni exhibit RDEV < 5% (10%). A\n213  non-negligible tail with RDEV > 10% highlights the risk of outlier-driven errors when only a few spectra\n214  are analyzed per sample. Substantially improved measurement accuracy is achieved by extracting atomic\n215  fractions at the cluster centroids (Fig. 3c), where 75.8% (93.6%) of RDEV values fall below 5% (10%). This\n216  improvement underscores the advantage of the AutoEMXSp strategy, which aggregates multiple spectra in\n217  clusters to average their compositions, mitigating random variability and yielding more reliable estimates.\n218  Furthermore, we highlight that the 73 RDEV values obtained from low-Z elements (N, O, F; lighter color-\n219  ing) follow similar accuracy trends as heavier elements. We note that analogous trends were observed when\n220  analyzing separately the three groups of samples\u2014i.e, minerals, commercial powders and lab-synthesized\n221  materials (Extended Data Fig. 7).\n\n\n    a\n\n\n\n\n\n         All valid spectra post-filtering          Cluster centroids                Cluster centroids\n         b                 N,O,F        c                        d          RDEV > 10%\n                                Other\n                              elements\n           61.3%                        75.8%                         71.2%\n                          84.4%                        93.6%                          90.3%\n\n\n\n\n\n     Fig. 3: Performance of AutoEMXSp benchmarked on single-phase powder samples. a, Peri-\n      odic table showing the frequency of each element\u2019s occurrence across all 74 analyzed samples; generated\n     using pymatviz [48]. b, Histogram of elemental atomic fraction (ni) relative deviation from expected value\n    (RDEV ) measured in all 2483 spectra retained after AutoEMXSp\u2019s \ufb01ltering step. Light-colored counts\n      highlight measurements of low-Z elements (N, O, F). Dark and light green bands indicate values within 5%\n     and 10% relative deviation, respectively; labeled percentages report the fraction of values in each range. c,\n     Histogram of RDEV values for ni measured at cluster centroids. d, Histogram of absolute deviation from\n     expected values (ADEV s) for centroid compositions; purple counts denote ni with RDEV > 10%. Dark\n     and light green bands indicate values within 1 at% and 2 at%, respectively.\n\n\n\n222     Absolute deviations from the expected value (ADEV , de\ufb01ned as = ni \u2212ni,nominal) for centroid com-\n223  positions are shown in Fig. 3d, with 71.2%/90.3%/95.8% of values measured within 1/2/3 at%, indicating\n\n\n                                                   7 224  generally modest absolute errors. Typically, ADEV values are larger for binary compounds, as discussed\n 225  in Extended Data Fig. 8. In Fig. 3d, we highlight that among the 15 reported centroid ni values with\n 226 RDEV > 10% (purple counts), 12 have ADEV < 1 at%, suggesting that large relative errors primarily\n 227  occur at low concentrations (< 10 at%) where absolute deviations remain small. Finally, we assess the\n 228  measurement uncertainty delivered by AutoEMXSp for single-phase samples. Excluding lab-synthesized\n 229  materials to minimize the in\ufb02uence of compositional inhomogeneity (Extended Data Fig. 9), we \ufb01nd that\n 230  48.1% (91.2%) of measured ni exhibit standard deviations \u03c3i < 1 at% (< 2 at%), corresponding to relative\n 231  uncertainties below 5% (10%) in 66.2% (95.6%) of cases, as shown in Extended Data Fig. 9.\n 232      Overall, the results demonstrate high compositional measurement accuracy for single-phase samples,\n 233  providing robust experimental data for ML-based analyses to resolve phase compositions in multi-phase\n 234  materials.\n\n 235  2.3 Versatility across compositionally complex and diverse powders\n\n 236  The proposed framework enables composition analysis across a broad spectrum of powder samples, spanning\n 237  signi\ufb01cant diversity in phase content and chemistry. Representative examples are illustrated in Fig. 4.\n 238  Owing to its re\ufb01ned spectral \ufb01tting routines and standard-based EDS quanti\ufb01cation, AutoEMXSp can\n 239  accurately measure complex multi-element compositions, such as the K-412 NIST standard (Fe: 3.1 at%, Mg:\n 240  10.6 at%, Ca: 6.0 at%, Al: 4.0 at%, Si: 16.8 at%, O: 59.4 at%; Fig. 4a), where peak overlapping complicates\n 241  accurate background \ufb01tting (Extended Data Fig. 2). The method also remains e\ufb00ective in the presence of\n 242  undetectable elements in low weight fraction, such as Li in Li3NiCoMnO6 (Fig. 4b).\n 243    The high measurement accuracy of AutoEMXSp enables the identi\ufb01cation of distinct phases with simi-\n 244   lar compositions within multi-phase samples. This is demonstrated in Fig. 4c, where a three-phase mixture\n 245  of MnO, Mn2O3, and Fe2O3 is correctly resolved despite the presence of chemically similar input candi-\n 246  date compositions such as MnO2, Mn3O4, and FeO. The close compositional proximity of Mn3O4 to the\n 247  green cluster centroid reduces the con\ufb01dence score (CScnd) for Mn2O3 (see Methods), yet the correct phase\n 248  composition is identi\ufb01ed. Additionally, a key strength of AutoEMXSp lies in its sensitivity to minority\n 249  phases. By employing the k-means clustering algorithm, which is density-independent, clusters consisting\n 250  of as few as one or two points can be isolated, enabling identi\ufb01cation of phases present \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=39 | Current Cost=$0.1839 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "## 1. dumit2025challengesandfuture pages 9-10 (Context ID: pqac-00000036)\n\nmputational modeling requires measures to ensure     als\u2019 physicochemical characterization.[111] Similarly, as the CRED                                            Conditions\nthe reliability and predictivity of its output. In the past years, the    evaluation method lacks nano-speci\ufb01c guidance, particularly for\nnanosafety \ufb01eld has served as a testing ground for the develop-    evaluation of ecotoxicity studies, the nanoCRED criteria were\nment of data-driven prediction models, leading to the creation of    developed[112] and implemented in the Science in Risk As-\nmore re\ufb01ned and detailed scoring concepts. The Klimisch score   sessment and Policy (SciRAP) project as a basis for judging\nrepresented the foundation for these developments, incorporat-   whether a study is adequate for chemical risk assessment.[11]\ning nano-speci\ufb01c criteria, as will be discussed in the following   In addition, the SciRAP in vitro  tool[113] was extended with\nsections.                                                        nanomaterial-relevant criteria, covering 38 criteria for report-\n                                                              ing quality, 19 criteria for methodological quality, and 4 guid-\n                                                           ance items to evaluate relevance. It supports harmonized eval-\n5.2. Nanomaterial-Speci\ufb01c Quality Criteria                         uation of nanomaterial in vitro toxicity studies and promotes                                                                   transparent, structured use of such data in the regulatory hazard                                                                                                                                                                                                                                              (https://onlinelibrary.wiley.com/terms-and-conditions)\nDi\ufb00erent  activities  for evaluating and labeling data  quality    assessment.[11]                                                             on\nhave been initiated. The Nanomaterial Data Curation Initia-     The development of data quality scoring systems has been an                      Wiley\ntive (NDCI), a project of the National Cancer Informatics Pro-    iterative process with many frameworks interlinked and build-                          Online\ngram Nanotechnology Working Group (NCIP NanoWG), ex-   ing upon one another (Figure 2). Card & Magnuson (2010)[114]\nplores the di\ufb00erent aspects of data curation within the de-   published a two-step method to assess the quality of studies ex-                               Library\nvelopment of informatics approaches to understanding nano-   amining the toxicity of nanomaterials, by using ToxRTool[101] to             for\n                                                                                                                                                                                                                                                                                                                                                                                 rulesmaterial behavior.[104] The initiative has published a series of   rank study reliability based on the adequacy of design, docu-\n                                                                                                                                                    of\narticles, one of which focuses on data quality and complete-   mentation of methods, materials, and results, and by determin-                  use;\nness as critical sub-topics in nanomaterial data curation.[9] An-   ing the completeness of physicochemical parameters being in-         OA\nother initiative is the establishment of the European Registry    vestigated. Building on this foundation, an approach to evaluate                                   articles\nof Materials.[105,106] Existing metadata reporting standards sup-   nanomaterial data quality was developed in the H2020 project             are\nport the documentation of experimental conditions and protocols   GUIDEnano.[115] This method aimed to minimize reliance on ex-\nfor bio-nano studies (MIRIBEL[107]) and material characteristics    pert judgement by modifying 1) the ToxRtool to evaluate the qual-                                   governed\n(MINChar[108] and MIAN[109]), as well as reporting focused on     ity of both human toxicity and ecotoxicity studies, and 2) the study         by\nspeci\ufb01c experiments such as nanomaterials protein corona deter-    of Langdon et al.,[116] which is adapted to all the environmental             the\nmination (MINBE[110]). Additionally, a NanoTox Metadata List[39]   compartments. Based on the GUIDEnano[115] and DaNa criteria                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  applicablewas elaborated to report the toxicological context of a study. The    checklist,[117] Kokalj et al.[118] developed assessment criteria for\nneed to assess nanomaterial data quality has led to adaptation    the quality of studies tailored to (nano)plastics safety research. In                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              Creative\n                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     CommonsAdv. Sustainable Syst. 2026, 10, e00567        e00567 (9 of 18)     \u00a9 2025 The Author(s). Advanced Sustainable Systems published by Wiley-VCH GmbH\n                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     License                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            23667486,\n                                                                                                                                                                                                                                                                                                                                                                                   2026,\nwww.advancedsciencenews.com                                                                  www.advsustainsys.com          4,\nthe approach published by Comandella et al.,[119] completeness of    nal template design. The resulting (meta)data template provides                                                Downloaded\nphysicochemical data on nanomaterials is assessed by assigning  \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036]\n\nStatus: Paper Count=30 | Relevant Papers=10 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=37 | Current Cost=$0.1839 | Disease-Target Evidence=0",
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+              {
+                "role": "assistant",
+                "content": "Let me now update the plan and continue gathering evidence on remaining topics:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01HErKQw25o1ja6tuEfc4Jwk",
+                    "type": "function",
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+                      "arguments": "{\"plan_objective_id\": 1, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 1,\\n  \\\"objective\\\": \\\"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\\\",\\n  \\\"rationale\\\": \\\"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\\\",\\n  \\\"evaluation\\\": \\\"Multiple citations provide comprehensive list of required metadata for standard spectra.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_018dKtGyHZ78RnXpQHfVEh1i",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 2, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 2,\\n  \\\"objective\\\": \\\"Research transferability of standard spectra between instruments - detector variation, published methodologies\\\",\\n  \\\"rationale\\\": \\\"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\\\",\\n  \\\"evaluation\\\": \\\"Sufficient evidence gathered on transferability challenges and published methodologies.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_01LUNsQ58xGhPsHUqs7d57hK",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 3, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 3,\\n  \\\"objective\\\": \\\"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\\\",\\n  \\\"rationale\\\": \\\"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\\\",\\n  \\\"evaluation\\\": \\\"Sufficient evidence with numerical accuracy figures.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_01Btxo21YBAmma85FD4efXF3",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 6, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 6,\\n  \\\"objective\\\": \\\"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\\\",\\n  \\\"rationale\\\": \\\"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \\u00b15% RDEV, 82% within \\u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\\\",\\n  \\\"evaluation\\\": \\\"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01HErKQw25o1ja6tuEfc4Jwk",
+                "info": {
+                  "start_ts": 4918.332153139,
+                  "end_ts": 4918.33941302
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_018dKtGyHZ78RnXpQHfVEh1i",
+                "info": {
+                  "start_ts": 4918.339476441,
+                  "end_ts": 4918.340028872
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01LUNsQ58xGhPsHUqs7d57hK",
+                "info": {
+                  "start_ts": 4918.340061278,
+                  "end_ts": 4918.340539165
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \u00b15% RDEV, 82% within \u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\",\n      \"evaluation\": \"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01Btxo21YBAmma85FD4efXF3",
+                "info": {
+                  "start_ts": 4918.340600173,
+                  "end_ts": 4918.340958927
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me look for information on physical standards and public repositories:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_017yoxpw43hPbCVRJN9gHktc",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"question\": \"What physical standards are used for Al, Si, Mg in EPMA and EDS analysis? Which NIST SRMs are relevant (SRM 470 K-glasses, SRM 481, 482, 2063a)? What compound standards are used for Mg (MgO, periclase, forsterite, spinel)? Is pure Mg metal usable as an EPMA standard?\"}",
+                      "name": "gather_evidence"
+                    }
+                  },
+                  {
+                    "id": "toolu_01EhgpJ2DAaHT13QuSVLT1hR",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"question\": \"What are the standards used at 5 keV in the Newbury and Ritchie 2024 study? What standards did they use for Mg, Al, Si specifically?\"}",
+                      "name": "gather_evidence"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000039\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 5-6'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt shows EPMA/EDS analyses using both pure-element and oxide standards. For Al (in SRM 2062) the authors used pure element standards (Table 7: \"Pure Element Standards; Al K ...\"). Si is analyzed in different sample types; for glasses (SRM 470 K411 and K412) the analyses use oxide standards rather than pure elements (\"Oxide Standards Except for Fe\"). SRM 470 (K\u2011glass; K411 and K412) is explicitly used for glass analyses; SRM 2062 (Al\u2013Ti\u2013Nb\u2013W alloy) and SRM 483 (Fe\u20133Si transformer steel) are also included in these tables. Mg is treated as an oxide in the glass analyses: oxygen was either by assumed stoichiometry or \"O Directly Analyzed (MgO)\" (Tables 8b, 9b), indicating MgO was used as a compound standard/oxygen standard in these DTSA\u2011II analyses. The excerpt does not mention NIST SRM 481, 482, or 2063a, nor does it mention compound standards such as periclase, forsterite, or spinel, and it does not state whether pure Mg metal was used or recommended as an EPMA standard. Further sources should be consulted for recommendations on periclase/forsterite/spinel or the acceptability of pure Mg metal as a standard.\n\n\n---\n\n## pqac-00000040\n\nFrom text 'newbury2024testingtheaccuracy pages 14-16'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nTable 1 (pages 14\u201316) lists the analytical standards used in this study. For Mg-containing materials the table repeatedly lists MgO as the standard. For Si-bearing materials the standard shown is SiO2, and for Al the table shows Al2O3 as a standard. The table also cites NIST SRM identifiers used in the study: entries labelled SRM470_K411_O- and SRM470_K412_O- appear in the material/standard columns, and the text explicitly mentions EDS spectra of NIST SRM 482 (Au40-Cu60) recorded at multiple beam energies. Sample preparation notes indicate materials were mounted, polished and (for non-conductors) coated with an approximately 10 nm carbon layer. The excerpt does not mention SRM 481 or SRM 2063a, nor does it list compound Mg standards such as periclase, forsterite, or spinel, nor any use of pure Mg metal as an EPMA standard\u2014those details are not present in the provided pages.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=41 | Current Cost=$0.2112 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
+                "tool_call_id": "toolu_017yoxpw43hPbCVRJN9gHktc",
+                "info": {
+                  "start_ts": 4955.347283287,
+                  "end_ts": 4987.695527357
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000041\n\nFrom text 'newbury2024testingtheaccuracy pages 14-16'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nTable 1 (continued) shows the standards used for the 5 keV analyses. In the block of columns labeled with materials ending in \u201c_5keV\u201d the Standard row lists GaP, MgO, MgO, SiO2, CaF2, K412, MgO, MgO, Al2O3, SiO2, CaF2, K411. The corresponding Ele-ment row maps those standards to elements: P, O, Mg, Si, Ca, Fe, O, Mg, Al, Si, Ca, Fe. Thus for the 5 keV measurements shown in this portion of the table (materials such as Mg-Al-P_5keV, Mg-Al-Si-Ca-Fe_5keV, Si-Pb_5keV), the standards assigned to Mg are MgO, to Al is Al2O3, and to Si is SiO2. The table therefore indicates repeated use of MgO for Mg standards and SiO2 and Al2O3 for Si and Al standards within the 5 keV dataset.\n\n\n---\n\n## pqac-00000042\n\nFrom text 'newbury2024testingtheaccuracy pages 1-3'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nThe study tested EDS microanalysis at an incident beam energy of 5 keV and implemented a standards-based, k-ratio measurement protocol using the NIST DTSA-II software. The authors analyzed a broad set of reference materials suitable for microanalysis, including NIST Standard Reference Materials (SRMs), certified reference materials (CRMs), reagent compounds, stoichiometric binary compounds, and well-characterized minerals. The NIST SRMs listed explicitly include SRM 470 K411 glass (composition O-Mg-Si-Ca-Fe) and SRM 470 K412 glass (composition O-Mg-Al-Si-Ca-Fe), along with other SRMs (e.g., SRM 479 stainless steel, SRM 481/482 metal alloys, SRM 1871\u20131875 series glasses). Reagent and stoichiometric compounds and mineral standards were also used as challenge specimens. From the excerpt, SRM 470 K411 and SRM 470 K412 are the explicit glass standards containing Mg, Si (K411) and Mg, Al, Si (K412), and these materials were included among the standards used in the 5 keV analyses.\n\n\n---\n\n## pqac-00000043\n\nFrom text 'newbury2024testingtheaccuracy pages 16-18'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt states that standards for analysis were a suite of pure elements (examples given include Si) and, where pure elements were incompatible or unstable under the vacuum/beam, stoichiometric compounds were used (example given: MgO). Non-conductive standards were coated with an ~10 nm carbon layer. The paper shows examples of spectra recorded at 5 keV (e.g., NIST SRM 482 (Au40-Cu60)), and it notes that some materials (example: AlN) were excluded because C and O became significant at reduced beam energies. The excerpt therefore indicates Mg was analyzed using a stoichiometric compound standard (MgO) and Si was included among the pure-element standards. The excerpt does not explicitly state which standard was used for Al.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=44 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
+                "tool_call_id": "toolu_01EhgpJ2DAaHT13QuSVLT1hR",
+                "info": {
+                  "start_ts": 4955.423241282,
+                  "end_ts": 5024.116549652
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now I have substantial evidence. Let me do a few more targeted searches and then prepare the answer:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_013Xyr6QH35xVpVC82morYnx",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"text_name_list\": [\"goldstein2018quantitativeanalysisthe pages 6-8\", \"goldstein2018quantitativeanalysisthe pages 8-9\"]}",
+                      "name": "read_text"
+                    }
+                  },
+                  {
+                    "id": "toolu_0164vD694gdqqzYoWCCo4hYn",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"text_name_list\": [\"newbury2019electronexcitedxraymicroanalysis pages 8-10\"]}",
+                      "name": "read_text"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "## 1. goldstein2018quantitativeanalysisthe pages 8-9 (Context ID: pqac-00000045)\n\nAnalysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n         20.3 Examples of the k-ratio/Matrix              the error budget. In this analysis and the analyses reported\n             Correction Protocol with DTSA II            below, the relative deviation from the expected value (RDEV)\n           (Newbury and Ritchie 2015b)                    (also referred to as \u201crelative error\u201d) is calculated with the\n                                                                       \u201cexpected\u201d value taken as the stoichiometric formula value or\n          20.3.1  Analysis of Major Constituents            the value obtained from an \u201cabsolute\u201d analytical method, just\n                 (C\u2009>\u20090.1 Mass Fraction) with                 as in gravimetric analysis:\n               Well-\u00adResolved Peaks                                                                                         \uf8ee ( Analyzed value \u2212 expected value ) \uf8f9\n                                                  RDEV = \uf8ef                                 \uf8fa \u00d7 100%    (20.3)\n         The EDS spectra of the minerals pyrite (FeS2) and troilite               \uf8f0         expected value         \uf8fb\n          (FeS) measured at E0\u2009=\u200920 keV with a dead-time of\u2009~\u200910\u2009% are\n        shown in .\u2003 Fig. 20.4 and feature well separated peaks for the  Optimizing Analysis Strategy\n         Fe K- and L- families and the S K-family. These spectra were                                                           The DTSA II analysis report includes for each analyzed ele-\n          analyzed with Fe and CuS serving both as peak-fitting refer-                                                         ment the ZAF factors and the estimated uncertainties in\n          ences and as standards. CuS is chosen for the S reference and                                                                        these factors as well as uncertainties due to the counting sta-\n          standard rather than elemental S since CuS is stable under                                                                                          tistics associated with the measurements of the unknown and\n           electron bombardment while elemental S is not stable. The                                                                           of the standard (Ritchie and Newbury 2012). Careful exami-\n         spectrum for FeS and the residual spectrum after peak-fitting                                                                     nation of these factors can be used to refine the analytical\n           are also shown in .\u2003 Fig. 20.4. The results for seven replicate                                                                           strategy to optimize the measurement. Reducing the uncer-\n           analyses are listed in .\u2003 Table 20.1 (FeS) and .\u2003 Table 20.2 (FeS2)   tainty due to the counting statistics requires increasing the\n          along with the ZAF correction factors and the \u00adcomponents of                                                                        dose. The absorption factor A is strongly influenced by the\n\n\n\n             a  180 000                                                                                                                                                FeS_20kV10n9%DT_50s\n                                                                                                                                                FeS_20kV10n9%DT_50s\n                160 000\n                                                                                     E0 = 20 KeV\n                140 000                                                                           FeS\n                120 000                                                      FeS2\n                                   Counts 10080 000000\n\n                 60 000\n\n                 40 000\n\n                 20 000\n\n                      0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                  Photon energy (keV)\n\n           b\n                 14 000                                                                                                            FeS_20kV10n9%DT_50s\n                                                                                                                                                 Residual_FeS_20kV10n9%DT_50s\n\n                 12 000\n                                                                           E0 = 20 KeV\n                 10 000                                          FeS\n                                                                                   Fitting residual\n                                   Counts   8 00020              6 000\n\n                  4 000\n\n                  2 000\n\n                      0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                  Photon energy (keV)\n\n\n      . .\u200a\u200a\u200aFig. 20.4\u2003  a SDD-EDS spectra of Pyrite (FeS2) (blue) and meteoritic Troilite (FeS (red) at E0\u2009=\u200920 keV. b NIST DTSA-II analysis of FeS using Fe and\n          CuS as peak-fitting references and as standards. The original spectrum (red) and the residual spectrum after peak-fitting (blue) are shown                                                                                                               317                                      20\n20.3 \u00b7 Examples of the k-ratio/Matrix Correction Protocol with DTSA II\n\n\n\n  . .\u200a\u200a\u200aTable 20.1\u2003  Analysis of FeS (meteoritic troilite) at E0\u2009=\u200920 keV     . .\u200a\u200a\u200aTable 20.3\u2003  Analysis of FeS at E0\u2009=\u200910 keV with CuS and Fe as\n    with CuS and Fe as fitting references and standards Integrated              fitting references and standards Integrated spectrum count,\n    spectrum count, 0.1\u201320 keV\u2009=\u20097,048,000; uncertainties expressed         0.1\u201310 keV\u2009=\u20095,630,000; uncertainties expressed in mass\n    in mass fraction. Analysis performed with Fe K-L2,3 and S K-L2,3              fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.5052        0.4948              Cav (atom frac)                     0.503           0.497\n\n    Z-correction                        0.977          0.95               Z-correction                       0.973           0.937\n\n    A-correction                        1.118          0.983              A-correction                      1.041           0.997\n\n    F-correction                        1.003         1                  F-correction                       1.001          1\n\n   \u03c3 (7 replicates)                     0.00075       0.00075         \u03c3 (7 replicates)                    0.00056         0.00056\n     \u03c3Rel (%)                             0.15\u2009%         0.15\u2009%                \u03c3Rel (%)                            0.11\u2009%           0.11\u2009%\n   RDEV (%)                           1.00\u2009%       \u22121.00\u2009%          RDEV (%)                          0.59\u2009%        \u22120.59\u2009%\n\n   C (mass frac, single analysis)         0.3699        0.6305          C (mass frac, single analysis)        0.3627          0.6257\n\n    Counting error, std                 0.00020       0.0003           Counting error, std                0.0002          0.0008\n\n    Counting error, unk                 0.00020       0.0007           Counting error, unk                0.0003          0.0018\n\n    A-factor error                       0.0017        0.0002             A-factor error                     0.0006          4.10E-05\n\n    Z-factor error                       2.20\u00d7105      4.10\u00d710\u20136           Z-factor error                      2.20\u00d710\u20135       1.30\u00d710\u20136\n\n   Combined errors                   0.0017        0.0008          Combined errors                  0.0007          0.0019\n\n\n\n  . .\u200a\u200a\u200aTable 20.2\u2003  Analysis of FeS2 (pyrite) at E0\u2009=\u200920 keV with CuS      . .\u200a\u200a\u200aTable 20.4\u2003  Analysis of FeS2 at E0\u2009=\u200910 keV with CuS and Fe as\n   and Fe as fitting references and standards Integrated spectrum             fitting references and standards Integrated spectrum count,\n    count, 0.1.\u201320 keV\u2009=\u20097,765,000; uncertainties expressed in mass          0.1\u201310 keV\u2009=\u20096,253,000); uncertainties expressed in mass\n     fraction. Analysis performed with Fe K-L2,3 and S K-L2,3                       fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.6726        0.3274              Cav (atom frac)                     0.671           0.329\n\n    Z-correction                        0.957          0.928              Z-correctio\n\n## 2. goldstein2018quantitativeanalysisthe pages 6-8 (Context ID: pqac-00000046)\n\nin the center of the Faraday cup aperture\n                                                        opening, the primary beam electrons as well as all BSEs\nwhere A is the active area of the detector and r is the distance  and SEs generated at the inner surfaces are collected with\nfrom the X-ray source on the specimen to the detector. Some   very little loss through the small aperture, so that the cur-\nEDS  systems  are mounted on  a  retractable arm  that   rent flowing to the electrical ground is the total incident\nenables the analyst to choose the value of r. A consistent and  beam current.           314    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n          20.2.4  Choosing the Beam Current            SDD-EDS, a more conservative counting strategy is sug-\n                                                                          gested, such that the beam current is chosen so that the\n           After the analyst has chosen the EDS time constant, the   dead-\u00adtime on the most highly excited standard of interest,\n           detector solid angle (for a retractable detector), and the beam   for example, Al or Si, is less than 10\u2009%. Despite the opera-\n           energy, the beam current should be chosen so as to give a   tion of the anti-coincidence function, SDD-EDS systems\n          reasonable detector throughput, as expressed by the system   typically show evidence of coincidence peaks above a dead-\n          dead-time. .\u2003 Figure 20.2 shows the relationship between the  time of 10\u2009% from highly excited parent peaks, as illustrated\n          input count rate (ICR) of X-rays that arrive at the detector   in .\u2003 Fig. 20.3, which shows the in-growth of an extensive\n         and the output count rate (OCR) of photons that are actually   set of coincidence peaks from several parent peaks. If it is\n           stored in the measured spectrum. The OCR initially rises lin-  important to measure low intensity X-ray peaks that cor-\n           early with the ICR, but as photons arrive at a progressively  respond to minor or trace constituents that occur in spec-\n           greater rate at the detector, photon coincidence begins to   tral regions affected by coincidence peaks, then choosing\n          occur and the anti-coincidence function begins to reject   the low dead-\u00adtime to minimize coincidence will be an\n           these coincidence events, reducing the OCR. Eventually a  important issue in selecting the general analytical condi-\n       maximum OCR value is reached beyond which the OCR   tions. If there is no interest in measuring X-ray peaks of\n          decreases with increasing ICR, eventually falling to zero   possible constituents that occur in the region of coinci-\n           (\u201cparalyzable dead-time\u201d). A useful measure of the activity  dence peaks, then these regions can be ignored and a\n            state of the EDS detector is the system \u201cdead-time\u201d which is  counting strategy that involves higher dead-time operation\n          defined as                                             can be used.\n                                                          Once the analytical conditions (EDS time constant, solid\n                                               100    (20.2)   angle, beam energy, and beam current appropriate to the                Dead-time ( % ) = \uf8ee\uf8f0 (                           ICR \u2212 OCR ) / ICR \uf8f9\uf8fb\u2217\n                                                                 complete suite of standards) have been chosen, these condi-\n      A classic strategy with the low throughput Si(Li)-EDS is to   tions should be used for all standards and unknowns to\n           select a beam current on a highly excited pure element such   achieve the basic measurement consistency required for the\n           as Al or Si that produces a dead-time of 30\u2009% or less. With   k-ratio/matrix corrections protocol.\n\n\n\n      . .\u200a\u200a\u200aFig. 20.2\u2003  Output count rate\n           (OCR) vs. input count rate for an\n          SDD-EDS array of four 10-mm2                                  30 mm2 SDD at medium throughtput\n            detectors\n                                                  200,000\n                                                                                                                        Ideal response\n                                                                                                         (no deadtime)\n\n                                                  160,000\n                                                                                                                                                                                                    (counts/s)\n                                                  120,000\n                                                                              Rate\n                                                                                                  Count\n                                                    80,000\n                                                                                                                      Output\n\n                                                    40,000\n20\n\n                                                   0\n                                                     0          40,000        80,000       120,000       160,000      200,000\n                                                                                     Input Count Rate (counts/s)                                                                                                               315                                      20\n20.2 \u00b7 Instrumentation Requirements\n\n\n\n\n   a\n     3 500 000                                                                                                    K412_20kV5nAMED5eV40kHz3DT_5ks\n\n     3 000 000                                  SRM470 Glass K412\n                                                           E0 = 20 keV\n                                                  Deadtime = 3%\n     2 500 000\n\n\n     2 000 000       Counts\n     1 500 000\n\n\n     1 000 000\n\n     5 000 000\n\n\n            0\n                0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                       Photon energy (keV)\n\n  b\n                                                                                                                     K412_20kV5nAMED5eV40kHz3DT_5ks\n\n      100 000\n\n\n       80 000\n\n\n       60 000       Counts\n\n\n       40 000\n\n\n       20 000\n\n\n            0\n               0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                       Photon energy (keV)\n\n   c                                                                                                                       K412_20kV5nA40kHz_3DT\n                                                                                      Al+Al                                                                        K412_20kV50nA387kHz_29DT\n\n                                                                         SRM470 Glass K412                                                      Si+O                Si+Mg;      Si+Si                                           E0 = 20 keV\n                                                                                Deadtime = 3%\n                                                                                Deadtime = 29%         Counts\n                                                                                                                                     Mg+Ca      Si+Ca\n\n\n\n\n\n       0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0         10.0\n                                                      Photon energy (keV)\n\n\n. .\u200a\u200a\u200aFig. 20.3\u2003 SDD-EDS spectra of NIST SRM (glass K412, E0\u2009=\u200920 keV: a, b at 3\u2009% dead-time (red); c 3\u2009% (red) and 29\u2009% dead-time (blue), showing\nin-growth of coincidence peaks           316    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n         20.3 Examples of the k-ratio/Matrix              the error budget. In this analysis and the analyses reported\n             Correction Protocol with DTSA II            below, the relative deviation from the expected value (RDEV)\n           (Newbury and Ritchie 2015b)                    (also referred to as \u201crelative error\u201d) is calculated with the\n                                                                       \u201cexpected\u201d value taken as the stoichiometric formula value or\n          20.3.1  Analysis of Major Constituents            the value obtained from an \u201cabsolute\u201d analytical method, just\n                 (C\u2009>\u20090.1 Mass Fraction\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=47 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "read_text",
+                "tool_call_id": "toolu_013Xyr6QH35xVpVC82morYnx",
+                "info": {
+                  "start_ts": 5066.357680303,
+                  "end_ts": 5080.289543007
+                }
+              },
+              {
+                "role": "tool",
+                "content": "## 1. newbury2019electronexcitedxraymicroanalysis pages 8-10 (Context ID: pqac-00000044)\n\n                                       1.0037                                          0.6646                                  0.3354\n\n       RDEV (%)                                                                             \u22120.32                                      0.63\n\n       \u03c3 (seven replicates)                          0.0131                                         0.00222                                0.00222\n\n       \u03c3 relative (%)                                   1.3                                                0.33                                      0.66\n\n                                                          S (Mass Concentration) Ideal = 0.4006            Mo (Mass Concentration) Ideal = 0.5994\n\n\n         Single analysis                        1.0010                          0.3971                                              0.6039\n\n       RDEV (%)                                                        \u22120.87                                                  0.75\n\n        k uncertainty                                                             0.0006, 0.15%                                          0.0014, 0.23%\n\n         A-factor uncertainty                                                       0.0006, 0.15%                                          0.0007, 0.12%\n\n         Z-factor uncertainty                                                     0.000028, 0.0001%                                    0.000045, 0.0001%\n\n       Combined uncertainty                                                    0.0008, 0.20%                                          0.0016, 0.26%\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X      Microscopy and Microanalysis                                                                                           9\n\n\n\n\n\n         Fig. 4. EDS spectrum of SrWO4 (E0 = 10 keV) showing the region of the Sr L-family and the W M-family; lower, the peak fitting residual spectrum (blue) after fitting\n         for Sr and W.\n\n\n      repeat the analysis and include Ti in the suite of elements for   which qualitative and quantitative analyses with the construction\n       analysis.                                                             of peak fitting residual spectrum are applied iteratively (Newbury\n                                           & Ritchie, 2018). After each round of peak fitting, the residual spec-\n                                                              trum is inspected to discover any previously unrecognized peaks\n       Iterative Qualitative\u2013Quantitative Analysis to Discover Hidden\n                                                              and to assign them to the correct elements using the characteristic\n     Peaks\n                                                                  peak markers. Note that discontinuities in the continuum back-\n      This example of NIST microanalysis glass K2496 illustrates the   ground caused by absorption edges and broadened by the detector\n       basis for a robust analytical strategy for EDS microanalysis in    function into peak-like structures can also be detected.\n\n\n       Table 12. Analysis of SrWO4 [E0 = 10 keV; SrF2 and W Used as Fitting References (Sr L-family and W M-family) and as Standards; Oxygen Was Calculated by the\n      Method of Assumed Stoichiometry; Values in Atom Concentration; Combined Uncertainties as Estimated from NIST DTSA-II].\n\n                             Raw Analytical Total         O (Atomic Concentration by                  Sr (Atomic           W (Atomic\n         Parameter                 (Mass Concentration)                   Stoichiometry)                      Concentration)               Concentration)\n\n\n        Mean                              1.0017                              0.6660                             0.1678                       0.1661\n\n        RDEV (%)                                                        \u22120.10                                 0.68                       \u22120.33\n\n        \u03c3 (seven replicates)                0.0019                             0.00053                           0.00065                      0.00033\n\n        \u03c3 relative (%)                       0.19                                 0.80                                 0.39                           0.20\n\n                                            O (Mass Concentration)              Sr (Mass Concentration)        W (Mass Concentration)\n                                                                           Ideal = 0.1908                         Ideal = 0.2612                          Ideal = 0.5480\n\n\n          Single analysis                     1.0029                      0.1913                         0.2627                              0.5489\n\n        RDEV (%)                                                        0.27                             0.58                                  0.16\n\n         k uncertainty                                                                                       0.0007, 0.27%                         0.0009, 0.16%\n\n           A-factor uncertainty                                                                                0.0093, 3.5%                          0.0077, 1.4%\n\n           Z-factor uncertainty                                                                               2.7\u00d710\u22125, 0.010%                     5.8\u00d710\u22125, 0.011%\n\n        Combined uncertainty                                                                              0.0093, 3.5%                          0.0078, 1.4%\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X     10                                                                                 Dale E. Newbury and Nicholas W.M. Ritchie\n\n\n\n\n\n        Fig. 5. EDS spectrum of the mineral Benitoite (BaTiSi3O9) (E0 = 10 keV) showing the region of the Ti K-family and the Ba L-family; lower, the peak fitting residual\n      spectrum (blue) after fitting for Ti and Ba.\n\n\n\n         Additionally, when the standards-based intensity ratio proto-    analytical total provide important information, especially a low\n      col is applied for quantitative analysis, the raw (unnormalized)    total which should be considered as a possible indicator of a miss-\n      analytical total, which is the sum of all elemental concentrations    ing element(s).\n     including oxygen calculated by the method of assumed stoichi-    An example of iterative qualitative\u2013quantitative analysis  is\n     ometry,  is determined. As discussed above, deviations in the   presented in Figure 8 and Table 15 for the analysis of NIST\n\n\n\n      Table 13. Analysis of Benitoite (BaTiSi3O9) [E0 = 10 keV; Ti and Sanbornite (BaSi2O5) Used as Fitting References (Si K-family, Ti K-family, and Ba L-family) and as\n      Standards; Oxygen Was Calculated by the Method of Assumed Stoichiometry; Values in Atom Concentration; Combined Uncertainties as Estimated from NIST\n       DTSA-II].\n\n                           Raw Analytical Total      O (Atomic Concentration             Si (Atomic               Ti (Atomic           Ba (Atomic\n        Parameter                 (Mass Concentration)              Stoichiometry)              Concentration)         Concentration)         Concentration)\n\n\n       Mean                             0.9991                        0.6425                     0.2143                  0.0708                0.0723\n\n       RDEV (%)                                                   \u22120.05                          0.0                  \u22120.84                    1.3\n\n       \u03c3 (seven replicates)                                             0.000049                   0.00013                0.00019               0.00013\n\n       \u03c3 relative                                                  0.008%                  0.06%                0.26%               0.18%\n\n                            O (Mass Concentration)        Si (Mass Concentration)          Ti (Mass Concentration)       Ba (Mass Concentration)\n                                                  Ideal = 0.3482                  Ideal = 0.2038                    Ideal = 0.1158                     Ideal = 0.3321\n\n         Single analysis       0.9995               0.3473                  0.2033                        0.1147                         0.3347\n\n       RDEV (%)                             \u22120.26                  \u22120.25                       \u22120.95                            0.78\n\n        k uncertainty                                                         0.0001, 0.05%                  0.0004, 0.35%                   0.0011, 0.32%\n\n         A-factor          \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=45 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "read_text",
+                "tool_call_id": "toolu_0164vD694gdqqzYoWCCo4hYn",
+                "info": {
+                  "start_ts": 5066.358385922,
+                  "end_ts": 5076.70606513
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me update the remaining plan objectives and create the artifacts:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_012fetPhMSnahqoMA7t6K9o1",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 4, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 4,\\n  \\\"objective\\\": \\\"Research physical standards suppliers and certified reference materials for Al, Si, Mg\\\",\\n  \\\"rationale\\\": \\\"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Newbury & Ritchie 2024 lists NIST SRMs (470 K411/K412, 479, 481, 482, 1871-1875). They used MgO for Mg, Al2O3 for Al, SiO2 for Si at 5 keV. The paper lists SPI (West Chester, PA) for minerals, Geller Microanalytical Laboratory (Topsfield, MA) for stoichiometric compounds, Alfa Aesar for reagent compounds. Newbury & Ritchie 2015 describes use of MgO, KCl, FeS2, GaP, CaF2 as compound standards. Additional supplier information (Astimex, MAC, Ted Pella) from expert knowledge.\\\",\\n  \\\"evaluation\\\": \\\"Concrete supplier names and standards identified with sufficient detail from the literature.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_013xnvkza6w1rdE9aM8kNgtr",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 5, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 5,\\n  \\\"objective\\\": \\\"Research public repositories of EDS/EPMA spectra\\\",\\n  \\\"rationale\\\": \\\"Question 5 asks about downloadable spectrum libraries in EMSA format\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"NIST DTSA-II includes a built-in standards database. The ISO 22029 EMSA/MAS format is the standard format. No large publicly downloadable measured EDS standards library was identified in the literature beyond the DTSA-II internal database. The de-ma.ch web database (Allaz 2024) and Zenodo deposits exist but were not obtainable for detailed review. Remote standards approach described by Newbury & Ritchie.\\\",\\n  \\\"evaluation\\\": \\\"Key resources identified; limitations in publicly available measured standard spectra documented.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 lists NIST SRMs (470 K411/K412, 479, 481, 482, 1871-1875). They used MgO for Mg, Al2O3 for Al, SiO2 for Si at 5 keV. The paper lists SPI (West Chester, PA) for minerals, Geller Microanalytical Laboratory (Topsfield, MA) for stoichiometric compounds, Alfa Aesar for reagent compounds. Newbury & Ritchie 2015 describes use of MgO, KCl, FeS2, GaP, CaF2 as compound standards. Additional supplier information (Astimex, MAC, Ted Pella) from expert knowledge.\",\n      \"evaluation\": \"Concrete supplier names and standards identified with sufficient detail from the literature.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \u00b15% RDEV, 82% within \u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\",\n      \"evaluation\": \"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_012fetPhMSnahqoMA7t6K9o1",
+                "info": {
+                  "start_ts": 5135.110758985,
+                  "end_ts": 5135.113155531
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 lists NIST SRMs (470 K411/K412, 479, 481, 482, 1871-1875). They used MgO for Mg, Al2O3 for Al, SiO2 for Si at 5 keV. The paper lists SPI (West Chester, PA) for minerals, Geller Microanalytical Laboratory (Topsfield, MA) for stoichiometric compounds, Alfa Aesar for reagent compounds. Newbury & Ritchie 2015 describes use of MgO, KCl, FeS2, GaP, CaF2 as compound standards. Additional supplier information (Astimex, MAC, Ted Pella) from expert knowledge.\",\n      \"evaluation\": \"Concrete supplier names and standards identified with sufficient detail from the literature.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"completed\",\n      \"result\": \"NIST DTSA-II includes a built-in standards database. The ISO 22029 EMSA/MAS format is the standard format. No large publicly downloadable measured EDS standards library was identified in the literature beyond the DTSA-II internal database. The de-ma.ch web database (Allaz 2024) and Zenodo deposits exist but were not obtainable for detailed review. Remote standards approach described by Newbury & Ritchie.\",\n      \"evaluation\": \"Key resources identified; limitations in publicly available measured standard spectra documented.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \u00b15% RDEV, 82% within \u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\",\n      \"evaluation\": \"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_013xnvkza6w1rdE9aM8kNgtr",
+                "info": {
+                  "start_ts": 5135.113222685,
+                  "end_ts": 5135.113772505
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me create a summary artifact and then compose the final answer:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01ALNMFNcJzbhppB8hRRwLaV",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"artifact_type\": \"table\", \"description\": \"Create a table summarizing the required metadata for an EDS standard spectrum to be usable in standards-based k-ratio quantification, with columns for: Metadata Parameter, Description/Purpose, and EMSA/MAS Keyword (where applicable). Include: beam energy, probe current, live time, take-off angle, detector window parameters, energy calibration (zero and gain), FWHM at Mn Ka, process time, standard composition and traceability, date, contamination/coating state, detector-to-specimen distance, tilt, azimuth. Note that this information is derived from Goldstein et al. 2018 (Scanning Electron Microscopy and X-ray Microanalysis, 4th ed.), the EMSA/MAS spectrum file format (ISO 22029), and Newbury & Ritchie 2015.\"}",
+                      "name": "create_artifact"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "### Artifact (ID artifact-00)\n\n| Metadata Parameter | Description/Purpose | EMSA/MAS Keyword (where applicable) |\n|---|---|---|\n| Beam energy / accelerating voltage | Required because k-ratios are valid only when unknown and standard are measured under the same excitation conditions; changes ionization cross-sections, overvoltage, depth of generation, and matrix corrections. (pqac-00000000, pqac-00000002, pqac-00000005, pqac-00000022) | `#BEAMKV` |\n| Probe current | Needed to document electron dose and to verify reproducibility/linearity of X-ray intensity; rigorous k-ratio work should measure current with a Faraday cup/picoammeter. (pqac-00000000, pqac-00000013, pqac-00000035, pqac-00000046) | `#PROBECUR` |\n| Live time | Dose in EDS is probe current \u00d7 live time; live time, not real time, determines effective dose because dead time removes useful counts. (pqac-00000000, pqac-00000013, pqac-00000025, pqac-00000035) | `#LIVETIME` |\n| Real time / dead time | Important to assess pulse pile-up/coincidence and detector operating regime; Newbury & Ritchie recommend conservative operation around ~10% dead time for standards-based work, especially when weak peaks sit near coincidence/tail artifacts. (pqac-00000006, pqac-00000013, pqac-00000035, pqac-00000046) | `#REALTIME`, `#DEADTIME` |\n| Detector elevation / take-off angle | Required geometric parameter for absorption correction; should match between unknown and standard and be verified physically if necessary. (pqac-00000000, pqac-00000002, pqac-00000013, pqac-00000026) | often `#ELEVANGLE` or vendor-specific |\n| Detector azimuth angle | Needed because detector orientation changes X-ray path length and effective efficiency; should be fixed and recorded for reusable standards. (pqac-00000000, pqac-00000013) | often vendor-specific / not always standardized |\n| Specimen tilt | Changes take-off geometry and absorption; Goldstein/Newbury specify tilt should be controlled, preferably zero for bulk standards unless intentionally used. (pqac-00000000, pqac-00000013, pqac-00000022) | often `#XTILTSTGE`, `#YTILTSTGE` or vendor-specific |\n| Detector-to-specimen distance / working distance | Sets solid angle and count rate; must be reproducible between standard and unknown. Off-axis position also changes apparent low-energy efficiency because of window-grid/trap shadowing. (pqac-00000000, pqac-00000002, pqac-00000027) | often `#WORKING`, `#DISTANCE` or vendor-specific |\n| Detector active area / solid angle | Needed to interpret count rate and portability of archived spectra; different detector geometries change throughput and sensitivity. (pqac-00000000, pqac-00000002, pqac-00000015) | usually not in classic MSA core keywords; vendor-specific |\n| Detector window type and thickness | Critical below ~2 keV because polymer/SiN vs Be windows transmit low-energy X-rays very differently; affects Mg K, Al K, O K, etc. (pqac-00000009, pqac-00000010, pqac-00000019, pqac-00000027) | usually vendor-specific / not a required classic MSA keyword |\n| Window support grid / electron trap details | Off-axis shadowing and low-energy attenuation can change intensity and background, especially for light elements. (pqac-00000027) | vendor-specific |\n| Detector dead layer / front contact / Si absorption characteristics | Needed when comparing detectors or simulating spectra because fluorescence in dead layer, escape peaks, and efficiency roll-off alter low-energy response. (pqac-00000009, pqac-00000011) | vendor-specific |\n| Detector response function / incomplete charge collection behavior | Essential for fitting trace peaks under tails; low-energy tailing and peak-shape differences are detector-specific and limit transferability of standard spectra. (pqac-00000009, pqac-00000012, pqac-00000037) | not represented in classic MSA keyword set |\n| Energy calibration zero offset | Required so standard and unknown spectra align channel-for-channel for integrated-peak k-ratios and peak fitting. (pqac-00000022, pqac-00000035) | `#OFFSET` |\n| Energy calibration gain / channel width | Required to define energy-per-channel; Goldstein recommends fixed channel width (e.g., 5 eV/channel) and consistent calibration. (pqac-00000022, pqac-00000035) | `#XPERCHAN`, sometimes paired with `#OFFSET` |\n| Number of channels / energy range | Needed to reconstruct spectrum and assure same fitting range; spectra should span low-energy region through the Duane\u2013Hunt limit. (pqac-00000022, pqac-00000035) | `#NPOINTS`, `#XUNITS` |\n| Energy resolution / FWHM at Mn K\u03b1 | Peak overlap sensitivity depends on detector resolution; should be documented because different FWHM values change deconvolution and low-energy tail contributions. (pqac-00000026, pqac-00000010, pqac-00000011) | often `#MNFWHM` or vendor-specific |\n| Process time / shaping time / time constant | Must be fixed; adaptive process time is specifically discouraged for standards-based quantification because it changes peak shape and resolution. (pqac-00000000, pqac-00000013, pqac-00000026) | often `#TIMECNST` or vendor-specific |\n| Count total / integrated counts | High-count spectra are needed for robust MLLS fitting and trace-level overlap correction; archive the total counts or dose associated with the standard. (pqac-00000006, pqac-00000007, pqac-00000017) | `#DATATYPE` with counts array; total counts often derived or vendor-specific |\n| Standard identity | The material used as the standard must be named explicitly so composition, homogeneity, and suitability can be checked. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | `#SAMPLE` |\n| Standard composition | Required because k-ratio denominator must correspond to a known concentration in the standard. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | no single core keyword; usually comment/header text |\n| Certification / traceability | For rigorous work, the standard composition should be certified or independently established and microscopically homogeneous. (pqac-00000002, pqac-00000003, pqac-00000042) | usually comment/header text |\n| Date/time of acquisition | Needed for traceability, detector stability checks, and QA of archived reusable standards. (pqac-00000000, pqac-00000013) | `#DATE`, `#TIME` |\n| Operator / instrument identifier | Supports QA and cross-checking of archived standards; important when spectra are reused. (pqac-00000013) | `#OWNER`, `#TITLE`, vendor-specific instrument fields |\n| Specimen surface preparation state | Surface roughness/topography directly affects low-energy X-rays; for photons below ~1 keV surfaces should be extremely flat, and standards/unknowns should be prepared similarly. (pqac-00000002, pqac-00000007, pqac-00000022) | usually comment/header text |\n| Coating material and thickness | Carbon or metal coatings absorb low-energy X-rays; mismatch between standard and unknown coatings can cause significant error at low kV. (pqac-00000004, pqac-00000007, pqac-00000034) | usually comment/header text |\n| Contamination / oxidation / tarnish state | Surface films create composite specimens and strongly bias low-energy analysis; should be documented, especially for reactive standards like Mg-bearing materials. (pqac-00000003, pqac-00000018, pqac-00000034) | usually comment/header text |\n| Vacuum / chamber conditions | Useful for assessing contamination growth and detector performance stability during acquisition. (pqac-00000018, pqac-00000034) | vendor-specific |\n| Peak-family / line selection used for quantification | EDS often quantifies whole line families rather than a single line; the selected family must be known to interpret k-ratios and matrix corrections. (pqac-00000005, pqac-00000016, pqac-00000024) | usually analysis metadata, not core MSA |\n| Background/fit model or peak-shape reference linkage | Particularly valuable for trace-overlap cases, because usability of a stored standard also depends on the associated peak-shape references and fitting strategy. (pqac-00000016, pqac-00000017, pqac-00000023) | not in classic MSA core; DTSA-II/project metadata |\n| QA status / same-conditions verification | Archived standards are reusable only if a QA protocol confirms the unknown was measured under the same beam energy, dose, and EDS parameters. (pqac-00000000, pqac-00000013) | not a classic MSA keyword; external QA record |\n\n\n*Table: This table summarizes the metadata that must accompany an EDS standard spectrum for rigorous standards-based k-ratio quantification. It combines the practical requirements emphasized by Goldstein/Newbury/Ritchie with the fields typically represented in the EMSA/MAS .msa format and notes where classic MSA keywords are incomplete for modern detector-response details.*\n\nArtifact IDs that may be injected into the answer: [artifact-00]\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=47 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "create_artifact",
+                "tool_call_id": "toolu_01ALNMFNcJzbhppB8hRRwLaV",
+                "info": {
+                  "start_ts": 5182.036432442,
+                  "end_ts": 5211.214982695
+                }
+              },
+              {
+                "role": "assistant",
+                "content": null,
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_013Dk6gnt6nGCbaXL2Vrg2Ub",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"artifact_type\": \"table\", \"description\": \"Create a table of physical standards suppliers and certified reference materials relevant to Al, Si, and Mg for electron probe microanalysis / SEM-EDS. Include columns for: Supplier/Source, Product/CRM, Catalogue/SRM Number, Elements/Composition, and Notes. Include:\\n- NIST SRM 470 (K411 glass: O-Mg-Si-Ca-Fe; K412 glass: O-Mg-Al-Si-Ca-Fe)\\n- NIST SRM 481 (Au-Ag alloys)\\n- NIST SRM 482 (Au-Cu alloys)  \\n- NIST SRM 479 (Fe-Cr-Ni stainless steel)\\n- NIST SRM 483 (Fe-3Si transformer steel)\\n- NIST SRM 2063a (thin film)\\n- NIST SRM 1871-1875 (K-glass series)\\n- Geller MicroAnalytical Laboratory (Topsfield, MA) for stoichiometric binary compounds like MgO, Al2O3, SiO2\\n- SPI Supplies (West Chester, PA) for minerals (periclase, forsterite, dolomite, spinel, etc.)\\n- Astimex Standards Ltd (Toronto, Canada) for pure element and compound standard mounts\\n- Ted Pella Inc for microanalysis standards\\n- Micro-Analysis Consultants (MAC) (St Ives, UK) for mineral and synthetic standards\\n- P&H Developments for standards\\n- Alfa Aesar for reagent-grade compounds\\n- MgO as the recommended compound standard for Mg\\n- Note about pure Mg metal oxidation problem\\n- Smithsonian microbeam standards collection for minerals\\nFrom the Newbury & Ritchie 2024 paper data.\"}",
+                      "name": "create_artifact"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "### Artifact (ID artifact-01)\n\n| Supplier/Source | Product/CRM | Catalogue/SRM Number | Elements/Composition | Notes |\n|---|---|---|---|---|\n| NIST | Glass for microanalysis, K411 | SRM 470 K411 | O-Mg-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; useful as a multi-element glass containing Mg and Si. (pqac-00000031, pqac-00000042) |\n| NIST | Glass for microanalysis, K412 | SRM 470 K412 | O-Mg-Al-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; directly relevant to Al-Mg-Si calibration and overlap studies. (pqac-00000031, pqac-00000042) |\n| NIST | Gold-silver alloy set | SRM 481 | Au-Ag alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study as a certified alloy series suitable for microanalysis challenge specimens and standards work. (pqac-00000031, pqac-00000042) |\n| NIST | Gold-copper alloy set | SRM 482 | Au-Cu alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study; Newbury & Ritchie also discuss spectra of SRM 482 at multiple beam energies. (pqac-00000031, pqac-00000034, pqac-00000042) |\n| NIST | Stainless steel CRM | SRM 479 | Fe-Cr-Ni stainless steel | Explicitly listed in the 5 kV study among NIST microanalysis challenge materials. (pqac-00000031, pqac-00000042) |\n| NIST | Transformer steel CRM | SRM 483 | Fe-3Si steel | Mentioned by Newbury & Ritchie 2019 as an EPMA/EDS reference material in quantitative work. (pqac-00000039) |\n| NIST | Thin-film microanalysis SRM | SRM 2063a | Thin film; composition not verified here | Relevant NIST microanalysis SRM class, but exact composition/details were not verified in the retrieved sources; include only after checking the current NIST certificate. |\n| NIST | K-glass / oxide glass series | SRM 1871, 1872, 1873, 1875 | SRM 1871 K456: O-Si-Pb; SRM 1872 K453: O-Ge-Pb; SRM 1873 K458: O-Si-Zn-Ba; SRM 1875 K496: O-Mg-Al-P | Explicitly listed in the 5 kV study as microanalysis-qualified SRMs. SRM 1875 is especially relevant because it contains Mg and Al. (pqac-00000031, pqac-00000042) |\n| Geller MicroAnalytical Laboratory (Topsfield, MA, USA) | Stoichiometric binary compounds prepared for microanalysis | Vendor product line; specific catalogue IDs not verified here | MgO, Al2O3, SiO2, TiN, TiO2, Cr2N, etc. | Explicitly named by Newbury & Ritchie 2024 as a source of stoichiometric compounds with surfaces prepared for microanalysis. Recommended route for MgO, Al2O3, SiO2 standards. (pqac-00000031, pqac-00000040) |\n| SPI Supplies (West Chester, PA, USA) | Mineral standards / well-characterized minerals | Vendor product line; specific catalogue IDs not verified here | Minerals such as calcite, dolomite, fluorapatite, wollastonite, zircon; user-requested examples periclase/forsterite/spinel should be checked in current catalog | Explicitly named by Newbury & Ritchie 2024 as a source of minerals of known composition and micro-homogeneity used in the challenge set. (pqac-00000031, pqac-00000042) |\n| Astimex Standards Ltd (Toronto, Canada) | Mounted pure-element and compound microanalysis standards | Vendor product line; specific catalogue IDs not verified here | Pure Al, Si, alloys, oxides, silicates, custom mounts | Common EPMA/SEM-EDS supplier, but specific products were not verified in the retrieved literature; check current catalog for Al, Si, Mg-bearing mounts before purchase. |\n| Ted Pella, Inc. | Microanalysis standards and mounts | Vendor product line; specific catalogue IDs not verified here | Pure elements, compounds, calibration mounts | Widely used supplier, but no product-specific verification in retrieved sources; confirm current catalog details. |\n| Micro-Analysis Consultants (MAC), St Ives, UK | Mineral and synthetic EPMA standards | Vendor product line; specific catalogue IDs not verified here | Silicates, oxides, sulfides, synthetic compounds | Common EPMA standards source, but exact catalog entries were not verified in retrieved sources. |\n| P&H Developments | Electron microprobe standards | Vendor product line; specific catalogue IDs not verified here | Mineral and synthetic standards | Named by user request; no product-specific verification found in retrieved sources, so verify directly with supplier. |\n| Alfa Aesar (now Thermo Fisher chemicals) | Reagent compounds | Reagent-grade products; specific catalogue IDs not verified here | BaTiO3, PbS, MoS2 and other compounds | Explicitly named by Newbury & Ritchie 2024 as source of reagent compounds used as challenge specimens; reagent grade is not automatically a microanalysis standard, so homogeneity/prep must be checked. (pqac-00000031, pqac-00000040) |\n| Smithsonian microbeam standards collection | Mineral reference materials | Collection-level resource; no single catalogue number | Mineral standards, including Mg-bearing silicates/carbonates depending on collection | Valuable institutional standards resource, but not documented in the retrieved contexts; verify access and material list directly with Smithsonian microbeam facility. |\n| Recommended Mg standard chemistry | MgO (periclase chemistry) | Not a single catalog number | Mg and O | Newbury & Ritchie\u2019s 5 kV study repeatedly used MgO as the Mg standard; their standards table maps Mg to MgO at 5 kV. This is the best-supported Mg standard in the retrieved sources. (pqac-00000040, pqac-00000041, pqac-00000043) |\n| Recommended Al standard chemistry | Al2O3 | Not a single catalog number | Al and O | In the 5 kV study, Al was standardized with Al2O3 in the standards table; practical if oxide standards are already in the block. (pqac-00000040, pqac-00000041) |\n| Recommended Si standard chemistry | SiO2 or pure Si | Not a single catalog number | Si and O, or Si | The 5 kV study shows SiO2 used as a Si standard in multiple entries; Newbury & Ritchie also note that pure Si can be used among pure-element standards. (pqac-00000040, pqac-00000041, pqac-00000043) |\n| Caution on pure Mg metal | Pure Mg metal | Not recommended as first-choice standard for routine low-kV SEM-EDS | Mg metal, rapidly oxidizing surface | Not directly evaluated in the retrieved papers, but the literature retrieved strongly supports substitution with MgO; this is consistent with the practical oxidation/contamination problem for Mg metal and the repeated use of stoichiometric compounds when pure elements are unstable. (pqac-00000003, pqac-00000005, pqac-00000043) |\n\n\n*Table: This table summarizes physical standards sources and certified reference materials relevant to Al, Si, and Mg SEM-EDS/EPMA work, emphasizing items explicitly documented in the Newbury & Ritchie 2024 5 kV study. It distinguishes directly verified standards from commonly used suppliers whose current catalogue details should still be checked before procurement.*\n\nArtifact IDs that may be injected into the answer: [artifact-00, artifact-01]\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=47 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "create_artifact",
+                "tool_call_id": "toolu_013Dk6gnt6nGCbaXL2Vrg2Ub",
+                "info": {
+                  "start_ts": 5264.997456878,
+                  "end_ts": 5283.989548657
+                }
+              },
+              {
+                "role": "assistant",
+                "content": null,
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01AtT5WP7fdQH8qk1W2dWvxH",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 7, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 7,\\n  \\\"objective\\\": \\\"Create summary artifacts and submit final answer\\\",\\n  \\\"rationale\\\": \\\"Compile all findings into a comprehensive, well-cited answer\\\",\\n  \\\"status\\\": \\\"in-progress\\\",\\n  \\\"result\\\": null,\\n  \\\"evaluation\\\": null\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              }
+            ],
+            "hide_old_env_states": false,
+            "hide_old_action_content": false,
+            "sliding_window": null
+          },
+          "next_agent_state": {
+            "tools": [
+              {
+                "type": "function",
+                "info": {
+                  "name": "read_text",
+                  "description": "Given a list of text names, read their contents.\n\nThis tool is valuable to read the full contents of specific parts of documents,\ncomplementing the `gather_evidence` tool's indirect approach.\nThis can be an especially useful tool if `gather_evidence` does not find evidence,\nbut you think it is very likely that specific documents are still relevant to the question.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "text_name_list": {
+                        "description": "A list of up to 10 text names to read.\nThese text names can be any valid text names retrieved by other tools.",
+                        "items": {
+                          "type": "string"
+                        },
+                        "title": "Text Name List",
+                        "type": "array"
+                      }
+                    },
+                    "required": [
+                      "text_name_list"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "clinical_trials_search",
+                  "description": "Search for clinical trials, with support for repeated calls and concurrent execution.\n\nWill add new clinical trials to the state, and return metadata about the number of trials found.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "The search query string. Supports complex boolean expressions, field-specific\nsearches, and query modifiers through operators. All configuration is done through\noperators in the query string.\nQuery Syntax:\n    Basic Search:\n        Simple text automatically uses default EXPANSION[Relaxation] and COVERAGE[Contains]\n        >>> \"heart attack\"\n\n    Modified Search:\n        Use operators to modify search behavior:\n        >>> 'EXPANSION[None]COVERAGE[FullMatch]\"exact phrase\"'\n        >>> 'EXPANSION[Concept]heart attack'\n\n    Field Search:\n        Specify fields using AREA operator:\n        >>> 'AREA[InterventionName]aspirin'\n        >>> 'AREA[Phase]PHASE3'\n\n    Location Search:\n        Use SEARCH operator for compound location queries:\n        >>> 'cancer AND SEARCH[Location](AREA[LocationCity]Boston AND AREA[LocationState]Massachusetts)'\n\n    Complex Boolean:\n        Combine terms with AND, OR, NOT and parentheses:\n        >>> '(cancer OR tumor) AND NOT (EXPANSION[None]pediatric OR AREA[StdAge]CHILD)'\n\n    Date Ranges:\n        Use RANGE to specify date ranges with formats like \"yyyy-MM\" or \"yyyy-MM-dd\".\n        Note that MIN and MAX can be used for open-ended ranges:\n        >>> AREA[ResultsFirstPostDate]RANGE[2015-01-01, MAX]\n\nOperators:\n    EXPANSION[type]: Controls term expansion\n        - None: Exact match only, case and accent sensitive\n        - Term: Includes lexical variants (plurals, spellings)\n        - Concept: Includes UMLS synonyms\n        - Relaxation: Relaxes adjacency requirements (default)\n        - Lossy: Allows missing partial terms\n\n    COVERAGE[type]: Controls text matching\n        - FullMatch: Must match entire field\n        - StartsWith: Must match beginning of field\n        - EndsWith: Must match end of field\n        - Contains: Must match part of field (default)\n\n    AREA[field]: Specifies field to search\n        - See Field Reference for available fields\n\n    SEARCH[type]: Groups field searches\n        - Location: Groups location-related fields\n        - Study: Groups study-related fields\n\nUsage Notes:\n    - All search expressions are implicitly OR expressions\n    - Operator precedence (highest to lowest): terms/source operators, NOT/context operators, AND, OR\n    - Use quotes for exact phrase matching: \"heart attack\"\n    - Use parentheses for grouping: (heart OR cardiac) AND attack\n    - Use backslash to escape operators: \\AND\n    - Default expansion is EXPANSION[Relaxation]\n    - Default coverage is COVERAGE[Contains]\n\nField Reference:\n    High Priority Fields (weight >= 0.8):\n        - NCTId (1.0): Trial identifier\n        - Acronym (1.0): Study acronym\n        - BriefTitle (0.89): Short title\n        - OfficialTitle (0.85): Full official title\n        - Condition (0.81): Medical condition\n        - InterventionName (0.8): Primary intervention name\n        - OverallStatus: Trial status\n\n    Medium Priority Fields (0.5-0.79):\n        - InterventionOtherName (0.75): Alternative intervention names\n        - Phase (0.65): Trial phase\n        - StdAge (0.65): Standard age groups\n        - Keyword (0.6): Study keywords\n        - BriefSummary (0.6): Short description\n        - SecondaryOutcomeMeasure (0.5): Secondary outcomes\n\n    Low Priority Fields (< 0.5):\n        - DesignPrimaryPurpose (0.3): Primary purpose of study\n        - StudyType (0.3)\n        - Various descriptive, location, and administrative fields\n\nSupported Enums:\n    Phase:\n        - EARLY_PHASE1: Early Phase 1\n        - PHASE1: Phase 1\n        - PHASE2: Phase 2\n        - PHASE3: Phase 3\n        - PHASE4: Phase 4\n        - NA: Not Applicable\n\n    StandardAge:\n        - CHILD: Child\n        - ADULT: Adult\n        - OLDER_ADULT: Older Adult\n\n    Status:\n        - RECRUITING: Currently recruiting participants\n        - ACTIVE_NOT_RECRUITING: Active but not recruiting\n        - COMPLETED: Study completed\n        - ENROLLING_BY_INVITATION: Enrolling by invitation only\n        - NOT_YET_RECRUITING: Not yet recruiting\n        - SUSPENDED: Study suspended\n        - TERMINATED: Study terminated\n        - WITHDRAWN: Study withdrawn\n        - AVAILABLE: Available\n        - NO_LONGER_AVAILABLE: No longer available\n        - TEMPORARILY_NOT_AVAILABLE: Temporarily not available\n        - APPROVED_FOR_MARKETING: Approved for marketing\n        - WITHHELD: Withheld\n        - UNKNOWN: Unknown status\n\n    StudyType:\n        - INTERVENTIONAL: Interventional studies\n        - OBSERVATIONAL: Observational studies\n        - EXPANDED_ACCESS: Expanded access studies\n\n    PrimaryPurpose:\n        - TREATMENT: Treatment\n        - PREVENTION: Prevention\n        - DIAGNOSTIC: Diagnostic\n        - ECT: Educational/Counseling/Training\n        - SUPPORTIVE_CARE: Supportive Care\n        - SCREENING: Screening\n        - HEALTH_SERVICES_RESEARCH: Health Services Research\n        - BASIC_SCIENCE: Basic Science\n        - DEVICE_FEASIBILITY: Device Feasibility\n        - OTHER: Other\n\n    InterventionType:\n        - BEHAVIORAL: Behavioral interventions\n        - BIOLOGICAL: Biological interventions\n        - COMBINATION_PRODUCT: Combination product interventions\n        - DEVICE: Device interventions\n        - DIAGNOSTIC_TEST: Diagnostic test interventions\n        - DIETARY_SUPPLEMENT: Dietary supplement interventions\n        - DRUG: Drug interventions\n        - GENETIC: Genetic interventions\n        - PROCEDURE: Procedure interventions\n        - RADIATION: Radiation interventions\n        - OTHER: Other interventions\n\n    DesignAllocation:\n        - RANDOMIZED: Randomized allocation\n        - NON_RANDOMIZED: Non-randomized allocation\n        - NA: Not applicable\n\n    InterventionalAssignment:\n        - SINGLE_GROUP: Single group assignment\n        - PARALLEL: Parallel assignment\n        - CROSSOVER: Crossover assignment\n        - FACTORIAL: Factorial assignment\n        - SEQUENTIAL: Sequential assignment\n\n    ObservationalModel:\n        - COHORT: Cohort\n        - CASE_CONTROL: Case-Control\n        - CASE_ONLY: Case-Only\n        - CASE_CROSSOVER: Case-Crossover\n        - ECOLOGIC_OR_COMMUNITY: Ecologic or Community\n        - FAMILY_BASED: Family-Based\n        - DEFINED_POPULATION: Defined Population\n        - NATURAL_HISTORY: Natural History\n        - OTHER: Other\n\n    DesignMasking:\n        - NONE: None (Open Label)\n        - SINGLE: Single\n        - DOUBLE: Double\n        - TRIPLE: Triple\n        - QUADRUPLE: Quadruple\n\n    WhoMasked:\n        - PARTICIPANT: Participant\n        - CARE_PROVIDER: Care Provider\n        - INVESTIGATOR: Investigator\n        - OUTCOMES_ASSESSOR: Outcomes Assessor",
+                        "title": "Query",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "create_plan",
+                  "description": "Create a plan for to construct a thorough and accurate answer.\n\nDecompose the input task into a set of sub-objectives that need to\nbe met in order to form the answer. Subsequently, when working on solving\nthe query, you can focus on these objectives one by one. Note that the\n`update_plan` tool allows you to change the objectives if needed.\n\nIn addition to the objectives you deem necessary, add one final objective\nto call the `answer` tool with your final answer, so that you do not\nforget to submit your answer.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "plan_json": {
+                        "description": "A JSON string representing the plan. It should be a dictionary\nwith top-level key \"objectives\", whose value is a list of objectives.\nEach objective should be a dictionary with the following keys:\n- \"id\": (int) an integer id for the plan objective\n- \"objective\": (str) a human readable description of the objective's goal\n- \"rationale\": (str) a human readable rationale\n    describing why this objective is necessary and appropriate for the query.\n- \"status\": (str) updated task status, default to pending,\n    one of: pending, in-progress, or completed.\n    \"pending\" is yet to be started,\n    \"in-progress\" is the current objective being solved,\n    \"completed\" is successfully completed with acceptance criteria met.\n- \"result\": (str|None) The result of the objective, default to None.\n- \"evaluation\": (str|None) Description of why the objective result\n    meets the criteria for being complete. Default to None.",
+                        "title": "Plan Json",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "plan_json"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "view_images",
+                  "description": "Retrieve images from a document.\n\nUse this tool when you need to see figures, tables, or other visual content.\nThe tool works by asking a weaker LLM agent to scan through the document, looking for\nvisual content matching the query you provide. When the agent finds matches, it will\ncrop the page to the relevant region. It can be tasked to return multiple images,\nif desired. Note that the weaker LLM may be worse at *understanding* images than\nyou, so double-check its conclusions about the returned images. It is also stateless,\ni.e. it will not remember what you have asked it to find in the past.\n\nUse this tool carefully. It is difficult to retrieve images, and the images\nthemselves will fill up your context window quickly. Here are some guidelines:\n1. ALWAYS use this tool if the question explicitly mentions 'Table X' or 'Figure Y'.\n   These questions require visual content and cannot be answered with text alone.\n2. Use this tool as a fallback when gather_evidence fails repeatedly (2+ times\n   returning 'No relevant evidence'). This suggests the answer may be in visual content.\n3. When gather_evidence returns text mentioning 'see Figure X' or 'shown in Table Y',\n   you should call this tool to examine that specific visual reference.\n4. Only call this tool after directly inspecting relevant text with read_text\n   to confirm the document likely contains the visual you need.\n5. Don't use this tool in a broad-spectrum way (don't call on many documents\n   just to see what might be relevant).\n6. Never call this tool in parallel with itself.\n7. Users like visual evidence, so call this tool at least once before answering so you\n   can provide some image citations in the answer. Add this to your plan so you do not forget.\n   For images to be presented to the user, they must be cited in the final answer after retrieval\n   by this tool. You may ignore this instruction if the request is for the question is asking\n   for a specific piece of information and is not an open-ended research question.\n8. NEVER cite full-page images in your final answer, unless they are full-page panels figures or\n   tables. Cite relevant cropped regions if available, otherwise consider calling this tool again\n   to find a smaller region that answers the query.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "Query to search for visual content in the document. If you know the specific\nfigure/table/formula you are looking for, you can specify it here (e.g. \"find me\nFigure 3\" or \"extract the table on page 10\"). You can also request based on content\n(e.g. \"find me all volcano plots of gene X\" or \"I need the formula for the growth rate\").\nYou can even include explicit instructions for the LLM agent to follow (if helpful, not\nnecessarily required). The more specific and clear your query is here, the higher the\nchance of success.",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "text_name": {
+                        "description": "Name of a text chunk (e.g., 'smith2023example pages 1-5').",
+                        "title": "Text Name",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "query",
+                      "text_name"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "update_plan",
+                  "description": "Update the plan for a specific or new objective using a JSON string to create or\nreplace the existing objective.\n\nThe updated_json should be a JSON string representing a single plan objective object.\n\nYou may use this tool to update an objective, create a new one, or change\nstrategy if the current plan is not working. Only change strategy significantly\nas a last resort, after trying very hard to make the current plan work.\n\nOnly mark an objective as completed if you are absolutely sure that it has been fully\nmet. If it is only partially met, you may add additional objectives to the plan for\nwhat is missing.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "plan_objective_id": {
+                        "description": "The id of the objective to update.",
+                        "title": "Plan Objective Id",
+                        "type": "integer"
+                      },
+                      "updated_plan_objective_json": {
+                        "description": "A JSON string representing the updated objective.\nIt should be a dictionary with the with the following keys:\n- \"id\": (int) an integer id matching plan_objective_id, if not found, a new objective is created.\n- \"objective\": (str) a human readable description of the objective's goal\n- \"rationale\": (str) a human readable rationale\n    describing why this objective is necessary and appropriate for the query.\n- \"status\": (str) updated task status, default to pending,\n    one of: pending, in-progress, or completed.\n    \"pending\" is yet to be started,\n    \"in-progress\" is the current objective being solved,\n    \"completed\" is successfully completed with acceptance criteria met.\n- \"result\": (str|None) The result of the objective, default to None.\n- \"evaluation\": (str|None) Description of why the objective result\n    meets the criteria for being complete. Default to None.",
+                        "title": "Updated Plan Objective Json",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "plan_objective_id",
+                      "updated_plan_objective_json"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "create_artifact",
+                  "description": "Create an artifact that can be used in the final answer, based on information\nyou have collected so far.\n\nHow it works: the full message history thus far is passed to another LLM,\nalong with the question and your description. The LLM is tasked to create\nan artifact that matches your specifications, including a title, caption,\nand markdown content. You drive the process by specifying the type and\ndescribing what you want.\n\nOnly use this tool *after* you have gathered sufficient evidence or\ninformation to create a new artifact. Do not call this tool in parallel\nwith tools that are searching for information or evidence that would be\nnecessary to create this artifact.\n\nIt is very helpful after calls to several search tools,\nafter calls to the `gather_evidence` tool, but it is not required.\nHowever, it should be called before the `answer` tool at\nleast one time, but more may be given if specifically helpful for\nthe task, so that the `answer` tool can use the artifacts for the answer.\n\nAn artifact can be any string representable fact or list of facts,\nformatted using markdown syntax. The artifact will be generated as one of\nthe following types:\n- table: Markdown tables with rows and columns (e.g., findings, methods, molecules)\n- code_block: Code snippets in fenced code blocks\n- blockquote: Quoted text or important facts (using > prefix)\n- image: AI-generated image (chart, diagram, or visualization)\n\nEach artifact consists of:\n- A short title (3-8 words) that names what the artifact contains\n- A caption (1-2 sentences) describing what the artifact shows and why it's useful\n- Markdown content in a single element type (validated automatically with retries if needed)\n  For image type, content is a markdown image embed ``![title](data:image/png;base64,...)``,\n  embedding the PNG directly as a base64 data URL.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "artifact_type": {
+                        "description": "Artifact type to create. Must be one of: table,\ncode_block, blockquote, image.",
+                        "title": "Artifact Type",
+                        "type": "string"
+                      },
+                      "description": {
+                        "description": "Description of what you want in the artifact. Be specific\nabout what information should be included, how it should be organized,\nand what columns/sections/content you want. This guides the summary LLM.\nFor image type, describe the visual you want generated in detail.",
+                        "title": "Description",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "artifact_type",
+                      "description"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "paper_search",
+                  "description": "Search for papers in Google Scholar for you to look at.\n\nCan be called repeatedly with identical parameters to retrieve more results (max 2 repeats).\nA short summary of the retrieved papers will be returned, but to examine the full content of each paper,\nyou must use the gather_evidence tool.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "A Google Scholar search query, which can be a specific phrase, complete sentence,\nor general keywords, e.g. 'machine learning for immunology'. Also can be\ngiven search operators like 'author:'.",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "min_year": {
+                        "anyOf": [
+                          {
+                            "type": "integer"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "filter for minimum publication year.\nThe current year is 2026. If unsure about time range, do not set.",
+                        "title": "Min Year"
+                      },
+                      "max_year": {
+                        "anyOf": [
+                          {
+                            "type": "integer"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "filter for maximum publication year.\nThe current year is 2026. If unsure about time range, do not set.",
+                        "title": "Max Year"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "patent_search",
+                  "description": "Search for patents to increase the patent count.\n\nRepeat previous calls with the same query to continue a search.\nOnly repeat a maximum of three times.\nThis tool can be called concurrently.\nThis tool introduces novel patents, so invoke it when just beginning\nor when unsatisfied with the current evidence.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "A search query for patents (using Google Patents). Never include temporal\nfilters here (e.g. specific years or dates); instead use the `after` and `before`\narguments. Never include author filters here; instead use the `inventor` argument.\nSupports the following syntax, but they can be brittle and are not preferred; try\nsimple queries where possible:\n- Boolean operators: AND (default), OR, and - (NOT)\n- Exact phrases: \"quoted text\"\n- Proximity: NEAR/x, ADJ/x (ordered), WITH (20 words), SAME (200 words)\n- Field search: TI=(title), AB=(abstract), CL=(claims)\n- CPC codes: cpc:A01B or CPC=B60R22/low (includes children)\n- Wildcards: ? (0-1 char), * (0+ chars), # (exactly 1 char)\n- Chemistry: exact molecule names, SSS=molecule (substructure),\n  ~molecule (similar), SMILES strings, SMARTS=pattern, InChI keys,\n  CL=~molecule (chemistry in claims)",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "after": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Minimum patent date. Format: YYYYMMDD.\nExample: '20150101' for patents after Jan 1, 2015.",
+                        "title": "After"
+                      },
+                      "before": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Maximum patent date. Format: YYYYMMDD.\nExample: '20200101' for patents before Jan 1, 2020.",
+                        "title": "Before"
+                      },
+                      "date_type": {
+                        "default": "publication",
+                        "description": "Type of date that after and before refer to. Must be either 'publication'\nor 'filing'. Only necessary to set if after and/or before are set.",
+                        "title": "Date Type",
+                        "type": "string"
+                      },
+                      "inventor": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Filter by inventor name(s). Comma-separated for multiple.",
+                        "title": "Inventor"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "collect_cited_papers_in_evidence",
+                  "description": "Collect papers by traversing the citations of relevant papers to increase the paper count.\n\nThis tool has no effect if called when paper count or relevant papers are zero.\nThis tool will find papers that are likely to lead to more relevant evidence.\nThe papers found have a higher chance of relevance because this tool starts from relevant evidence.\nThis tool's usefulness increases with the amount of gathered evidence as there's more citations to consider.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {},
+                    "required": []
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "gather_evidence",
+                  "description": "Given a specific question, gather evidence from full-text of documents that have been retrieved by\nprevious tool calls.\n\nHere is how the tool works: the provided question is posed to all texts retrieved thus far\nby other tools. An LLM sees each text independently and is prompted to find information relevant\nto the question.\n\nThat is, we sample evidence `e \\sim LLM(prompt, text, q)` for each text. We only return pieces of\nevidence `e` that are sufficiently relevant to the question; if the text is irrelevant, then `e`\nis not included in the final response of this tool. Note that this LLM does not see the conversation\nhistory thus far, only the question and each text. Note that it only sees text, no images or other\nmedia from the contents (though tables and formulae may be parseable in some cases).\n\nThink of this tool as an efficient way to deeply scan all retrieved documents for evidence. It\nis complementary to the `read_text` tool, which can be used to directly inspect a subset of the\nretrieved documents.\n\nA valuable time to invoke this tool is after another tool finds potentially relevant documents.\nFeel free to invoke this tool in parallel with other tools, but do not call this tool in parallel with itself.\nOnly invoke this tool when the document count is above zero, or this tool will be useless.\n\nIf you call this tool 2+ times and repeatedly get 'No relevant evidence found',\nconsider whether the answer might be in visual content (figures/tables) rather than text,\nand use appropriate tools if available to access that content.\n\nOnce you receive evidence from this tool:\n\n1. Read Carefully: Don't skim. The evidence may contain multiple similar terms\n   or values\u2014make sure you identify the RIGHT one.\n\n2. For Comparative Questions: If the question asks \"which X has greatest Y\",\n   check that the evidence includes information about ALL relevant X options, not\n   just one or two. If you only see partial information, gather more evidence.\n\n3. Check for Noise: Verify that numbers or terms aren't just metadata\n   (page numbers, reference IDs, dates). Look for the value in meaningful\n   scientific context.\n\n4. Context Matters: A term appearing 71 times doesn't mean it's always the answer.\n   Verify which occurrence actually answers the question asked.\n\nIf the evidence doesn't clearly answer the question, gather more evidence before\nconcluding. Don't guess based on partial information.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "question": {
+                        "description": "Specific question to gather evidence for.",
+                        "title": "Question",
+                        "type": "string"
+                      },
+                      "text_name_focus_list": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "if there are known text names that are relevant to the question,\nyou can specify them here. This will ensure that the tool will look at these text names\nfirst, and then look at the rest of the evidence. If left as `None`, an embedding\nsearch will be performed on underlying content to find most relevant texts.",
+                        "title": "Text Name Focus List"
+                      }
+                    },
+                    "required": [
+                      "question"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "open_targets_search",
+                  "description": "Search for disease-target associations from OpenTargets database.\n\nAdds new disease-target association data to the state and returns top search results.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "disease_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of disease names to search for.\nUsage:\ndisease_names = [\"Alzheimer's\"] ->\n    Returns top targets for Alzheimer's\ndisease_names = [\"Alzheimer's\", \"Diabetes\"], target_names = [\"PSEN1\"] ->\n    Filters for only PSEN1-Alzheimer's/Diabetes evidence\ndisease_names = [\"Alzheimer's\"], drug_names = [\"Aducanumab\"] ->\n    Filters for Alzheimer's disease-target pairs treated by Aducanumab",
+                        "title": "Disease Names"
+                      },
+                      "target_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of target names to search for.\nUsage:\ntarget_names = [\"BACE1\"] ->\n    Returns top diseases associated with BACE1\ntarget_names = [\"BACE1\", \"APP\"], disease_names = [\"Alzheimer's\"] ->\n    Filters for only these target-Alzheimer's pairs\ntarget_names = [\"BACE1\"], drug_names = [\"Aducanumab\"] ->\n    Filters for BACE1 disease pairs treated by Aducanumab",
+                        "title": "Target Names"
+                      },
+                      "drug_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of drug names to generate or filter results.\nUsage:\ndrug_names = [\"Aducanumab\"] ->\n    Returns all disease-target pairs treated by Aducanumab\ndrug_names = [\"Aducanumab\"], disease_names = [\"Alzheimer's\"] ->\n    Filters for Alzheimer's pairs treated by Aducanumab\ndrug_names = [\"Aducanumab\"], target_names = [\"BACE1\"] ->\n    Filters for BACE1 disease pairs treated by Aducanumab",
+                        "title": "Drug Names"
+                      }
+                    },
+                    "required": []
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "answer",
+                  "description": "Submit your final answer to the user. You MUST call this tool on your final answer.\nIf you mark all objectives as completed but have not yet called this tool, then\nthe answer will not be submitted. Note that this tool should only be called once, as it\nimmediately terminates the run and submits the answer.\n\nWrite an answer based on the evidence from gather_evidence results in message history.\nIf the context provides insufficient information, provide a partial answer and explain\nwhy it is partial (e.g. the question is currently an open question in the field,\nyou were unable to obtain certain papers, etc.).\n\nFor each part of your answer, indicate which sources most support it via citation IDs at\nthe end of sentences, like (pqac-0000ABCD).\nYou are only allowed to cite available context IDs, indicated in previous messages by \"Context IDs that may be cited:\".\n## Valid citation examples, only use comma/space delimited parentheticals:\n\n- (pqac-0000ABCD, pqac-0000EFGH)\n- (pqac-0000IJKL)\n\n## Invalid citation examples:\n\n- (pqac-0000ABCD and pqac-0000EFGH)\n- (pqac-0000ABCD;pqac-0000EFGH)\n- (pqac-0000ABCD-pqac-0000EFGH)\n- pqac-0000ABCD and pqac-0000EFGH\n- Example's work pqac-0000ABCD\n- (pages pqac-0000ABCD)\n- ![description](pqac-0000ABCD)\n- ()\n\nDo not concatenate citation ids, just use them as-is.\n\nWhen writing your answer, embed artifacts if relevant artifacts have been previously\ncreated by the `create_artifact` tool. To embed an artifact, simply include this in your\nanswer, on its own line and without any additional formatting (i.e. no backticks, code fences,\nquotes, additional tags, etc.).\nAlways provide at least some introductory sentence or paragraph before referring to an artifact,\nso that the artifact is properly contextualized.\nHere is an example reference to an artifact with ID \"artifact-XY\":\n<artifact id=\"artifact-XY\"/>\n\nValid artifact IDs are indicated in previous messages by 'Artifact IDs that may be injected into the answer:'.\n\n\nDouble-check your answer:\n\n1. Evidence Match: Re-read the specific evidence snippets you're citing. Does your\n   answer actually match what they say? Don't rely on memory from 20+ messages ago.\n\n2. For Comparative Questions (\"which X has greatest/maximum/highest Y\"):\n   - Did you examine ALL options mentioned in the evidence?\n   - Did you explicitly compare their values?\n   - Example: If evidence mentions \"Pancreatic: 0.92, Liver: 0.85, Lung: 0.78\",\n     verify you compared all three, not just two.\n\n3. For Specific Value Questions (\"How many\", \"What is the\", specific terms):\n   - Does the exact value you're stating appear in the evidence?\n   - Are you extracting from the right context (not noise like page numbers)?\n\n4. Sanity Check: Read your answer. Does it directly address what was asked?\n\nDon't use Markdown image syntax like ![...](...) to reference media in your answer,\nbecause media get automatically linked by the system based on your answer's citations.\n\nWrite in the style of a scientific article, with concise sentences and\ncoherent paragraphs. This answer will be used directly,\nso do not add any extraneous information.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "answer": {
+                        "description": "valid answer, cited with citation IDs.",
+                        "title": "Answer",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "answer"
+                    ]
+                  }
+                }
+              }
+            ],
+            "messages": [
+              {
+                "role": "user",
+                "content": "Use the tools to answer the question: I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.\n\nStart by making a plan, and update the plan as you go. Your answer will be returned to the user when all plan objectives are completed. Be thorough and ensure your evidence matches the user's question.",
+                "info": null
+              },
+              {
+                "role": "assistant",
+                "content": "\n\nI'll create a comprehensive plan to address this multi-part question about SEM-EDS standards-based quantification.",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_016qD7jWzhrDrjZBuisuwM3M",
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+                    "function": {
+                      "arguments": "{\"plan_json\": \"{\\n  \\\"objectives\\\": [\\n    {\\n      \\\"id\\\": 1,\\n      \\\"objective\\\": \\\"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\\\",\\n      \\\"rationale\\\": \\\"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 2,\\n      \\\"objective\\\": \\\"Research transferability of standard spectra between instruments - detector variation, published methodologies\\\",\\n      \\\"rationale\\\": \\\"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 3,\\n      \\\"objective\\\": \\\"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\\\",\\n      \\\"rationale\\\": \\\"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 4,\\n      \\\"objective\\\": \\\"Research physical standards suppliers and certified reference materials for Al, Si, Mg\\\",\\n      \\\"rationale\\\": \\\"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 5,\\n      \\\"objective\\\": \\\"Research public repositories of EDS/EPMA spectra\\\",\\n      \\\"rationale\\\": \\\"Question 5 asks about downloadable spectrum libraries in EMSA format\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 6,\\n      \\\"objective\\\": \\\"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\\\",\\n      \\\"rationale\\\": \\\"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 7,\\n      \\\"objective\\\": \\\"Create summary artifacts and submit final answer\\\",\\n      \\\"rationale\\\": \\\"Compile all findings into a comprehensive, well-cited answer\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    }\\n  ]\\n}\"}",
+                      "name": "create_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Plan registered and formatted correctly, with some modifications:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "create_plan",
+                "tool_call_id": "toolu_016qD7jWzhrDrjZBuisuwM3M",
+                "info": {
+                  "start_ts": 4092.087651473,
+                  "end_ts": 4092.090283959
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+              {
+                "role": "assistant",
+                "content": "Let me begin with parallel searches across multiple topics:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_012niF3hCcCELZiFsH81WLEJ",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 1, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 1,\\n  \\\"objective\\\": \\\"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\\\",\\n  \\\"rationale\\\": \\\"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\\\",\\n  \\\"status\\\": \\\"in-progress\\\",\\n  \\\"result\\\": null,\\n  \\\"evaluation\\\": null\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"in-progress\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_012niF3hCcCELZiFsH81WLEJ",
+                "info": {
+                  "start_ts": 4105.90889696,
+                  "end_ts": 4105.910674089
+                }
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+                "role": "assistant",
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+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01Q6QzfmUJTUaE37F9rwTvBx",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"EMSA MAS MSA spectrum file format specification EDS microanalysis\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_016Qhr9dS26wxR1YtxHjvMco",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"DTSA-II NIST standards-based k-ratio quantification EDS Ritchie\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_01D5Nvbe43QYfNMbJkfm89c8",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Newbury Ritchie low voltage SEM-EDS quantification k-ratio protocol\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_016rf7SVgyqxtxmhj8EFjKYD",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"EDS detector response silicon drift detector peak tailing incomplete charge collection low energy\"}",
+                      "name": "paper_search"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Reliable Surface Analysis Data of Nanomaterials in Support of Risk Assessment Based on Minimum Information Requirements\nValid Text Names:\n'radnik2021reliablesurfaceanalysis pages 1-2', 'radnik2021reliablesurfaceanalysis pages 2-4', 'radnik2021reliablesurfaceanalysis pages 4-5', 'radnik2021reliablesurfaceanalysis pages 5-7', 'radnik2021reliablesurfaceanalysis pages 7-9', 'radnik2021reliablesurfaceanalysis pages 9-11', 'radnik2021reliablesurfaceanalysis pages 11-12', 'radnik2021reliablesurfaceanalysis pages 12-15', 'radnik2021reliablesurfaceanalysis pages 15-17', 'radnik2021reliablesurfaceanalysis pages 17-18', 'radnik2021reliablesurfaceanalysis pages 18-20', 'radnik2021reliablesurfaceanalysis pages 20-20'\n\nBibTex:\n@article{radnik2021reliablesurfaceanalysis,\n    author = \"Radnik, J\u00f6rg and Kersting, Reinhard and Hagenhoff, Birgit and Bennet, Francesca and Ciornii, Dmitri and Nymark, Penny and Grafstr\u00f6m, Roland and Hodoroaba, Vasile-Dan\",\n    title = \"Reliable Surface Analysis Data of Nanomaterials in Support of Risk Assessment Based on Minimum Information Requirements\",\n    year = \"2021\",\n    journal = \"Nanomaterials\",\n    volume = \"11\",\n    pages = \"639\",\n    month = \"Mar\",\n    doi = \"10.3390/nano11030639\",\n    url = \"https://doi.org/10.3390/nano11030639\",\n    publisher = \"MDPI AG\",\n    issue = \"3\",\n    issn = \"2079-4991\"\n}\n\n\nAbstract:\nThe minimum information requirements needed to guarantee high-quality surface analysis data of nanomaterials are described with the aim to provide reliable and traceable information about size, shape, elemental composition and surface chemistry for risk assessment approaches. The widespread surface analysis methods electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) were considered. The complete analysis sequence from sample preparation, over measurements, to data analysis and data format for reporting and archiving is outlined. All selected methods are used in surface analysis since many years so that many aspects of the analysis (including (meta)data formats) are already standardized. As a practical analysis use case, two coated TiO2 reference nanoparticulate samples, which are available on the Joint Research Centre (JRC) repository, were selected. The added value of the complementary analysis is highlighted based on the minimum information requirements, which are well-defined for the analysis methods selected. The present paper is supposed to serve primarily as a source of understanding of the high standardization level already available for the high-quality data in surface analysis of nanomaterials as reliable input for the nanosafety community.\n\nRelevant Snippet:\n\u2026 EDS spectra of the two particulate samples prepared as dry powder on a silicon substrate were taken at 10 kV, see Figure 4. The analysis surfaces were selected roughly similarly, so \u2026\n\n\n---\n\n## 2. Critical Issues in Scanning Electron Microscope Metrology\nValid Text Names:\n'postek1994criticalissuesin pages 1-2', 'postek1994criticalissuesin pages 2-3', 'postek1994criticalissuesin pages 3-6', 'postek1994criticalissuesin pages 6-7', 'postek1994criticalissuesin pages 7-8', 'postek1994criticalissuesin pages 8-10', 'postek1994criticalissuesin pages 10-11', 'postek1994criticalissuesin pages 11-13', 'postek1994criticalissuesin pages 13-15', 'postek1994criticalissuesin pages 15-16', 'postek1994criticalissuesin pages 16-18', 'postek1994criticalissuesin pages 18-19', 'postek1994criticalissuesin pages 19-20', 'postek1994criticalissuesin pages 20-24', 'postek1994criticalissuesin pages 24-26', 'postek1994criticalissuesin pages 26-28', 'postek1994criticalissuesin pages 28-28', 'postek1994criticalissuesin pages 28-30', 'postek1994criticalissuesin pages 30-30', 'postek1994criticalissuesin pages 30-31', 'postek1994criticalissuesin pages 31-31'\n\nBibTex:\n@article{postek1994criticalissuesin,\n    author = \"Postek, M.T.\",\n    title = \"Critical Issues in Scanning Electron Microscope Metrology\",\n    year = \"1994\",\n    journal = \"Journal of Research of the National Institute of Standards and Technology\",\n    volume = \"99\",\n    pages = \"641-671\",\n    month = \"Sep\",\n    doi = \"10.6028/jres.099.059\",\n    url = \"https://doi.org/10.6028/jres.099.059\",\n    publisher = \"National Institute of Standards and Technology (NIST)\",\n    issue = \"5\",\n    issn = \"1044-677X\"\n}\n\n\nAbstract:\nDuring the manufacturing of present-day integrated circuits, certain measurements must be made of the submicrometer structures composing the device with a high degree of repeatability. Optical microscopy, scanning electron microscopy, and the various forms of scanning probe microscopies are major microscopical techniques used for this submicrometer metrology. New techniques applied to scanning electron microscopy have improved some of the limitations of this technique and time will permit even further improvements. This paper reviews the current state of scanning electron microscope (SEM) metrology in light of many of these recent improvements.\n\nRelevant Snippet:\n\u2026 coupled to an xray microanalysis system. Today, many desktop \u2026 microscope, Proc EMSA GW Bailey, ed. (1968) pp. 359-360. \u2026 detection in electron microscopy and spectroscopy, part 1, \u2026\n\n\n---\n\n## 3. Chemical Microscopy\nValid Text Names:\n'cooke1996chemicalmicroscopy pages 3-4', 'cooke1996chemicalmicroscopy pages 6-7', 'cooke1996chemicalmicroscopy pages 7-8', 'cooke1996chemicalmicroscopy pages 12-13', 'cooke1996chemicalmicroscopy pages 15-16', 'cooke1996chemicalmicroscopy pages 16-17', 'cooke1996chemicalmicroscopy pages 18-19', 'cooke1996chemicalmicroscopy pages 20-21', 'cooke1996chemicalmicroscopy pages 22-23', 'cooke1996chemicalmicroscopy pages 24-25', 'cooke1996chemicalmicroscopy pages 25-26', 'cooke1996chemicalmicroscopy pages 26-27', 'cooke1996chemicalmicroscopy pages 28-29', 'cooke1996chemicalmicroscopy pages 30-31', 'cooke1996chemicalmicroscopy pages 32-33', 'cooke1996chemicalmicroscopy pages 34-35', 'cooke1996chemicalmicroscopy pages 36-37', 'cooke1996chemicalmicroscopy pages 37-37', 'cooke1996chemicalmicroscopy pages 38-39', 'cooke1996chemicalmicroscopy pages 41-42', 'cooke1996chemicalmicroscopy pages 41-41', 'cooke1996chemicalmicroscopy pages 42-43', 'cooke1996chemicalmicroscopy pages 44-44', 'cooke1996chemicalmicroscopy pages 44-45', 'cooke1996chemicalmicroscopy pages 45-46'\n\nBibTex:\n@article{cooke1996chemicalmicroscopy,\n    author = \"Cooke, Peter M.\",\n    title = \"Chemical Microscopy\",\n    volume = \"68\",\n    issn = \"0003-2700\",\n    url = \"https://doi.org/10.1021/a1960011t\",\n    doi = \"10.1021/a1960011t\",\n    number = \"12\",\n    journal = \"Analytical Chemistry\",\n    publisher = \"American Chemical Society (ACS)\",\n    year = \"1996\",\n    month = \"Jan\",\n    pages = \"333-378\",\n    issue = \"12\"\n}\n\n\nRelevant Snippet:\n\u2026 MAS at Loyola Marymount University. It has been highly recommended to microbeam scientists and SEM operators that use ED \u2026 toacoustic spectroscopy, and FT-Raman spectroscopy \u2026\n\n\nUnobtainable Papers:\nJohn J Friel and Richard B Mott. Energy-dispersive spectrometry from then until now: a chronology of innovation. Microscopy and Microanalysis, 4:559-566, Dec 1998. URL: https://doi.org/10.1017/s1431927698980539, doi:10.1017/s1431927698980539.\nMasashi Watanabe. Practical aspects and advanced applications of xeds. ArXiv, pages 467-503, Jan 2016. URL: https://doi.org/10.1007/978-3-319-26651-0\\_17, doi:10.1007/978-3-319-26651-0\\_17.\nJohn Henry J. Scott, Scott A. Wight, and Barbara B. Thorne. Xml for microanalysis: emsa/mas spectrum file format 2.0? Microscopy and Microanalysis, 8:646-647, Aug 2002. URL: https://doi.org/10.1017/s1431927602105782, doi:10.1017/s1431927602105782.\nMasashi Watanabe. Practical Aspects and Advanced Applications of XEDS, pages 729-775. Springer Nature Switzerland, Jan 2026. URL: https://doi.org/10.1007/978-3-031-80789-3\\_24, doi:10.1007/978-3-031-80789-3\\_24.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_01Q6QzfmUJTUaE37F9rwTvBx",
+                "info": {
+                  "start_ts": 4116.718020368,
+                  "end_ts": 4145.733581443
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Using the EDS Clues: Peak Fitting Residual Spectrum and Analytical Total\nValid Text Names:\n'newbury2019usingtheeds pages 1-2'\n\nBibTex:\n@article{newbury2019usingtheeds,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Using the EDS Clues: Peak Fitting Residual Spectrum and Analytical Total\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"446-447\",\n    month = \"Aug\",\n    doi = \"10.1017/s1431927619002964\",\n    url = \"https://doi.org/10.1017/s1431927619002964\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"S2\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nElectron-excited X-ray microanalysis with energy dispersive X-ray spectrometry (EDS) can provide comprehensive elemental analysis for all elements, except for H and He which do not produce X-rays. However, the poorer spectral resolution, ~125 eV full peak width at half peak maximum (FWHM) as compared to ~8 eV for wavelength dispersive spectrometry (WDS) at Mn K-L2,3(5890 eV), leads to frequent peak interference situations in EDS spectra. When interferences occur between the available analytical characteristic X-ray peaks, it is possible that one of the constituents will not be recognized during qualitative analysis (X-ray peak assignment), even for interferences of major-upon-major constituents (where \u201cmajor\u201d is arbitrarily defined as a mass concentration Ci > 0.1; \u201cminor\u201d is 0.01 \u2264 Ci \u2264 0.1, and trace is Ci < 0.01). For interference involving major-upon-minor or major-upon-trace constituents, it is much more likely that the minor or trace constituent will not be recognized. To detect such hidden peaks, the EDS analytical software should construct the \u201cresidual spectrum\u201d that remains after peak fitting of the complete X-ray families of the known constituents to extract characteristic X-ray intensities necessary for the subsequent quantitative analysis. Moreover, if this quantitative analysis is performed by following the standards-based k-ratio protocol with matrix corrections (for electron scattering, X-ray absorption, and secondary X-ray fluorescence) originated by Castaing, then the raw analytical total, i.e., the sum of all constituents including any element such as oxygen calculated by the method of assumed stoichiometry, can also suggest the possibility of missing constituents through deviation below unity [1,2]. The following example illustrates the use of these tools for the analysis of NIST SRM 481 Au-Ag alloys (nominal 20Au-80Ag). The surface being analyzed was metallographically prepared in the early 1970s and stored in a desiccator. In Figure 1 (upper), the Au M-family and Ag L-family appear to account for all the X-ray peaks in this energy range. Quantitative analysis with pure element standards and NIST DTSA-II reveals anomalously low analytical totals with the Ag L-family and either the Au L3-M4,5 (0.9040) or the Au M-family (0.8382). Note that if the normalized concentrations are used, the relative deviation from expected value (RDEV) calculated as: RDEV=[(Measured-True)/True] x 100% is modest for analysis with Ag L3-M4,5 (-0.79%) and Au L3-M4,5 (2.7%), although the result for Au has a large RDEV value for analysis with Ag L3-M4,5 (3.4%) and the Au M-family (-11.8%). Close inspection of the peak fitting residual spectrum shown in Figure 1 (lower) reveals the reason for the low totals: S and Cl are present within a surface tarnish layer, but the S K-family is hidden under the Au M-family, while the Cl K-family is hidden under the Ag L-family. Including these elements in the analysis reveals S (0.0162) and Cl (0.0105) and increases the Ag and Au concentrations due to improved fitting, raising the analytical total to 0.9945 for analysis with Ag L-family and Au L3-M4,5, and to 0.9730 for analysis with the Au Mfamily. When analyzed at low beam energy (5 keV), the tarnish layer comprises a larger fraction of the sampling depth, and the S and Cl K-family peaks become much more obvious, as shown in Figure 2. Quantitative analysis at E0=5 keV yields an analytical total of 0.9961 and an Ag/Au ratio of 8.3 compared to 3.5 expected from the SRM values. Much higher levels of S (0.0949) and Cl (0.0905) are found. The Ag content of the surface layer is likely enriched relative to Au due to the formation of Ag sulfide and chloride in the tarnish layer. Trace Cu (0.0082), likely deposited on the surface during the original polishing by transfer from a nearby co-mounted Cu standard, is also detected in the tarnish layer.\n\nRelevant Snippet:\n\u2026 is performed by following the standards-based k-ratio protocol with matrix corrections (for \u2026 Quantitative analysis with pure element standards and NIST DTSA-II reveals anomalously low \u2026\n\n\nUnobtainable Papers:\nDale E Newbury and Nicholas W M Ritchie. Energy-dispersive x-ray spectrum simulation with nist dtsa-ii: comparing simulated and measured electron-excited spectra. Dec 2022. URL: https://doi.org/10.1017/s1431927622012272, doi:10.1017/s1431927622012272.\nNicholas W.M. Ritchie. Standards-based quantification in dtsa-ii\u2014part i. Microscopy Today, 19:30-36, Aug 2011. URL: https://doi.org/10.1017/s155192951100085x, doi:10.1017/s155192951100085x.\nN. Ritchie, Andrew A. Herzing, and V. Oleshko. Quantification of stem-in-sem energy dispersive x-ray spectra using bulk standards. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29:1921-1930, Nov 2023. URL: https://doi.org/10.1093/micmic/ozad109, doi:10.1093/micmic/ozad109.\nDale Newbury and Nicholas Ritchie. Quantitative electron-excited x-ray microanalysis with low energy l-peaks. Microscopy and Microanalysis, 26:44-49, Aug 2020. URL: https://doi.org/10.1017/s1431927620013215, doi:10.1017/s1431927620013215.\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis at low beam energy: almost always an adventure! \u2020. Microscopy and Microanalysis, 22:735-753, Aug 2016. URL: https://doi.org/10.1017/s1431927616011521, doi:10.1017/s1431927616011521.\nDale E Newbury and Nicholas WM Ritchie. Quantitative electron-excited x-ray microanalysis with low-energy l-shell x-ray peaks measured with energy-dispersive spectrometry. Microscopy and Microanalysis, 27:1375-1408, Dec 2021. URL: https://doi.org/10.1017/s1431927621012617, doi:10.1017/s1431927621012617.\nN. Ritchie, Jeffrey M. Davis, and D. Newbury. Dtsa-ii: a new tool for simulating and quantifying eds spectra - application to difficult overlaps. Microscopy and Microanalysis, 14(S2):1176-1177, Aug 2008. URL: https://doi.org/10.1017/s143192760808361x, doi:10.1017/s143192760808361x.\nNicholas W. M. Ritchie, Michael J. Mengason, and Dale E. Newbury. Standard bundles simplify standards-based quantification in nist dtsa-ii. Microscopy and Microanalysis, 23:220-221, Jul 2017. URL: https://doi.org/10.1017/s1431927617001787, doi:10.1017/s1431927617001787.\nMichael Mengason and Nicholas Ritchie. Overcoming peak overlaps in titanium- and vanadium-bearing materials with multiple linear least squares fitting. Microscopy and Microanalysis, 23(3):491-500, Mar 2017. URL: https://doi.org/10.1017/s1431927617000265, doi:10.1017/s1431927617000265.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\nValid Text Names:\n'goldstein2018quantitativeanalysisthe pages 1-4', 'goldstein2018quantitativeanalysisthe pages 4-6', 'goldstein2018quantitativeanalysisthe pages 6-8', 'goldstein2018quantitativeanalysisthe pages 8-9', 'goldstein2018quantitativeanalysisthe pages 9-11', 'goldstein2018quantitativeanalysisthe pages 11-12', 'goldstein2018quantitativeanalysisthe pages 12-14', 'goldstein2018quantitativeanalysisthe pages 14-16', 'goldstein2018quantitativeanalysisthe pages 16-18', 'goldstein2018quantitativeanalysisthe pages 18-22', 'goldstein2018quantitativeanalysisthe pages 18-18', 'goldstein2018quantitativeanalysisthe pages 22-23', 'goldstein2018quantitativeanalysisthe pages 23-24', 'goldstein2018quantitativeanalysisthe pages 24-26', 'goldstein2018quantitativeanalysisthe pages 26-28', 'goldstein2018quantitativeanalysisthe pages 28-29', 'goldstein2018quantitativeanalysisthe pages 29-30', 'goldstein2018quantitativeanalysisthe pages 30-31', 'goldstein2018quantitativeanalysisthe pages 31-31'\n\nBibTex:\n@article{goldstein2018quantitativeanalysisthe,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"309-339\",\n    doi = \"10.1007/978-1-4939-6676-9\\_20\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_20\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nThis module discusses the procedure used to perform a rigorous quantitative elemental microanalysis by SEM/EDS following the k-ratio/matrix correction protocol using the NIST DTSA-II software engine for bulk specimens. Bulk specimens have dimensions that are sufficiently large to contain the full range of the direct electron-excited X-ray production (typically 0.5\u201310 \u03bcm) as well as the range of secondary X-ray fluorescence induced by the propagation of the characteristic and continuum X-rays (typically 10\u2013100 \u03bcm).\n\nRelevant Snippet:\n\u2026 This chapter discusses the procedure used to perform a rigorous quantitative elemental microanalysis by SEM/EDS following the k-ratio/matrix correction protocol using the NIST DTSA-\u2026\n\n\n---\n\n## 2. Quantitative SEM/EDS, Step 1: What Constitutes a Sufficiently Flat Specimen?\nValid Text Names:\n'newbury2013quantitativesemedsstep pages 1-2'\n\nBibTex:\n@article{newbury2013quantitativesemedsstep,\n    author = \"Newbury, D.E. and Ritchie, N.W.\",\n    title = \"Quantitative SEM/EDS, Step 1: What Constitutes a Sufficiently Flat Specimen?\",\n    year = \"2013\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"19\",\n    pages = \"1244-1245\",\n    month = \"Aug\",\n    doi = \"10.1017/s1431927613008210\",\n    url = \"https://doi.org/10.1017/s1431927613008210\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"S2\",\n    issn = \"1431-9276\"\n}\n\n\nRelevant Snippet:\n\u2026 -8370 The most rigorous quantitative electron-excited x-ray \u2026 spectrometry (SEM/EDS) follows the k ratio protocol: measure \u2026 By utilizing the k ratio protocol, SEM/EDS has been shown to \u2026\n\n\n---\n\n## 3. Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\nValid Text Names:\n'newbury2019electronexcitedxraymicroanalysis pages 1-2', 'newbury2019electronexcitedxraymicroanalysis pages 2-3', 'newbury2019electronexcitedxraymicroanalysis pages 3-4', 'newbury2019electronexcitedxraymicroanalysis pages 4-5', 'newbury2019electronexcitedxraymicroanalysis pages 5-6', 'newbury2019electronexcitedxraymicroanalysis pages 6-8', 'newbury2019electronexcitedxraymicroanalysis pages 8-10', 'newbury2019electronexcitedxraymicroanalysis pages 10-13', 'newbury2019electronexcitedxraymicroanalysis pages 13-15', 'newbury2019electronexcitedxraymicroanalysis pages 15-16', 'newbury2019electronexcitedxraymicroanalysis pages 16-18', 'newbury2019electronexcitedxraymicroanalysis pages 18-20', 'newbury2019electronexcitedxraymicroanalysis pages 20-22', 'newbury2019electronexcitedxraymicroanalysis pages 22-26', 'newbury2019electronexcitedxraymicroanalysis pages 26-28', 'newbury2019electronexcitedxraymicroanalysis pages 28-29', 'newbury2019electronexcitedxraymicroanalysis pages 29-30', 'newbury2019electronexcitedxraymicroanalysis pages 29-29', 'newbury2019electronexcitedxraymicroanalysis pages 30-31'\n\nBibTex:\n@article{newbury2019electronexcitedxraymicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W.M.\",\n    title = \"Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"1075-1105\",\n    month = \"Oct\",\n    doi = \"10.1017/s143192761901482x\",\n    url = \"https://doi.org/10.1017/s143192761901482x\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"05\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nAbstract 2018 marked the 50th anniversary of the introduction of energy dispersive X-ray spectrometry (EDS) with semiconductor detectors to electron-excited X-ray microanalysis. Initially useful for qualitative analysis, EDS has developed into a fully quantitative analytical tool that can match wavelength dispersive spectrometry for accuracy in the determination of major (mass concentration C > 0.1) and minor (0.01 \u2264 C \u2264 0.1) constituents, and useful accuracy can extend well into the trace (0.001 < C < 0.01) constituent range even when severe peak interference occurs. Accurate analysis is possible for low atomic number elements (B, C, N, O, and F), and at low beam energy, which can optimize lateral and depth spatial resolution. By recording a full EDS spectrum at each picture element of a scan, comprehensive quantitative compositional mapping can also be performed.\n\nRelevant Snippet:\n\u2026 of quantitative analysis that followed the Castaing k-ratio/matrix corrections protocol (eg, \u2026 a new level of electron-excited elemental X-ray microanalysis (Newbury & Ritchie, 2015a). \u2026\n\n\n---\n\n## 4. Testing the accuracy of low-beam-energy electron-excited X-ray microanalysis with energy-dispersive spectrometry\nValid Text Names:\n'newbury2024testingtheaccuracy pages 1-3', 'newbury2024testingtheaccuracy pages 3-4', 'newbury2024testingtheaccuracy pages 4-6', 'newbury2024testingtheaccuracy pages 6-8', 'newbury2024testingtheaccuracy pages 8-9', 'newbury2024testingtheaccuracy pages 9-11', 'newbury2024testingtheaccuracy pages 11-12', 'newbury2024testingtheaccuracy pages 12-14', 'newbury2024testingtheaccuracy pages 14-16', 'newbury2024testingtheaccuracy pages 16-18', 'newbury2024testingtheaccuracy pages 18-22', 'newbury2024testingtheaccuracy pages 22-24', 'newbury2024testingtheaccuracy pages 24-24'\n\nBibTex:\n@article{newbury2024testingtheaccuracy,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Testing the accuracy of low-beam-energy electron-excited X-ray microanalysis with energy-dispersive spectrometry\",\n    year = \"2024\",\n    journal = \"Journal of Materials Science\",\n    volume = \"59\",\n    pages = \"19088-19111\",\n    month = \"Oct\",\n    doi = \"10.1007/s10853-024-10285-4\",\n    url = \"https://doi.org/10.1007/s10853-024-10285-4\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"40\",\n    issn = \"0022-2461\"\n}\n\n\nAbstract:\nThe accuracy of electron-excited X-ray microanalysis with energy-dispersive spectrometry (EDS) has been tested in the low beam energy range, specifically at an incident beam energy of 5 keV, which is the lowest beam energy for which a useful characteristic X-ray peak can be excited for all elements of the periodic table, excepting H and He. Elemental analysis results are reported for certified reference materials (CRM), stoichiometric compounds, minerals, and metal alloys of independently known or measured composition which had microscopic homogeneity suitable for microanalysis. Two-hundred sixty-three concentration measurements for 39 elements in 113 materials were determined following the k-ratio protocol and using the EDS analytical software NIST DTSA-II. The accuracy of the results, as characterized by the relative deviation from expected value (RDEV) metric, was such that more than 98% of the results were found to be captured within a range of \u00b15% RDEV, while 82% of the results fell in the range -2% to 2% RDEV.\n\nRelevant Snippet:\n\u2026 k-ratio protocol and using the EDS analytical software NIST \u2026 Analysis followed the standards-based measurement protocol\u2026 as that provided by the NIST DTSA-II software platform [3]. \u2026\n\n\n---\n\n## 5. Quantitative Analysis: From k-ratio to Composition\nValid Text Names:\n'goldstein2018quantitativeanalysisfrom pages 1-3', 'goldstein2018quantitativeanalysisfrom pages 3-4', 'goldstein2018quantitativeanalysisfrom pages 4-5', 'goldstein2018quantitativeanalysisfrom pages 5-6', 'goldstein2018quantitativeanalysisfrom pages 6-7', 'goldstein2018quantitativeanalysisfrom pages 7-9', 'goldstein2018quantitativeanalysisfrom pages 9-10', 'goldstein2018quantitativeanalysisfrom pages 10-11', 'goldstein2018quantitativeanalysisfrom pages 11-12', 'goldstein2018quantitativeanalysisfrom pages 12-14', 'goldstein2018quantitativeanalysisfrom pages 14-15', 'goldstein2018quantitativeanalysisfrom pages 15-17', 'goldstein2018quantitativeanalysisfrom pages 17-18', 'goldstein2018quantitativeanalysisfrom pages 18-19'\n\nBibTex:\n@article{goldstein2018quantitativeanalysisfrom,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Quantitative Analysis: From k-ratio to Composition\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"289-307\",\n    month = \"Nov\",\n    doi = \"10.1007/978-1-4939-6676-9\\_19\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_19\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nA k-ratio is the ratio of a pair of characteristic X-ray line intensities, I, measured under similar experimental conditions for the unknown (unk) and standard (std): \n \n$$ k={I}_{unk}/{I}_{std} $$ \n \nThe measured intensities can be associated with a single characteristic X-ray line (as is typically the case for wavelength spectrometers) or associated with a family of characteristic X-ray lines (as is typically the case for energy dispersive spectrometers.) The numerator of the k-ratio is typically the intensity measured from an unknown sample and the denominator is typically the intensity measured from a standard material\u2014a material of known composition.\n\nRelevant Snippet:\n\u2026 Table 19.2, which gives the results of an SEM- EDS analysis of a YBa2Cu3O7-X single crystal by the k-ratio/standards protocol (NIST DTSA) compared to standardless \u2026\n\n\n---\n\n## 6. Measurement uncertainties of energy dispersive X-ray spectroscopy in the scanning electron microscope (SEM-EDX/EDS)\nValid Text Names:\n'tong2026measurementuncertaintiesof pages 1-8', 'tong2026measurementuncertaintiesof pages 8-11', 'tong2026measurementuncertaintiesof pages 11-12', 'tong2026measurementuncertaintiesof pages 12-15', 'tong2026measurementuncertaintiesof pages 15-18', 'tong2026measurementuncertaintiesof pages 18-21', 'tong2026measurementuncertaintiesof pages 21-24', 'tong2026measurementuncertaintiesof pages 24-26'\n\nBibTex:\n@article{tong2026measurementuncertaintiesof,\n    author = \"Tong, V. and Mingard, K.\",\n    title = \"Measurement uncertainties of energy dispersive X-ray spectroscopy in the scanning electron microscope (SEM-EDX/EDS)\",\n    year = \"2026\",\n    journal = \"Unknown journal\",\n    month = \"Mar\",\n    doi = \"10.47120/npl.mat135\",\n    url = \"https://doi.org/10.47120/npl.mat135\",\n    publisher = \"National Physical Laboratory\"\n}\n\n\nRelevant Snippet:\n\u2026 microscope (SEM-EDX or SEM-EDS \u2013 the terms are generally \u2026 [1] DE Newbury and NWM Ritchie, \u2018Performing elemental \u2026 - k-ratio standards database optimised for 10 kV - Qualitative \u2026\n\n\n---\n\n## 7. Chemical characterisation is rough: the impact of topography and measurement parameters on energy-dispersive X-ray spectroscopy in biominerals\nValid Text Names:\n'shirley2022chemicalcharacterisationis pages 1-2', 'shirley2022chemicalcharacterisationis pages 2-5', 'shirley2022chemicalcharacterisationis pages 5-7', 'shirley2022chemicalcharacterisationis pages 7-9', 'shirley2022chemicalcharacterisationis pages 9-12', 'shirley2022chemicalcharacterisationis pages 12-14', 'shirley2022chemicalcharacterisationis pages 14-15', 'shirley2022chemicalcharacterisationis pages 15-15'\n\nBibTex:\n@article{shirley2022chemicalcharacterisationis,\n    author = \"Shirley, Bryan and Jarochowska, Emilia\",\n    title = \"Chemical characterisation is rough: the impact of topography and measurement parameters on energy-dispersive X-ray spectroscopy in biominerals\",\n    year = \"2022\",\n    journal = \"Facies\",\n    volume = \"68\",\n    month = \"Mar\",\n    doi = \"10.1007/s10347-022-00645-4\",\n    url = \"https://doi.org/10.1007/s10347-022-00645-4\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"2\",\n    issn = \"0172-9179\"\n}\n\n\nAbstract:\nEnergy dispersive X-ray microscopy (EDX) is a widely available, inexpensive method of characterizing the in-situ elemental composition of samples in Earth and life sciences. Common protocols and textbooks focussing on material sciences address EDX analysis of metallic samples that can be polished perfectly, whereas geoscientists often investigate specimens with prominent topography and composed of light, difficult to resolve elements. This is further compounded by the scarcity of literature surrounding the methodology of SEM\u2013EDX in the field of palaeontology, leading to common misinterpretations and artefacts during data acquisition. Here, the common errors in elemental composition obtained with EDX arising from surface topography and from parameters subject to user decisions are quantified. As a model, fossil bioapatite (conodonts) and abiotic Durango apatite are used. It is shown that even microscale topography can distort measured composition by up to 34%, whereas topographic features such as tilt with respect to the electron beam lead to differences of up to 85%. Working distance was not the most important parameter affecting the results and led to differences in composition of up to 13%, whereas the choice of standard and its levelling with the sample surface led to inaccuracy reaching 33%. EDX results can be also affected by beam damage and the effects of acceleration voltage on sample acquisition and resolution are quantified. An estimate is provided of the severity of errors associated with samples which cannot satisfy preparation requirements for EDX fully, such as holotypes, and with user decisions. Using a palaeontological example, recommendations are offered for the best parameters and the relative importance of error sources are assessed.\n\nRelevant Snippet:\n\u2026 \u201csemi-quantitative\u201d (Newbury et al. 1995; Newbury and Ritchie 2014). \u2026 a low voltage for EDX has a number of limitations; using low \u2026 through standardization following the k ratio protocol. \u2026\n\n\n---\n\n## 8. Enhanced quantification for 3D SEM\u2013EDS: Using the full set of available X-ray lines\nValid Text Names:\n'burdet2015enhancedquantificationfor pages 1-2', 'burdet2015enhancedquantificationfor pages 2-3', 'burdet2015enhancedquantificationfor pages 3-4', 'burdet2015enhancedquantificationfor pages 4-5', 'burdet2015enhancedquantificationfor pages 5-8', 'burdet2015enhancedquantificationfor pages 8-9', 'burdet2015enhancedquantificationfor pages 8-8', 'burdet2015enhancedquantificationfor pages 9-10'\n\nBibTex:\n@article{burdet2015enhancedquantificationfor,\n    author = \"Burdet, Pierre and Croxall, S.A. and Midgley, P.A.\",\n    title = \"Enhanced quantification for 3D SEM\u2013EDS: Using the full set of available X-ray lines\",\n    year = \"2015\",\n    journal = \"Ultramicroscopy\",\n    volume = \"148\",\n    pages = \"158-167\",\n    month = \"Jan\",\n    doi = \"10.1016/j.ultramic.2014.10.010\",\n    url = \"https://doi.org/10.1016/j.ultramic.2014.10.010\",\n    publisher = \"Elsevier BV\",\n    issn = \"0304-3991\"\n}\n\n\nRelevant Snippet:\n\u2026 k-ratio:(1) k - ratio A = I u n k , A I s t d , A , where I is the intensity, A is an element, unk is the unknown, and std is the standard. In a first step to obtain the k-ratio\u2026 iterative procedure until a \u2026\n\n\nUnobtainable Papers:\nD.E. Newbury and N.W. Ritchie. How to do really bad sem/eds quantitative analysis, and never even notice! Microscopy and Microanalysis, 18:1004-1005, Jul 2012. URL: https://doi.org/10.1017/s1431927612006873, doi:10.1017/s1431927612006873.\nDale E. Newbury and Nicholas W. M. Ritchie. Rigorous quantitative elemental microanalysis by scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds) with spectrum processing by nist dtsa-ii. SPIE Proceedings, 9236:92360H, Sep 2014. URL: https://doi.org/10.1117/12.2065842, doi:10.1117/12.2065842.\nAlexis T. Riche, Peter McSwiggen, Kayleigh Harvey, Shelby Bowden, Rachel Bergin, Spencer M. Scott, Bryan J. Foley, and Kyle M. Samperton. Mixed element microparticle characterization by electron probe microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, Mar 2025. URL: https://doi.org/10.1093/mam/ozaf022, doi:10.1093/mam/ozaf022.\nDale E. Newbury and Nicholas W. M. Ritchie. Faults and foibles of quantitative scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds). SPIE Proceedings, 8378:837803, May 2012. URL: https://doi.org/10.1117/12.912770, doi:10.1117/12.912770.\nDale E. Newbury* and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds) quantitative? Scanning, 35 3:141-68, May 2013. URL: https://doi.org/10.1002/sca.21041, doi:10.1002/sca.21041.\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W.M. Ritchie, John Henry J. Scott, and David C. Joy. Scanning electron microscopy and x-ray microanalysis. Scanning Electron Microscopy and X-Ray Microanalysis, Jan 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9, doi:10.1007/978-1-4939-6676-9.\nAaron Shugar, Michael Notis, Dale Newbury, and Nicholas Ritchie. Investigating a moche cast copper artifact for its manufacturing technology. MRS Proceedings, 1656:95-109, Aug 2017. URL: https://doi.org/10.1557/opl.2014.822, doi:10.1557/opl.2014.822.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)\nValid Text Names:\n'newbury2015performingelementalmicroanalysis pages 1-2', 'newbury2015performingelementalmicroanalysis pages 2-4', 'newbury2015performingelementalmicroanalysis pages 4-5', 'newbury2015performingelementalmicroanalysis pages 5-6', 'newbury2015performingelementalmicroanalysis pages 6-7', 'newbury2015performingelementalmicroanalysis pages 7-9', 'newbury2015performingelementalmicroanalysis pages 9-11', 'newbury2015performingelementalmicroanalysis pages 11-13', 'newbury2015performingelementalmicroanalysis pages 13-15', 'newbury2015performingelementalmicroanalysis pages 15-17', 'newbury2015performingelementalmicroanalysis pages 17-20', 'newbury2015performingelementalmicroanalysis pages 20-21', 'newbury2015performingelementalmicroanalysis pages 21-23', 'newbury2015performingelementalmicroanalysis pages 23-25', 'newbury2015performingelementalmicroanalysis pages 25-26', 'newbury2015performingelementalmicroanalysis pages 26-26'\n\nBibTex:\n@article{newbury2015performingelementalmicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)\",\n    year = \"2015\",\n    journal = \"Journal of Materials Science\",\n    volume = \"50\",\n    pages = \"493-518\",\n    month = \"Nov\",\n    doi = \"10.1007/s10853-014-8685-2\",\n    url = \"https://doi.org/10.1007/s10853-014-8685-2\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"2\",\n    issn = \"0022-2461\"\n}\n\n\nAbstract:\nElectron-excited X-ray microanalysis performed in the scanning electron microscope with energy-dispersive X-ray spectrometry (EDS) is a core technique for characterization of the microstructure of materials. The recent advances in EDS performance with the silicon drift detector (SDD) enable accuracy and precision equivalent to that of the high spectral resolution wavelength-dispersive spectrometer employed on the electron probe microanalyzer platform. SDD-EDS throughput, resolution, and stability provide practical operating conditions for measurement of high-count spectra that form the basis for peak fitting procedures that recover the characteristic peak intensities even for elemental combination where severe peak overlaps occur, such PbS, MoS2, BaTiO3, SrWO4, and WSi2. Accurate analyses are also demonstrated for interferences involving large concentration ratios: a major constituent on a minor constituent (Ba at 0.4299 mass fraction on Ti at 0.0180) and a major constituent on a trace constituent (Ba at 0.2194 on Ce at 0.00407; Si at 0.1145 on Ta at 0.0041). Accurate analyses of low atomic number elements, C, N, O, and F, are demonstrated. Measurement of trace constituents with limits of detection below 0.001 mass fraction (1000\u00a0ppm) is possible within a practical measurement time of 500\u00a0s.\n\nRelevant Snippet:\n\u2026 of quantitative analysis was based upon their experience with the WDS k-ratio protocol. The \u2026 Unless the specimen geometry is carefully controlled, SEM/EDS analysis is subject to errors \u2026\n\n\nUnobtainable Papers:\nM. MARTINI, J.W. MAYER, and K.R. ZANIO. Drift velocity and trapping in semiconductors\u2014transient charge technique. ArXiv, 3:181-261, Jan 1972. URL: https://doi.org/10.1016/b978-0-12-002903-7.50010-2, doi:10.1016/b978-0-12-002903-7.50010-2.\nFrancesco Ceraudo, Giovanni Della Casa, Giuseppe Bertuccio, Walter Bonvicini, Riccardo Campana, Daniela Cirrincione, Ettore Del Monte, Yuri Evangelista, Marco Feroci, Francesco Ficorella, Mauro Fiorini, Marco Grassi, Piero Malcovati, Filippo Mele, Giancarlo Pepponi, Alexandre Rachevski, Irina Rashevskaya, Gianluigi Zampa, Nicola Zampa, and Nicola Zorzi. Imaging and spectroscopic performances of the silicon drift detector of the wide field monitor. Space Telescopes and Instrumentation 2024: Ultraviolet to Gamma Ray, 13093:130936U-130936U-9, Aug 2024. URL: https://doi.org/10.1117/12.3020204, doi:10.1117/12.3020204.\nNicholas W.M. Ritchie, Dale E. Newbury, and Jeffrey M. Davis. Eds measurements of x-ray intensity at wds precision and accuracy using a silicon drift detector. Microscopy and Microanalysis, 18:892-904, Jul 2012. URL: https://doi.org/10.1017/s1431927612001109, doi:10.1017/s1431927612001109.\nDale E. Newbury. Electron-excited energy dispersive x-ray spectrometry at high speed and at high resolution: silicon drift detectors and microcalorimeters. Microscopy and Microanalysis, 12:527-537, Oct 2006. URL: https://doi.org/10.1017/s1431927606060673, doi:10.1017/s1431927606060673.\nVasile-Dan Hodoroaba and Mathias Procop. A method to test the performance of an energy-dispersive x-ray spectrometer (eds). Microscopy and Microanalysis, 20:1556-1564, Jul 2014. URL: https://doi.org/10.1017/s1431927614001652, doi:10.1017/s1431927614001652.\nG. Calzolai, S. Tapinassi, M. Chiari, M. Giannoni, S. Nava, G. Pazzi, and F. Lucarelli. Silicon drift detector response function for pixe spectra fitting. Feb 2018. URL: https://doi.org/10.1016/j.nimb.2017.09.010, doi:10.1016/j.nimb.2017.09.010.\nDale E. Newbury and Nicholas W. M. Ritchie. Elemental mapping of microstructures by scanning electron microscopy-energy dispersive x-ray spectrometry (sem-eds): extraordinary advances with the silicon drift detector (sdd). Journal of Analytical Atomic Spectrometry, 28:973-988, Jun 2013. URL: https://doi.org/10.1039/c3ja50026h, doi:10.1039/c3ja50026h.\nPJ Statham. X\u2010ray microanalysis with si (li) detectors. Unknown journal, 1981. URL: https://doi.org/10.1111/j.1365-2818.1981.tb01276, doi:10.1111/j.1365-2818.1981.tb01276.\nAndrea Vacchi. Silicon Drift Detectors, pages 609-661. Springer Nature Singapore, Jan 2024. URL: https://doi.org/10.1007/978-981-19-6960-7\\_18, doi:10.1007/978-981-19-6960-7\\_18.\nM. Miliucci, A. Scordo, D. Sirghi, A. Amirkhani, A. Baniahmad, M. Bazzi, D. Bosnar, M. Bragadireanu, M. Carminati, M. Cargnelli, A. Clozza, C. Curceanu, L. De Paolis, R R Del Grande, C. Fiorini, C. Guaraldo, M. Iliescu, M. Iwasaki, P. Levi Sandri, J. Marton, P. Moskal, F. Napolitano, S. Nied\u017awiecki, K. Piscicchia, F. Sgaramella, H. Shi, M. Silarski, F. Sirghi, M. Skurzok, A. Spallone, M. T\u00fcchler, O. V\u00e1zquez Doce, and J. Zmeskal. Silicon drift detectors system for high-precision light kaonic atoms spectroscopy. Measurement Science and Technology, 32:095501, May 2021. URL: https://doi.org/10.1088/1361-6501/abeea9, doi:10.1088/1361-6501/abeea9.\nM. Miliucci, M. Iliescu, F. Sgaramella, M. Bazzi, D. Bosnar, M. Bragadireanu, M. Carminati, M. Cargnelli, A. Clozza, C. Curceanu, G. Deda, L. De Paolis, R R Del Grande, C. Fiorini, C. Guaraldo, M. Iwasaki, P. King, P. Levi Sandri, J. Marton, P. Moskal, F. Napolitano, S. Nied\u017awiecki, K. Piscicchia, A. Scordo, H. Shi, M. Silarski, D. Sirghi, F. Sirghi, M. Skurzok, A. Spallone, M. T\u00fcchler, O. V\u00e1zquez Doce, and J. Zmeskal. Large area silicon drift detectors system for high precision timed x-ray spectroscopy. Jun 2022. URL: https://doi.org/10.1088/1361-6501/ac777a, doi:10.1088/1361-6501/ac777a.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                      "arguments": "{\"query\": \"EDS standard spectrum transferability detector response cross-instrument k-ratio Statham Fiori\"}",
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+                      "arguments": "{\"query\": \"EPMA electron probe microanalysis standards certified reference materials magnesium aluminium silicon\"}",
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+                    "id": "toolu_011WZDp8fnpXdE1hZ7xmFDjG",
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+                      "arguments": "{\"query\": \"AlSi10Mg additive manufacturing SEM-EDS composition quantification laser powder bed fusion\"}",
+                      "name": "paper_search"
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+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=13 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. X-ray Spectrometry.\nValid Text Names:\n'tsuji2010xrayspectrometry. pages 1-2', 'tsuji2010xrayspectrometry. pages 2-3', 'tsuji2010xrayspectrometry. pages 3-4', 'tsuji2010xrayspectrometry. pages 4-5', 'tsuji2010xrayspectrometry. pages 5-6', 'tsuji2010xrayspectrometry. pages 6-7', 'tsuji2010xrayspectrometry. pages 7-8', 'tsuji2010xrayspectrometry. pages 8-9', 'tsuji2010xrayspectrometry. pages 9-10', 'tsuji2010xrayspectrometry. pages 12-13', 'tsuji2010xrayspectrometry. pages 14-15', 'tsuji2010xrayspectrometry. pages 15-16', 'tsuji2010xrayspectrometry. pages 16-18', 'tsuji2010xrayspectrometry. pages 19-20', 'tsuji2010xrayspectrometry. pages 20-21', 'tsuji2010xrayspectrometry. pages 21-23', 'tsuji2010xrayspectrometry. pages 25-27', 'tsuji2010xrayspectrometry. pages 27-28', 'tsuji2010xrayspectrometry. pages 28-29', 'tsuji2010xrayspectrometry. pages 29-30', 'tsuji2010xrayspectrometry. pages 30-31', 'tsuji2010xrayspectrometry. pages 31-32', 'tsuji2010xrayspectrometry. pages 35-36', 'tsuji2010xrayspectrometry. pages 36-36', 'tsuji2010xrayspectrometry. pages 38-38'\n\nBibTex:\n@article{tsuji2010xrayspectrometry.,\n    author = \"Tsuji, Kouichi and Nakano, Kazuhiko and Takahashi, Yoshio and Hayashi, Kouichi and Ro, Chul-Un\",\n    title = \"X-ray Spectrometry.\",\n    year = \"2010\",\n    journal = \"Analytical chemistry\",\n    volume = \"82 12\",\n    pages = \"4950-87\",\n    doi = \"10.1021/ac101069d\",\n    url = \"https://doi.org/10.1021/ac101069d\",\n    month = \"May\",\n    publisher = \"American Chemical Society (ACS)\",\n    issue = \"12\",\n    issn = \"0003-2700\"\n}\n\n\nRelevant Snippet:\n\u2026 DTSA-II was developed in Java for a high level of platform independence and available free from the NIST \u2026 Scott and Ritchie (111) demonstrated that NISTMonte for the MC simulations \u2026\n\n\nUnobtainable Papers:\nNicholas W.M. Ritchie. Using dtsa-ii to simulate and interpret energy dispersive spectra from particles. Microscopy and Microanalysis, 16:248-258, Apr 2010. URL: https://doi.org/10.1017/s1431927610000243, doi:10.1017/s1431927610000243.\nP T Pinard and S Richter. Improving the quantification at high spatial resolution using a field emission electron microprobe. IOP Conference Series: Materials Science and Engineering, 55:012016, Mar 2014. URL: https://doi.org/10.1088/1757-899x/55/1/012016, doi:10.1088/1757-899x/55/1/012016.\nNicholas W. M. Ritchie. Efficient simulation of secondary fluorescence via nist dtsa-ii monte carlo. Microscopy and Microanalysis, 23:618-633, Mar 2017. URL: https://doi.org/10.1017/s1431927617000307, doi:10.1017/s1431927617000307.\nJuan P.N. Cruz, Carlos M. Garz\u00f3n, Johan K. Nore\u00f1a, Fabian Pineda, Juan. S. Cachaya, and Abel A.C. Recco. Accuracy of a reference-free monte carlo approach for sem-eds thickness assessment of tin coatings onto diverse substrates. Micron, 154:103204, Mar 2022. URL: https://doi.org/10.1016/j.micron.2021.103204, doi:10.1016/j.micron.2021.103204.\nDale E. Newbury and Nicholas W. M. Ritchie. Simulating electron-excited energy dispersive x-ray spectra with the nist dtsa-ii open-source software platform. MRS Advances, 7:892-898, Jun 2022. URL: https://doi.org/10.1557/s43580-022-00300-8, doi:10.1557/s43580-022-00300-8.\nNicholas W.M. Ritchie. Spectrum simulation in dtsa-ii. Microscopy and Microanalysis, 15:454-468, Sep 2009. URL: https://doi.org/10.1017/s1431927609990407, doi:10.1017/s1431927609990407.\nD. E. Pukhov. A comparison of the peak-to-background method and an empirical correction of the results in the energy-dispersive electron probe quantitative analysis of powder materials. Journal of Analytical Chemistry, 78:652-662, May 2023. URL: https://doi.org/10.1134/s1061934823050118, doi:10.1134/s1061934823050118.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=19 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Phase identification of microfeatures using EPMA methods, especially high-resolution X-ray spectroscopy\nValid Text Names:\n'love2001phaseidentificationof pages 1-2', 'love2001phaseidentificationof pages 2-3', 'love2001phaseidentificationof pages 3-6', 'love2001phaseidentificationof pages 6-7', 'love2001phaseidentificationof pages 7-11', 'love2001phaseidentificationof pages 11-14', 'love2001phaseidentificationof pages 14-14'\n\nBibTex:\n@article{love2001phaseidentificationof,\n    author = \"Love, G and Scott, V.D\",\n    title = \"Phase identification of microfeatures using EPMA methods, especially high-resolution X-ray spectroscopy\",\n    year = \"2001\",\n    journal = \"Micron\",\n    volume = \"32 2\",\n    pages = \"115-28\",\n    month = \"Feb\",\n    doi = \"10.1016/s0968-4328(00)00004-4\",\n    url = \"https://doi.org/10.1016/s0968-4328(00)00004-4\",\n    publisher = \"Elsevier BV\",\n    issue = \"2\",\n    issn = \"0968-4328\"\n}\n\n\nRelevant Snippet:\n\u2026 with negligible silicon and only a small amount of aluminium. \u2026 composite of magnesium alloy reinforced with silicon carbide \u2026 effects; standards of silicon carbide and silica were prepared \u2026\n\n\nUnobtainable Papers:\nAndy Fisher, Phill S. Goodall, Michael W. Hinds, Simon M. Nelms, and Denise M. Penny. Atomic spectrometry update . industrial analysis : metals , chemicals and advanced materials. Journal of Analytical Atomic Spectrometry, 18:1497, Jan 2005. URL: https://doi.org/10.1039/c2ja90058k, doi:10.1039/c2ja90058k.\nS. Timmerman, S. Matveev, M.U. Gress, and G.R. Davies. A methodology for wavelength dispersive electron probe microanalysis of unpolished silicate minerals. Journal of Geochemical Exploration, 159:243-251, Dec 2015. URL: https://doi.org/10.1016/j.gexplo.2015.09.016, doi:10.1016/j.gexplo.2015.09.016.\nNirmalya Karar and Vipin Jain. Alloys as Certified Reference Materials (CRMs), pages 697-730. Springer Nature Singapore, Jan 2023. URL: https://doi.org/10.1007/978-981-99-2074-7\\_33, doi:10.1007/978-981-99-2074-7\\_33.\nJustyna Kostrzewa, Jacek Anyszkiewicz, Tadeusz Gorewoda, Ewa Jamroz, Kjell Blandhol, Alf Yngve Guldhav, Magdalena Knapik, Jadwiga Charasi\u0144ska, and Agata Jak\u00f3bik-Kolon. Development of new series of certified reference materials for ferrosilicon magnesium alloys. Processes, 12:1017, May 2024. URL: https://doi.org/10.3390/pr12051017, doi:10.3390/pr12051017.\nYuanze Wang, Dayi Yang, Hongshi Zhao, Chao Liu, Feng He, Yingliang Tian, and Zhiyong Zhao. Synergistic enhancement of transparent magnesium\u2013aluminium\u2013silicon glass-ceramic containing alkali-free nanocrystalline phase: effects of crystallisation and ion exchange. Jun 2026. URL: https://doi.org/10.1016/j.jeurceramsoc.2025.118060, doi:10.1016/j.jeurceramsoc.2025.118060.\nR. B. Marinenko and D. H. Blackburn. Glasses for microanalysis : new nbs (u.s.a.) standard reference materials. Le Journal De Physique Colloques, 45:C2-769-C2-774, Feb 1984. URL: https://doi.org/10.1051/jphyscol:19842177, doi:10.1051/jphyscol:19842177.\nKurt F.J. Heinrich and Dale E. Newbury. Electron Probe X-Ray Microanalysis, pages 516-535. ASM International, Jan 1986. URL: https://doi.org/10.31399/asm.hb.v10.a0001768, doi:10.31399/asm.hb.v10.a0001768.\nXiangfa Liu, Jinguo Qiao, Yuying Wu, Xiangjun Liu, and Xiufang Bian. Epma analysis of calcium-rich compounds in near eutectic al\u2013si alloys. Journal of Alloys and Compounds, 388:83-90, Feb 2005. URL: https://doi.org/10.1016/j.jallcom.2004.07.012, doi:10.1016/j.jallcom.2004.07.012.\nV. D. Scott and G. Love. Epma using low-energy (0.1-1.0 kev) x-rays-an historical perspective. Journal of Analytical Atomic Spectrometry, 14:367-376, Jan 1999. URL: https://doi.org/10.1039/a806766j, doi:10.1039/a806766j.\nR. B. Marinenko. Standards for electron probe microanalysis. ArXiv, pages 251-260, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_14, doi:10.1007/978-1-4899-2617-3\\_14.\nOlga Yu. Belozerova, Mikhail A. Mikhailov, and Tamara V. Demina. Investigation of synthesized be-bearing silicate glass as laboratory reference sample at x-ray electron probe microanalysis of silicates. Spectrochimica Acta Part B: Atomic Spectroscopy, 127:34-41, Jan 2017. URL: https://doi.org/10.1016/j.sab.2016.11.007, doi:10.1016/j.sab.2016.11.007.\nM. Lovell, W. D. Ehmann, W. Markesbery, S. Melethil, C. Swyt, and P. Zatta. Standardization in biological analyses of aluminum: what are the needs? Journal of toxicology and environmental health, 48 6:637-48, Aug 1996. URL: https://doi.org/10.1080/009841096161113, doi:10.1080/009841096161113.\nValentina G. Batanova, Alexander V. Sobolev, and Dmitry V. Kuzmin. Trace element analysis of olivine: high precision analytical method for jeol jxa-8230 electron probe microanalyser. Chemical Geology, 419:149-157, Dec 2015. URL: https://doi.org/10.1016/j.chemgeo.2015.10.042, doi:10.1016/j.chemgeo.2015.10.042.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=19 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Influence of silicon morphology on direct current plasma electrolytic oxidation process in AlSi10Mg alloy produced with laser powder bed fusion\nValid Text Names:\n'pezzato2022influenceofsilicon pages 1-2', 'pezzato2022influenceofsilicon pages 2-3', 'pezzato2022influenceofsilicon pages 3-4', 'pezzato2022influenceofsilicon pages 4-5', 'pezzato2022influenceofsilicon pages 5-8', 'pezzato2022influenceofsilicon pages 8-10', 'pezzato2022influenceofsilicon pages 10-13', 'pezzato2022influenceofsilicon pages 13-15', 'pezzato2022influenceofsilicon pages 15-16', 'pezzato2022influenceofsilicon pages 16-17', 'pezzato2022influenceofsilicon pages 17-17'\n\nBibTex:\n@article{pezzato2022influenceofsilicon,\n    author = \"Pezzato, L. and Gennari, C. and Franceschi, M. and Brunelli, K.\",\n    title = \"Influence of silicon morphology on direct current plasma electrolytic oxidation process in AlSi10Mg alloy produced with laser powder bed fusion\",\n    year = \"2022\",\n    journal = \"Scientific Reports\",\n    volume = \"12\",\n    month = \"Aug\",\n    doi = \"10.1038/s41598-022-18176-x\",\n    url = \"https://doi.org/10.1038/s41598-022-18176-x\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"1\",\n    issn = \"2045-2322\"\n}\n\n\nAbstract:\nIn this work, plasma electrolytic oxidation (PEO) process was applied on AlSi10Mg samples, produced with laser powder bed fusion (L-PBF), in the as printed condition and after different heat treatments, and, for comparison, on as-cast samples of AlSi10Mg. PEO process was performed in direct-current mode using high current densities and short time in a basic silicate electrolyte. For the first time, the effects of silicon morphology in L-PBF AlSi10Mg samples, in as printed condition and after different heat treatments, on the obtained PEO coating were investigated in terms of microstructure and corrosion properties. The microstructure of the substrate was characterized with optical and electron microscopy observations (optical microscopy OM, scanning electron microscopy SEM, and transmission electron microscopy TEM) and with X-ray diffraction (XRD). The analysis showed that heat treatments of annealing and solution treating modified the morphology and distribution of silicon in the samples obtained through L-PBF. The PEO coated samples were characterized with SEM, both on the surface and in the cross-section, and compositional analysis were performed with energy dispersive spectroscopy (EDS) analysis and elemental mapping. The coatings were also analyzed with XRD and the corrosion properties evaluated through electrochemical impedance spectroscopy (EIS) tests. Also microhardness tests were performed on the substrates and on the coatings. The microstructure of the coatings was strongly influenced by the silicon distribution. In particular, a non-uniform distribution of silicon and the presence of iron-rich intermetallic (obtained in the as-cast and solution treated samples) induced the formation of more porous and thinner coatings in comparison with the ones obtained in the as printed and annealed samples. The not-uniform silicon distribution produced a not-homogenous distribution of silicon into the coatings. The particular cellular structure of the as printed sample induced the formation of a coating with a higher amorphous fraction, in comparison with the ones produced on the other samples. The higher thickness and lower porosity of the coatings obtained on the annealed and as printed samples resulted in an increase of the corrosion resistance.\n\nRelevant Snippet:\n\u2026 coated samples were analyzed by SEM\u2013EDS to evaluate the \u2026 Analysis of PEO coatings. PEO coatings were produced \u2026 prepared by laser powder bed fusion additive manufacturing and \u2026\n\n\n---\n\n## 2. Gold, Silver, and Electrum Electroless Plating on Additively Manufactured Laser Powder-Bed Fusion AlSi10Mg Parts: A Review\nValid Text Names:\n'ashkenazi2021goldsilverand pages 1-2', 'ashkenazi2021goldsilverand pages 2-3', 'ashkenazi2021goldsilverand pages 3-6', 'ashkenazi2021goldsilverand pages 6-8', 'ashkenazi2021goldsilverand pages 8-10', 'ashkenazi2021goldsilverand pages 10-13', 'ashkenazi2021goldsilverand pages 13-17', 'ashkenazi2021goldsilverand pages 17-21', 'ashkenazi2021goldsilverand pages 21-23', 'ashkenazi2021goldsilverand pages 23-25', 'ashkenazi2021goldsilverand pages 25-26', 'ashkenazi2021goldsilverand pages 26-28'\n\nBibTex:\n@article{ashkenazi2021goldsilverand,\n    author = \"Ashkenazi, Dana and Inberg, Alexandra and Shacham-Diamand, Yosi and Stern, Adin\",\n    title = \"Gold, Silver, and Electrum Electroless Plating on Additively Manufactured Laser Powder-Bed Fusion AlSi10Mg Parts: A Review\",\n    year = \"2021\",\n    journal = \"THE Coatings\",\n    volume = \"11\",\n    pages = \"422\",\n    month = \"Apr\",\n    doi = \"10.3390/coatings11040422\",\n    url = \"https://doi.org/10.3390/coatings11040422\",\n    publisher = \"MDPI AG\",\n    issue = \"4\",\n    issn = \"2079-6412\"\n}\n\n\nAbstract:\nAdditive manufacturing (AM) revolutionary technologies open new opportunities and challenges. They allow low-cost manufacturing of parts with complex geometries and short time-to-market of products that can be exclusively customized. Additive manufactured parts often need post-printing surface modification. This study aims to review novel environmental-friendly surface finishing process of 3D-printed AlSi10Mg parts by electroless deposition of gold, silver, and gold\u2013silver alloy (e.g., electrum) and to propose a full process methodology suitable for effective metallization. This deposition technique is simple and low cost method, allowing the metallization of both conductive and insulating materials. The AlSi10Mg parts were produced by the additive manufacturing laser powder bed fusion (AM-LPBF) process. Gold, silver, and their alloys were chosen as coatings due to their esthetic appearance, good corrosion resistance, and excellent electrical and thermal conductivity. The metals were deposited on 3D-printed disk-shaped specimens at 80 and 90 \u00b0C using a dedicated surface activation method where special functionalization of the printed AlSi10Mg was performed to assure a uniform catalytic surface yielding a good adhesion of the deposited metal to the substrate. Various methods were used to examine the coating quality, including light microscopy, optical profilometry, XRD, X-ray fluorescence, SEM\u2013energy-dispersive spectroscopy (EDS), focused ion beam (FIB)-SEM, and XPS analyses. The results indicate that the developed coatings yield satisfactory quality, and the suggested surface finishing process can be used for many AM products and applications.\n\nRelevant Snippet:\n\u2026 Additive manufacturing has been used for various materials, \u2026 SEM-EDS analysis revealed that the AlSi10Mg disk-shaped \u2026 and the chemical composition of the AlSi10Mg powder. Next, \u2026\n\n\n---\n\n## 3. Effect of Build Orientation and Heat Treatment on Erosion Behavior of Al10SiMg Fabricated Using Laser Powder Bed Fusion\nValid Text Names:\n'angolkar2023effectofbuild pages 1-2', 'angolkar2023effectofbuild pages 2-4', 'angolkar2023effectofbuild pages 4-6', 'angolkar2023effectofbuild pages 6-7', 'angolkar2023effectofbuild pages 7-9', 'angolkar2023effectofbuild pages 9-11', 'angolkar2023effectofbuild pages 11-14', 'angolkar2023effectofbuild pages 14-16', 'angolkar2023effectofbuild pages 16-17', 'angolkar2023effectofbuild pages 17-18', 'angolkar2023effectofbuild pages 18-18'\n\nBibTex:\n@article{angolkar2023effectofbuild,\n    author = \"Angolkar, Pooja and Hussain, M. Manzoor\",\n    title = \"Effect of Build Orientation and Heat Treatment on Erosion Behavior of Al10SiMg Fabricated Using Laser Powder Bed Fusion\",\n    year = \"2023\",\n    journal = \"Tribology in Industry\",\n    volume = \"45\",\n    pages = \"561-578\",\n    month = \"Dec\",\n    doi = \"10.24874/ti.1470.04.23.06\",\n    url = \"https://doi.org/10.24874/ti.1470.04.23.06\",\n    publisher = \"Faculty of Engineering, University of Kragujevac\",\n    issue = \"4\",\n    issn = \"0354-8996\"\n}\n\n\nAbstract:\nLaser Powder Bed Fusion (LPBF) is a form of additive manufacturing that can directly make metal components and has begun to be employed in a variety of industrial situations. Moreover, the erosion characteristics of SLM-produced items have been documented relatively infrequently. In the current work, the erosion behavior of a heat-treated Al-Si-10% Mg alloy generated via laser powder bed fusion (LPBF) has been investigated. The samples were printed in three directions (horizontal (0o), vertical (90o), and inclined (45o) on the build platform using the Direct Metal Laser Sintering (DMLS) system (EOS M 290) machine. Al%Si-10%Mg samples were given treatment (T5, T6). Optical and scanning electron microscopes (SEM) were used to examine the microstructure under both printed and heat-treated conditions. Energy Dispersive Spectroscopy (EDS) and X-ray Diffraction (XRD) were used to investigate the alloy's elemental composition and compound production. The erosion test was executed in each of the three orientations, plus heat-treated samples and as-printed samples. The selected input parameters were impingement angle and flow velocity. The erosion rate was examined and contrasted across orientations for printed and heat-treated conditions to establish the best orientation. The post-eroded surface was analysed using SEM, EDS, and XRD to evaluate possible erosion processes. The key findings were: T5 heat-treated samples sustain well and have the least mass loss; Horizontal (0\u00b0) oriented samples undergo less erosion compared to other orientations; T6 heat-treated samples show maximum erosion on printed samples, and hence it is not recommended. T5 heat treatment is proven to be superior in providing high erosion resistance, followed by printed and T6 heat-treatment, respectively. The heat treatment effects are more significant than the orientation effects in determining the erosion resistance of the Al10SiMg alloy. The erosion mechanisms, such as ploughing, melting, and cratering, were identified.\n\nRelevant Snippet:\n\u2026 of the most popular commercial additive manufacturing (AM) processes is laser Powder Bed \u2026 and analysis are necessary to precisely characterise the erosion behaviour of AlSi10Mg \u2026\n\n\n---\n\n## 4. Manufacturability and microstructure of AlSi10Mg/SiC composites with different volume fractions of SiC using laser powder bed fusion\nValid Text Names:\n'conzelmann2026manufacturabilityandmicrostructure pages 1-2', 'conzelmann2026manufacturabilityandmicrostructure pages 2-4', 'conzelmann2026manufacturabilityandmicrostructure pages 4-6', 'conzelmann2026manufacturabilityandmicrostructure pages 6-9', 'conzelmann2026manufacturabilityandmicrostructure pages 9-12', 'conzelmann2026manufacturabilityandmicrostructure pages 12-13', 'conzelmann2026manufacturabilityandmicrostructure pages 13-14', 'conzelmann2026manufacturabilityandmicrostructure pages 14-15', 'conzelmann2026manufacturabilityandmicrostructure pages 15-15'\n\nBibTex:\n@article{conzelmann2026manufacturabilityandmicrostructure,\n    author = \"Conzelmann, Achim and Seifert, Hans J\u00fcrgen and Mozaffari-Jovein, Hadi\",\n    title = \"Manufacturability and microstructure of AlSi10Mg/SiC composites with different volume fractions of SiC using laser powder bed fusion\",\n    year = \"2026\",\n    journal = \"The International Journal of Advanced Manufacturing Technology\",\n    volume = \"142\",\n    pages = \"2215-2229\",\n    month = \"Dec\",\n    doi = \"10.1007/s00170-025-17075-5\",\n    url = \"https://doi.org/10.1007/s00170-025-17075-5\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"5-6\",\n    issn = \"0268-3768\"\n}\n\n\nAbstract:\n<jats:title>Abstract</jats:title>\n                  <jats:p>\n                    In the present study commercially available AlSi10Mg and SiC powders were mixed in a tumble mixer with resulting compositions of 5, 15 and 25 vol% SiC and processed using laser powder bed fusion. Different process parameters were used to manufacture samples which were characterized by various properties, such as porosity, microstructure and occurring phases to evaluate the manufacturability of the powder mixtures. The samples showed increasing porosity with lowered volumetric energy density and increasing SiC content. Relative densities of about 93.0% (25 vol% SiC), 94.5% (15 vol% SiC) and 98.5% (5 vol% SiC) respectively could be achieved. In addition, the correlation between the used energy density and the retained SiC particles in the samples was investigated. The quantity of retained SiC particles correlates negatively with the achievable density for all compositions, making compromises between these two properties necessary depending on the desired application. It is shown that SiC can get dissolved due to the high absorption of the laser energy resulting in the formation of primary silicon crystals as well as Al\n                    <jats:sub>4</jats:sub>\n                    C\n                    <jats:sub>3</jats:sub>\n                    and Al\n                    <jats:sub>4</jats:sub>\n                    SiC\n                    <jats:sub>4</jats:sub>\n                    phases. Microstructure characterizations using AFM revealed the influence of the SiC fraction on the eutectic structure and the formation of the new phases. Finally, EDS and TOF-SIMS analysis showed that the formed Al\n                    <jats:sub>4</jats:sub>\n                    C\n                    <jats:sub>3</jats:sub>\n                    phase can react with the humidity of ambient air at the surface, leading to localized cracks due to AlOOH formation.\n                  </jats:p>\n\nRelevant Snippet:\n\u2026 available AlSi10Mg and SiC powders were mixed in a tumble mixer with resulting compositions \u2026 Further analysis of the laser interaction with SiC particles was conducted using pure SiC \u2026\n\n\nUnobtainable Papers:\nIndrajeet Katti, Duyao Zhang, Dong Qiu, Matthias Weiss, Joy H. Forsmark, and Mark Easton. The effect of the iso\u2010thermal heat treatment on the microstructure and properties of powder bed fusion\u2013laser beam alsi10mg alloy. Advanced Engineering Materials, May 2024. URL: https://doi.org/10.1002/adem.202400202, doi:10.1002/adem.202400202.\nIbrahim H. ZainElabdeen, Rehan Umer, Wesley J. Cantwell, James Weston, and Kamran A. Khan. Microstructure and elevated temperature mechanical properties of bimetal part fabricated by laser powder bed fusion of alsi10mg on rolled aa6061-t651. Aug 2025. URL: https://doi.org/10.1016/j.matdes.2025.114327, doi:10.1016/j.matdes.2025.114327.\nRabia Urkun and Dil\u015fad Akg\u00fcm\u00fc\u015f G\u00f6k. Alsi10mg honeycomb lattices produced by laser powder bed fusion: mechanical, thermal, and microstructural performances. Journal of Sandwich Structures &amp; Materials, Jun 2025. URL: https://doi.org/10.1177/10996362251355388, doi:10.1177/10996362251355388.\nG. Di Egidio, C. Martini, J. B\u00f6rjesson, E. Ghassemali, L. Ceschini, and A. Morri. Dry sliding behavior of alsi10mg alloy produced by laser-based powder bed fusion: influence of heat treatment and microstructure. Mar 2023. URL: https://doi.org/10.1016/j.wear.2022.204602, doi:10.1016/j.wear.2022.204602.\nElisa Padovano, Claudio Badini, Anna Pantarelli, Flavia Gili, and Fabio D\u2019Aiuto. A comparative study of the effects of thermal treatments on alsi10mg produced by laser powder bed fusion. Journal of Alloys and Compounds, 831:154822, Aug 2020. URL: https://doi.org/10.1016/j.jallcom.2020.154822, doi:10.1016/j.jallcom.2020.154822.\nPeidong He, Richard F. Webster, Jamie J. Kruzic, and Xiaopeng Li. Microstructural evolution and mechanical properties of co-modified alsi10mg alloy fabricated via in-situ alloying in laser powder bed fusion. Materials &amp; Design, 268:116580, Aug 2026. URL: https://doi.org/10.1016/j.matdes.2026.116580, doi:10.1016/j.matdes.2026.116580.\nJiyuan Zhang, Yong Yang, Qiuju Zheng, Shiwei Wu, Wenhou Wei, and Shoufeng Yang. Effect of nitrogen concentration on microstructure and mechanical properties of alsi10mg matrix composites fabricated by laser powder bed fusion. Virtual and Physical Prototyping, Jan 2026. URL: https://doi.org/10.1080/17452759.2025.2609346, doi:10.1080/17452759.2025.2609346.\nM. Srinivas, D. Pandey, TS Prasad, S. Purushothaman, and M. Sankar. Comparative tribological studies of additive manufactured as-built and chemically polished alsi10mg alloy surfaces. Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology, 239:789-806, Aug 2025. URL: https://doi.org/10.1177/13506501241276243, doi:10.1177/13506501241276243.\nHan Liu, Minheng Ye, Zuoyan Ye, Lili Wang, Guowei Wang, Xianfeng Shen, Ping Xu, and Chao Wang. High-quality surface smoothening of laser powder bed fusion additive manufacturing alsi10mg via intermittent electrochemical polishing. Aug 2022. URL: https://doi.org/10.1016/j.surfcoat.2022.128608, doi:10.1016/j.surfcoat.2022.128608.\nJunchao Yi, Xiaowei Zhang, Guozheng Liu, Jeremy Heng Rao, and Han Liu. Microstructure and dynamic microhardness of additively manufactured (tib2+tic)/alsi10mg composites with alsi10mg and b4c coated ti powder. Journal of Alloys and Compounds, 939:168718, Apr 2023. URL: https://doi.org/10.1016/j.jallcom.2023.168718, doi:10.1016/j.jallcom.2023.168718.\nZhen Zhang, Zhanyong Zhao, Xiaofeng Li, Beibei Wang, and Peikang Bai. Effect of direct aging on corrosion behavior of alsi10mg alloy fabricated by laser powder bed fusion. Acta Metallurgica Sinica (English Letters), 37:266-282, Nov 2024. URL: https://doi.org/10.1007/s40195-023-01628-2, doi:10.1007/s40195-023-01628-2.\nAmir Hadadzadeh, Babak Shalchi Amirkhiz, Sajad Shakerin, Josh Kelly, Jian Li, and Mohsen Mohammadi. Microstructural investigation and mechanical behavior of a two-material component fabricated through selective laser melting of alsi10mg on an al-cu-ni-fe-mg cast alloy substrate. Additive Manufacturing, 31:100937, Jan 2020. URL: https://doi.org/10.1016/j.addma.2019.100937, doi:10.1016/j.addma.2019.100937.\nNancy Huang, Qixiang Luo, Dean L. Bartles, Timothy W. Simpson, and Allison M. Beese. Effect of heat treatment on microstructure and mechanical properties of alsi10mg fabricated using laser powder bed fusion. Mar 2024. URL: https://doi.org/10.1016/j.msea.2024.146228, doi:10.1016/j.msea.2024.146228.\nL. Pezzato, M. Dabal\u00e0, Silvia Gross, and K. Brunelli. Effect of microstructure and porosity of alsi10mg alloy produced by selective laser melting on the corrosion properties of plasma electrolytic oxidation coatings. Surface & Coatings Technology, 404:126477, Dec 2020. URL: https://doi.org/10.1016/j.surfcoat.2020.126477, doi:10.1016/j.surfcoat.2020.126477.\nT. M. Nandakishor, T. Stoll, and E.A. J\u00e4gle. Coupled thermodynamic and microstructural mechanisms governing interfacial cracking in hybrid pbf-lb/m of alsi10mg onto aa2017 substrate. Jul 2026. URL: https://doi.org/10.1016/j.matchar.2026.116502, doi:10.1016/j.matchar.2026.116502.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=19 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000000\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 11-13'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt lists the metadata and requirements that must accompany EDS standard spectra for rigorous k-ratio quantification. Standard spectra must be measured and archived with known, reproducible beam energy and electron dose (beam current \u00d7 detector live time), and with documented EDS operating conditions (time constant/resolution, detector-to-specimen distance and detector active area/solid angle, detector take-off and azimuthal angles, and specimen tilt\u2014preferably zero). A calibrated beam-current measurement (Faraday cup + digital picoammeter) is required for a fully rigorous protocol, and a conservative beam current that yields roughly 10% detector deadtime is recommended to minimize pulse coincidence. Sample and standard surface condition must be controlled: highly polished, not chemically etched, and for low-energy lines surface roughness should be <50 nm rms. Standards may be co-mounted or prepared on separate mounts; they must have accurately known composition and be homogeneous at the micrometer scale. Finally, archived standard spectra can be reused only if a quality-assurance check confirms the unknown was measured under the same documented conditions (beam energy, dose, and EDS parameters), and high-count, stable peak-shape spectra are needed for robust peak fitting (MLLS) in severe overlap situations.\n\n\n---\n\n## pqac-00000001\n\nFrom text 'tong2026measurementuncertaintiesof pages 21-24'.\n\nV. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.\n\nThe excerpt lists the experimental requirements and metadata that should accompany an EDS standard spectrum used for k-ratio (standards-based) quantification. Key metadata/requirements include: identity and composition of the standard (single pure-element standard for each element; chemically similar standards where possible), flat polished sample/standard surface and homogeneity through the interaction volume, SEM accelerating voltage (electron energy \u2265 1.8 \u00d7 the X\u2011ray peak energy for elements of interest), sample orientation (surface normal to beam and ~35\u00b0 to the EDX detector), energy-scale calibration details (e.g., per ISO 22309:2011 using Al and Cu standards), beam current and detector-geometry calibration (e.g., \u2018Quant Optimisation\u2019 in Aztec), and a stable electron beam current. Also important are factory-supplied matrix correction data from comparable elemental standards and acquiring standards under the same experimental session to cancel dependence on beam current, geometry and chamber contamination. The excerpt does not contain the text of Goldstein et al. or their explicit checklist, so requirements specifically attributed to Goldstein et al. are not present here.\n\n\n---\n\n## pqac-00000002\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 2-4'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt specifies the experimental metadata that must accompany EDS standards used for k\u2011ratio/matrix quantification: the specimen surface condition (highly polished; avoid chemical etching because it produces topography that alters X\u2011ray intensities), the beam energy, the known dose (beam current and detector live time), the beam incidence angle, the detector elevation or \"take\u2011off\" angle, and detector efficiency (e.g., constant detector\u2011to\u2011target distance to keep solid angle constant). It also emphasizes that standards should be archived and recalled as needed (stability of EDS), and that certified reference materials (e.g., NIST SRMs) and materials confirmed to be homogeneous on the micrometer scale are appropriate standards. The excerpt does not present a separate, explicit list attributed to Goldstein et al.; the listed metadata and standard requirements above are those provided in this text.\n\n\n---\n\n## pqac-00000003\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 2-3'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe provided excerpt does not give an explicit checklist of metadata that must accompany an EDS standard spectrum for k\u2011ratio quantification, but it does cite key requirements for standards (Goldstein et al., 1975) used in a standards\u2011based k\u2011ratio protocol with matrix corrections. Those requirements include: (1) the standard's overall (bulk) composition must be measured by independent methods; (2) microscopic homogeneity must be established (by EPMA in the cited work); and (3) when pure elements are incompatible with vacuum or suffer electron\u2011beam damage, stoichiometric compounds (e.g., CaF2, GaP, FeS2 for S) are used instead. The text defines the \u201ctrue value\u201d as the concentration known from independent analysis and uses the relative deviation (RDEV) from expected values as the figure of merit for EPMA results. While instrument/measurement metadata (beam energy, detector type, acquisition conditions) are discussed elsewhere in the paper (e.g., analytical beam energy choices), the excerpt itself does not enumerate a formal metadata package that must accompany an EDS standard spectrum for k\u2011ratio quantification.\n\n\n---\n\n## pqac-00000004\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 9-11'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt documents examples of k-ratio protocol use and gives several experimental/metadata items shown alongside EDS standard spectra. Example spectra and k-ratio analysis were collected at a specified beam energy (E0 = 20 keV) using SDD-EDS (a four-detector array) with measured deadtime varying from 2% to 77%. The text emphasizes detector-related metadata (detector type: SDD-EDS; operating temperature ~-20 \u00b0C) and demonstrates that peak shapes and calibration remain stable over large input count rate ranges, which is important for reliable k-ratio fitting. For non-conductive standards and unknowns, the excerpt states a specimen must be coated and grounded, recommending a carbon coating 8\u201310 nm thick, and warns that differences in coating thickness between unknown and standards can introduce significant error (especially at low beam energies). The excerpt refers to Table 5 for k-ratio protocol analysis but does not reproduce a complete checklist of metadata or the requirements from Goldstein et al.; those Goldstein-specific requirements are not present on these pages.\n\n\n---\n\n## pqac-00000005\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 1-2'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt explains the k-ratio quantification principle: k = Iunknown/Istandard, where the characteristic X-ray peak intensity must be measured under identical conditions (\"measured under identical conditions of beam energy, known dose, and detector efficiency for both\") so detector efficiency and other instrumental factors cancel. It also states that standards need not closely match unknown composition and gives acceptable standard types: pure elements and stoichiometric compounds for elements that are gaseous in vacuum, highly reactive, beam-sensitive, or low melting (examples: MgO for O; KCl for K and Cl; FeS2 for S; GaP for Ga and P). The conversion from k-ratios to concentrations uses matrix correction factors Ci/Cstd = k i Z A F c, with Z, A, F, and c defined as corrections for electron scattering/energy loss, X-ray self-absorption, and secondary X-ray emission/continuum. The excerpt does not provide a detailed checklist of metadata fields that must accompany an EDS standard spectrum nor the explicit Goldstein et al. requirements; it provides only these operational and standard-selection points relevant to k-ratio measurement.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=19 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. SEM-EDS nanoanalysis of mineral composite materials: A Monte Carlo approach\nValid Text Names:\n'moro2021semedsnanoanalysisof pages 1-6', 'moro2021semedsnanoanalysisof pages 6-9', 'moro2021semedsnanoanalysisof pages 9-13', 'moro2021semedsnanoanalysisof pages 13-18', 'moro2021semedsnanoanalysisof pages 18-24', 'moro2021semedsnanoanalysisof pages 24-27', 'moro2021semedsnanoanalysisof pages 27-27'\n\nBibTex:\n@misc{moro2021semedsnanoanalysisof,\n    author = \"Moro, Daniele and Ulian, Gianfranco and Valdr\u00e8, Giovanni\",\n    title = \"SEM-EDS nanoanalysis of mineral composite materials: A Monte Carlo approach\",\n    year = \"2021\",\n    journal = \"Composite Structures\",\n    volume = \"259\",\n    pages = \"113227\",\n    month = \"Mar\",\n    doi = \"10.1016/j.compstruct.2020.113227\",\n    url = \"https://doi.org/10.1016/j.compstruct.2020.113227\",\n    publisher = \"Elsevier BV\",\n    issn = \"0263-8223\"\n}\n\n\nRelevant Snippet:\n\u2026 and Berger\u2019s tabulated partial and total cross-sections for \u2026 to-detector distance was set to 45 mm, the detector elevation \u2026 , because of the excitation of silicon belonging to the quartz matrix\u2026\n\n\nUnobtainable Papers:\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Dtsa-ii eds software. ArXiv, pages 235-264, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_17, doi:10.1007/978-1-4939-6676-9\\_17.\nDaniele Moro, Gianfranco Ulian, and Giovanni Valdr\u00e8. Fibre-reinforced geopolymer composites micro-nanochemistry by sem-eds simulations. Journal of Composites Science, 5:214, Aug 2021. URL: https://doi.org/10.3390/jcs5080214, doi:10.3390/jcs5080214.\nAdrien Teurtrie, Nathana\u00ebl Perraudin, Thomas Holvoet, Hui Chen, Duncan T.L. Alexander, Guillaume Obozinski, and C\u00e9cile H\u00e9bert. Espm: a python library for the simulation of stem-edxs datasets. Ultramicroscopy, 249:113719, Mar 2023. URL: https://doi.org/10.1016/j.ultramic.2023.113719, doi:10.1016/j.ultramic.2023.113719.\nMathias Procop and Ralf Terborg. Measurement and calculation of x-ray production efficiencies for copper, zirconium, and tungsten. Dec 2022. URL: https://doi.org/10.1017/s1431927622012351, doi:10.1017/s1431927622012351.\nNicholas W.M. Ritchie, Dale E. Newbury, and Abigail P. Lindstrom. Compton scattering artifacts in electron excited x-ray spectra measured with a silicon drift detector. Microscopy and Microanalysis, 17:903-910, Nov 2011. URL: https://doi.org/10.1017/s1431927611012189, doi:10.1017/s1431927611012189.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=20 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=19 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                      "arguments": "{\"query\": \"Newbury Ritchie low beam energy 5 keV EDS quantification accuracy light elements\"}",
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+                    "id": "toolu_0149CeGrCA7aqnBbiWjDaKmk",
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+                      "arguments": "{\"query\": \"NIST DTSA-II simulated spectrum detector response model accuracy comparison measured spectrum\"}",
+                      "name": "paper_search"
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+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Exploring the limits of EDS microanalysis: rare earth element analyses\nValid Text Names:\n'ritchie2018exploringthelimits pages 1-4', 'ritchie2018exploringthelimits pages 4-5', 'ritchie2018exploringthelimits pages 5-7', 'ritchie2018exploringthelimits pages 7-9', 'ritchie2018exploringthelimits pages 9-11', 'ritchie2018exploringthelimits pages 11-11'\n\nBibTex:\n@article{ritchie2018exploringthelimits,\n    author = \"Ritchie, N W M and Newbury, D E and Lowers, H and Mengason, M\",\n    title = \"Exploring the limits of EDS microanalysis: rare earth element analyses\",\n    year = \"2018\",\n    journal = \"IOP Conference Series: Materials Science and Engineering\",\n    volume = \"304\",\n    pages = \"012013\",\n    month = \"Aug\",\n    doi = \"10.1088/1757-899x/304/1/012013\",\n    url = \"https://doi.org/10.1088/1757-899x/304/1/012013\",\n    publisher = \"IOP Publishing\",\n    issn = \"1757-8981\"\n}\n\n\nAbstract:\nIt is a great time to be a microanalyst. After a few decades of incremental progress in energy-dispersive X-ray spectrometry (EDS), the last decade has seen the accuracy and precision surge forward. Today, the question is not whether EDS is generally useful but to identify the types of problems for which wavelength-dispersive X-ray spectrometry remains the better choice. The full extent of EDS\u2019s capabilities has surprised many. Low Z, low energy, and trace element detection have been demonstrated even in the presence of extreme peak interferences. In this paper, we will summarise the state-of-the-art and investigate a challenging problem domain, the analysis of minerals bearing multiple rare-earth elements.\n\nRelevant Snippet:\n\u2026 like major element interferences, light elements, trace elements, and low beam energy \u2026 both the 1 keV to 2.5 keV range and the 5 keV to 10 keV range suggests that all significant \u2026\n\n\n---\n\n## 2. Comprehensive Quantitative Elemental Microanalysis with Electron-Excited Energy Dispersive X-ray Spectrometry (EDS): 50 Years Young and Getting Better Every Day!\nValid Text Names:\n'newbury2018comprehensivequantitativeelemental pages 1-2'\n\nBibTex:\n@article{newbury2018comprehensivequantitativeelemental,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Comprehensive Quantitative Elemental Microanalysis with Electron-Excited Energy Dispersive X-ray Spectrometry (EDS): 50 Years Young and Getting Better Every Day!\",\n    year = \"2018\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"24\",\n    pages = \"712-713\",\n    month = \"Aug\",\n    doi = \"10.1017/s1431927618004051\",\n    url = \"https://doi.org/10.1017/s1431927618004051\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"S1\",\n    issn = \"1431-9276\"\n}\n\n\nRelevant Snippet:\n\u2026 that EDS requires a factor of 10 to 250 lower dose (beam \u2026 the same count precision, depending on the photon energy being \u2026 Low beam energy microanalysis (1 keV \u2264 E0 \u2264 5 keV) \u2026\n\n\n---\n\n## 3. Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\nValid Text Names:\n'goldstein2018energydispersivexray pages 1-2', 'goldstein2018energydispersivexray pages 2-4', 'goldstein2018energydispersivexray pages 4-6', 'goldstein2018energydispersivexray pages 6-7', 'goldstein2018energydispersivexray pages 7-9', 'goldstein2018energydispersivexray pages 9-10', 'goldstein2018energydispersivexray pages 10-11', 'goldstein2018energydispersivexray pages 11-14', 'goldstein2018energydispersivexray pages 14-15', 'goldstein2018energydispersivexray pages 15-16', 'goldstein2018energydispersivexray pages 16-18', 'goldstein2018energydispersivexray pages 18-20', 'goldstein2018energydispersivexray pages 20-22', 'goldstein2018energydispersivexray pages 22-25', 'goldstein2018energydispersivexray pages 25-26'\n\nBibTex:\n@article{goldstein2018energydispersivexray,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"209-234\",\n    doi = \"10.1007/978-1-4939-6676-9\\_16\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_16\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nAs illustrated in Fig. 16.1, the physical basis of energy dispersive X-ray spectrometry (EDS) with a semiconductor detector begins with photoelectric absorption of an X-ray photon in the active volume of the semiconductor (Si). The entire energy of the photon is transferred to a bound inner shell atomic electron, which is ejected with kinetic energy equal to the photon energy minus the shell ionization energy (binding energy), 1.838 keV for the Si K-shell and 0.098 keV for the Si L-shell. The ejected photoelectron undergoes inelastic scattering within the Si crystal. One of the consequences of the energy loss is the promotion of bound outer shell valence electrons to the conduction band of the semiconductor, leaving behind positively charged \u201choles\u201d in the valence band. In the conduction band, the free electrons can move in response to a potential applied between the entrance surface electrode and the back surface electrode across the thickness of the Si crystal, while the positive holes in the conduction band drift in the opposite direction, resulting in the collection of electrons at the anode on the back surface of the EDS detector. This charge generation process requires approximately 3.6 eV per electron hole pair, so that the number of charge carriers is proportional to the original photon energy, Ep: \n \n$$ n={E}_p/3.6\\ eV $$ \n \nFor a Mn K-L3 photon with an energy of 5.895 keV, approximately 1638 electron\u2013hole pairs are created, comprising a charge of 2.6 \u00d7 10\u221216 coulombs. Because the detector can respond to any photon energy from a threshold of approximately 50 eV to 30 keV or more, the process has been named \u201cenergy dispersive,\u201d although in the spectrometry sense there is no actual dispersion such as occurs in a diffraction element spectrometer.\n\nRelevant Snippet:\n\u2026 energy of 1.559 keV, a modest beam energy of 15 keV provides \u2026 and as a result the precision of quantitative analysis is also \u2026 of microparticles, low beam energy analysis, or another \u2026\n\n\nUnobtainable Papers:\nK. SCOTT and N.W.M. RITCHIE. Analysis of 3d elemental mapping artefacts in biological specimens using monte carlo simulation. Journal of Microscopy, 233:331-339, Feb 2009. URL: https://doi.org/10.1111/j.1365-2818.2009.03124.x, doi:10.1111/j.1365-2818.2009.03124.x.\nDale E. Newbury and Nicholas W. M. Ritchie. Quantitative x-ray microanalysis of low atomic number elements by sem/sdd-eds with nist dtsa ii: carbides and nitrides and oxides, oh my! Microscopy and Microanalysis, 20:702-703, Aug 2014. URL: https://doi.org/10.1017/s1431927614005236, doi:10.1017/s1431927614005236.\nPhilippe T Pinard, Simon Burgess, John Qing Zhang, and Peter J Statham. Characterization and customization of individual eds detectors to improve x-ray microanalysis of light elements. Microscopy and Microanalysis, Jul 2024. URL: https://doi.org/10.1093/mam/ozae044.096, doi:10.1093/mam/ozae044.096.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=25 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Harnessing Automated SEM-EDS and Machine Learning to Unlock High-Throughput Compositional Characterization of Powder Materials\nValid Text Names:\n'giunto2025harnessingautomatedsemeds pages 1-4', 'giunto2025harnessingautomatedsemeds pages 4-6', 'giunto2025harnessingautomatedsemeds pages 6-7', 'giunto2025harnessingautomatedsemeds pages 7-10', 'giunto2025harnessingautomatedsemeds pages 10-12', 'giunto2025harnessingautomatedsemeds pages 12-14', 'giunto2025harnessingautomatedsemeds pages 14-16', 'giunto2025harnessingautomatedsemeds pages 16-18', 'giunto2025harnessingautomatedsemeds pages 18-20', 'giunto2025harnessingautomatedsemeds pages 20-22', 'giunto2025harnessingautomatedsemeds pages 22-23', 'giunto2025harnessingautomatedsemeds pages 23-25', 'giunto2025harnessingautomatedsemeds pages 25-28', 'giunto2025harnessingautomatedsemeds pages 28-29', 'giunto2025harnessingautomatedsemeds pages 29-32', 'giunto2025harnessingautomatedsemeds pages 32-36', 'giunto2025harnessingautomatedsemeds pages 36-37'\n\nBibTex:\n@article{giunto2025harnessingautomatedsemeds,\n    author = \"Giunto, Andrea and Fei, Yuxing and Nevatia, Pragnay and Rendy, Bernardus and Szymanski, Nathan and Ceder, Gerbrand\",\n    title = \"Harnessing Automated SEM-EDS and Machine Learning to Unlock High-Throughput Compositional Characterization of Powder Materials\",\n    year = \"2025\",\n    journal = \"Unknown journal\",\n    month = \"Oct\",\n    doi = \"10.21203/rs.3.rs-7837297/v1\",\n    url = \"https://doi.org/10.21203/rs.3.rs-7837297/v1\",\n    publisher = \"Springer Science and Business Media LLC\"\n}\n\n\nAbstract:\n<title>Abstract</title>\n                <p>Compositional characterization is essential for understanding and optimizing material performance. For powder-based materials, ubiquitous across diverse technologies, accurately resolving the composition of individual phases at high throughput remains an unsolved challenge. This bottleneck slows material research and is particularly acute for autonomous laboratories, where large numbers of samples are synthesized and AI decision-making algorithms demand low-uncertainty data. Here, we integrate measurement automation, data filtering, and unsupervised machine learning to deliver a fully automated framework for high-throughput, phase-resolved compositional analysis of as-deposited powders using scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS). Our approach, implemented in the Python-based software AutoEMXSp, overcomes geometry-induced artifacts from irregular particle morphologies and enables accurate compositional quantification using only one experimental standard per element\u2014including light elements conventionally difficult to quantify in powders. Validated across 74 powder samples with elements spanning nitrogen to bismuth, AutoEMXSp consistently estimates compositions within 5\u201310% of their expected values and resolves minor or intermixed phases with high confidence. By delivering a robust, operator-free, high-throughput framework, this work paves the way for integration of powder compositional characterization into autonomous laboratory platforms, accelerating the pace of materials discovery and development.</p>\n\nRelevant Snippet:\n\u2026 -based EDS quantification with a single set of experimen- 57 \u2026 overestimation of continuum X-rays at low energies 117 (E < \u2026 for detector incomplete charge collection (ICC), peak shapes \u2026\n\n\nUnobtainable Papers:\nDavid B. Williams and C. Barry Carter. X-ray spectra and images. ArXiv, pages 605-623, Jan 2009. URL: https://doi.org/10.1007/978-0-387-76501-3\\_33, doi:10.1007/978-0-387-76501-3\\_33.\nPeter J Statham. Measuring performance of energy-dispersive x-ray systems. Microscopy and Microanalysis, 4:605-615, Dec 1998. URL: https://doi.org/10.1017/s1431927698980588, doi:10.1017/s1431927698980588.\nC. E. LYMAN, J. I. GOLDSTEIN, D. B. WILLIAMS, D. W. ACKLAND, S. VON HARRACH, A. W. NICHOLLS, and P. J. STATHAM. High\u2010performance x\u2010ray detection in a new analytical electron microscope. Journal of Microscopy, 176(2):85-98, Nov 1994. URL: https://doi.org/10.1111/j.1365-2818.1994.tb03503.x, doi:10.1111/j.1365-2818.1994.tb03503.x.\nLucia Spasevski, Simon Burgess, Philippe T Pinard, John Qing Zhang, and Katherine MacArthur. Advances in individual detector characterization and key parameters that affect modern eds performance. Microscopy and Microanalysis, Jul 2025. URL: https://doi.org/10.1093/mam/ozaf048.241, doi:10.1093/mam/ozaf048.241.\nDavid B. Williams and C. Barry Carter. X-ray Spectrometry, pages 581-603. Springer US, Jan 2009. URL: https://doi.org/10.1007/978-0-387-76501-3\\_32, doi:10.1007/978-0-387-76501-3\\_32.\nAT Ellis. Energy-dispersive x-ray fluorescence analysis using x-ray tube excitation. ArXiv, pages 212-251, Nov 2002. URL: https://doi.org/10.1201/9780203908709-3, doi:10.1201/9780203908709-3.\nLucia Spasevski, Simon Burgess, Philippe Pinard, John Qing Zhang, and Katherine MacArthur. Challenges in measuring low concentration of overlapping elements with eds and need for verification with standard materials. Jul 2026. URL: https://doi.org/10.1093/mam/ozaf048.260, doi:10.1093/mam/ozaf048.260.\nNicolas Brodusch, Karim Zaghib, and Raynald Gauvin. Improvement of the energy resolution of energy dispersive spectrometers (eds) using richardson\u2013lucy deconvolution. Ultramicroscopy, 209:112886, Feb 2020. URL: https://doi.org/10.1016/j.ultramic.2019.112886, doi:10.1016/j.ultramic.2019.112886.\nPeter J. Statham. Recent developments in instrumentation for x-ray microanalysis. ArXiv, pages 1-9, Jan 1998. URL: https://doi.org/10.1007/978-3-7091-7506-4\\_1, doi:10.1007/978-3-7091-7506-4\\_1.\nPeter J. Statham. Pile-up correction for improved accuracy and speed of x-ray analysis. Microchimica Acta, 155:289-294, Apr 2006. URL: https://doi.org/10.1007/s00604-006-0558-1, doi:10.1007/s00604-006-0558-1.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=25 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (SEM/EDS) quantitative? Effect of specimen shape\nValid Text Names:\n'newbury2011isscanningelectron pages 1-2', 'newbury2011isscanningelectron pages 2-3', 'newbury2011isscanningelectron pages 3-7', 'newbury2011isscanningelectron pages 7-10', 'newbury2011isscanningelectron pages 10-13', 'newbury2011isscanningelectron pages 13-16', 'newbury2011isscanningelectron pages 16-16'\n\nBibTex:\n@article{newbury2011isscanningelectron,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Is scanning electron microscopy/energy dispersive x-ray spectroscopy (SEM/EDS) quantitative? Effect of specimen shape\",\n    year = \"2011\",\n    journal = \"SPIE Proceedings\",\n    volume = \"8036\",\n    pages = \"803602\",\n    month = \"May\",\n    doi = \"10.1117/12.881040\",\n    url = \"https://doi.org/10.1117/12.881040\",\n    publisher = \"SPIE\",\n    issn = \"0277-786X\"\n}\n\n\nRelevant Snippet:\n\u2026 count spectra of unknowns and standards, the most accurate \u2026 solution is to simulate the bulk reference spectrum from an \u2026 tool such as NIST DTSAII which calculates the spectrum on a \u2026\n\n\nUnobtainable Papers:\nNicholas W. M. Ritchie. Manipulating spectra with dtsa-ii. Microscopy Today, 19:34-39, Apr 2011. URL: https://doi.org/10.1017/s1551929511000290, doi:10.1017/s1551929511000290.\nNicholas W. M. Ritchie. Getting started with nist* dtsa-ii. Microscopy Today, 19:26-31, Jan 2011. URL: https://doi.org/10.1017/s155192951000132x, doi:10.1017/s155192951000132x.\nDale E. Newbury and Nicholas W. M. Ritchie. Measurement of trace constituents by electron-excited x-ray microanalysis with energy-dispersive spectrometry. Microscopy and Microanalysis, 22:520-535, May 2016. URL: https://doi.org/10.1017/s1431927616000738, doi:10.1017/s1431927616000738.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=25 | Relevant Papers=3 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0386 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000006\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 20-21'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt shows DTSA-II simulated-standard analysis of NIST microanalysis glass K2496 (Table 11) producing concentrations very close to the as-synthesized values (example: 0.3230 vs 0.3197, 0.2291 vs 0.2256, 0.0180 vs 0.0176, 0.4299 vs 0.4371) with small relative errors (e.g., -1.0, -1.5, -2.4, 1.7 %) and small precision metrics (r relative (%) ~0.08\u20131.8 %). The authors emphasize an SDD-EDS measurement strategy (10 keV beam, deadtime \u224810 %, dose \u224810^7 counts) that yields high-count spectra and low detection limits; they recommend conservative counting to keep deadtime \u227210 % to avoid coincidence artifacts. The excerpt illustrates spectral interference issues (BaL\u03b1 vs TiK\u03b1 \u0394=41 eV; BaL\u03b23 vs TiK\u03b2 \u0394=4 eV) and shows that residual fitting can reveal low-level peaks masked by overlaps. Thus DTSA-II simulated spectra can give accurate quantification in well-controlled, high-count SDD-EDS measurements and can represent minor constituents within a few percent. The excerpt does not describe in detail how DTSA-II models detector effects such as incomplete charge collection, dead layer, or window transmission, nor does it fully enumerate failure modes beyond noted peak overlaps and deadtime/coincidence artifacts.\n\n\n---\n\n## pqac-00000007\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 11-13'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt shows that NIST DTSA-II, when used to process high-count, stable spectra and applied within a rigorous k-ratio protocol, can produce k-ratio determinations comparable to WDS and yield results within the EPMA/WDS error envelope (see Table 5 for sulfides at E0 = 20 keV). Achieving this performance requires strict measurement reproducibility: known beam energy, dose (electron current \u00d7 detector live time), fixed EDS parameters, and careful beam-current measurement (Faraday cup + picoammeter). A conservative operating strategy\u2014selecting beam current to give ~10% detector deadtime\u2014minimizes pulse coincidence, which becomes problematic above ~15% deadtime. High-count spectra with stable peak shape enable MLLS fitting to extract characteristic intensities even in severe peak overlap. The excerpt also notes practical failure modes for simulated/archived standards: standards must be homogeneous at the micrometer scale; sample surfaces must be highly polished (low topography, scratches < ~50 nm rms for low-energy X-rays); and at low beam energies (E0 \u2264 ~5 keV) differences in coating thickness between unknown and standards can introduce significant errors. The excerpt does not describe how DTSA-II models detector physics such as incomplete charge collection, detector dead layers, or window transmission.\n\n\n---\n\n## pqac-00000008\n\nFrom text 'newbury2011isscanningelectron pages 13-16'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\nThe excerpt states that NIST DTSA-II can be used to simulate a bulk reference EDS spectrum from an estimated composition using first-principles physics to yield absolute intensities. An example (bulk K411, E0 = 20 keV) compared measured and simulated spectra with no scaling; the summed characteristic peak plus background intensities differed by +1.2% (Fe K\u03b1) up to +19% (Mg K) in that case. The authors note that a simulated reference is useful when a flat, bulk reference of the same composition is unavailable, but requires an estimate of the composition (a first normalized analysis can serve as that estimate). The excerpt warns that anomalous absorption\u2014especially in the low-photon-energy region\u2014can cause large deviations from the ideal spectrum (notably for microscopic shards and irregular geometries), and that application of standard k-value/matrix corrections followed by normalization to such spectra can produce unacceptably large errors. The passage does not provide details on how DTSA-II implements detector-response effects such as incomplete charge collection, detector dead layer, or window transmission.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008]\n\nStatus: Paper Count=25 | Relevant Papers=4 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=9 | Current Cost=$0.0670 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000009\n\nFrom text 'tsuji2010xrayspectrometry. pages 9-10'.\n\nKouichi Tsuji, Kazuhiko Nakano, Yoshio Takahashi, Kouichi Hayashi, and Chul-Un Ro. X-ray spectrometry. Analytical chemistry, 82 12:4950-87, May 2010. URL: https://doi.org/10.1021/ac101069d, doi:10.1021/ac101069d. This article has 78 citations and is from a highest quality peer-reviewed journal.\n\nThe excerpt emphasizes that detailed, instrument-specific detector characterization is critical for FP-based XRF/EDS quantification. Key detector properties that must be known include absolute efficiency, energy resolution, and the precise shape of the detector response function. Scholze and Procop modelled EDS spectral response accounting for detector statistical and electronic noise, incomplete charge collection (which causes peak tailing), escape effects, and fluorescence from the front contact or dead layer\u2014all processes that alter peak shapes and continuum, particularly at low energies. An FP method that explicitly includes the energy-broadening response was used to predict peak-area ratios (KR fluorescence vs. scattered peaks), and the detector response curve was adjusted by matching theory to experiment. New SDDs with thin windows and improved electronics change throughput and low-energy sensitivity, and geometry/solid-angle differences further affect detected intensities. Taken together, these points indicate that uncorrected transfer of EDS standard spectra between different instruments/detectors is problematic unless detector-to-detector differences (resolution, window/dead layer absorption, incomplete charge collection, escape, response shape, and geometry) are modeled or empirically calibrated.\n\n\n---\n\n## pqac-00000010\n\nFrom text 'ritchie2018exploringthelimits pages 1-4'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nRelevant points from the excerpt for assessing transferability of EDS standard spectra and detector-to-detector effects on k-ratios (especially <2 keV): 1) EDS quantitation depends on integrating intensity over the same channel ranges on unknowns and standards: \"In the case of EDS, the intensity should be integrated over the same range of channels on the unknown and the standard.\" This implies standards and unknowns must be measured under consistent channel/binning and spectral-resolution conditions. 2) Detector physical differences matter: improvements and changes in \"dead layers trimmed,\" \"leakage currents\" and window materials affect low-energy X-ray transmission (\"These new window technologies permitted lower energy X-rays to reach the detector.\" and \"Some even, Li-K X-rays\"). 3) Resolution and peak shape affect peak integration and peak-to-background: \"Detector resolutions have improved.\"; \"The peak-to-background ratio on an EDS is determined by the ranges of channels used to estimate the continuum and peak intensity.\"; and the central FWHM holds \u224876% of peak intensity. 4) Limits of detection and k-ratios are constrained by the continuum vs signal: \"Ultimately, limits of detection are constrained by the magnitude of the background (continuum) level relative to the signal (characteristic) level.\" 5) By implication, differences in resolution, window transmission, dead layer and electronic performance between detectors will change observed peak shapes, background and low-energy sensitivity and thus will affect k-ratios for light elements below ~2 keV unless corrected or measured under matched conditions.\n\n\n---\n\n## pqac-00000011\n\nFrom text 'goldstein2018energydispersivexray pages 1-2'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\nThe excerpt describes the fundamental EDS detection physics and the principal measurement artifact relevant to low-energy X-rays. Photoelectric absorption in Si produces electron\u2013hole pairs (about 3.6 eV per pair), so the number of charge carriers (and statistical fluctuations) scales with photon energy. The EDS system builds a histogram of photon energies and has a usable energy range from about 0.05 keV to ~30 keV depending on detector design. The main artifact is peak broadening (the EDS resolution function): even sharply defined X-ray lines are broadened by statistical and detector contributions, and the measured FWHM is an energy-dependent function (a referenced equation is provided). The text contrasts older Si(Li) detectors with modern silicon drift detectors (SDD-EDS), implying detector design changes the detection characteristics. The table of contents also lists low-energy artifacts (Si-escape peak, Si absorption edge, internal fluorescence) that can affect spectra below a few keV. Together, these points indicate that detector-to-detector differences in resolution, efficiency and design will influence the measured peak shapes and low-energy response, which are the factors that would affect quantitative ratios for light elements.\n\n\n---\n\n## pqac-00000012\n\nFrom text 'newbury2011isscanningelectron pages 13-16'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\nThe excerpt describes using a \"remote-standards standardless\" approach in which a library of standard measurements made on another instrument supplies standard intensities; calculated corrections are applied for beam energy and spectrometer efficiency differences between instruments. However, no dose calibration is attempted, so the raw analytical total from such transferred standards has no validity and normalization is required\u2014thereby removing indicators of geometric or other deviations. The authors emphasize that the low-photon-energy region is particularly sensitive to anomalous absorption and spectrum-shape deviations; a measured-vs-simulated example for bulk K411 at 20 keV showed discrepancies ranging from +1.2% (FeK\u03b1) to +19% (MgK), illustrating larger uncertainties at low energies. Because a flat-bulk reference of the exact composition is often unavailable, the authors recommend simulating a bulk reference spectrum (e.g., with NIST DTSA-II) and using x-ray spectrum imaging (XSI) to locate favorable regions on rough specimens for analysis. The excerpt discusses spectrometer efficiency corrections but does not explicitly detail the separate effects of detector resolution, window, dead layer, or incomplete charge collection on k-ratios below 2 keV.\n\n\n---\n\n## pqac-00000013\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 11-13'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt states that SDD-EDS stability allows use of previously measured, stored standard spectra, provided a quality-assurance protocol confirms the unknown is measured under the same conditions as the archived standards (beam energy, dose, and EDS parameters). It emphasizes that spectra for unknowns and standards must be acquired under known, reproducible conditions including beam energy, electron dose/dead time, fixed time constant (resolution), detector-to-specimen distance (solid angle), detector take-off/azimuthal angles, and specimen tilt. A Faraday cup/digital picoammeter for beam current measurement is recommended for a rigorous k-ratio protocol. The authors recommend operating to yield ~10% detector deadtime to minimize pulse-coincidence (sum) peaks, noting coincidence grows significantly above ~15% deadtime; coincidence can still affect low-Z element peaks at high count rates. High-count spectra with stable peak shape and position improve MLLS peak fitting and thus k-ratio determination. The excerpt does not provide quantitative data on how detector-to-detector variations (resolution, window, dead layer, incomplete charge collection) specifically affect k-ratios for light elements below ~2 keV, so no direct numeric effects are given here.\n\n\n---\n\n## pqac-00000014\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 16-18'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses using a \u2018\u2018remote standards\u2019\u2019 approach and calibration transfer to address limitations of purely first\u2011principles (standardless) EDS quantification. It states that the remote standards method, tied to measurements of real materials, is inherently more accurate than first\u2011principles approaches. A practical calibration\u2011transfer technique mentioned is using a \u2018\u2018golden detector\u2019\u2019 (calibrated at a beamline) plus a carefully chosen reference material to transfer the calibration from that detector to other instruments (Alvisi et al., 2006). The text also notes that vendors often do not fully document their standardless implementations, leaving users uncertain about how numerical concentrations are derived. The paper includes low\u2011voltage (E0 = 5 keV) analyses and spectra (e.g., borides with B K\u2011L2,3 peak and YBa2Cu3O7 at 5 keV, and an EDS spectrum of BaCl2 at 5 keV), indicating attention to light\u2011element measurements at low energies. While the excerpt does not provide quantitative k\u2011ratio shifts caused by detector\u2011to\u2011detector differences (resolution, window, dead layer, incomplete charge collection), it implies such differences must be corrected via transferred calibration/standards to obtain accurate low\u2011energy (below ~2 keV) analyses.\n\n\n---\n\n## pqac-00000015\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 9-11'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt describes differences between silicon drift detectors (SDD-EDS) and older Si(Li)-EDS: SDDs operate around -20 \u00b0C (Peltier cooled) versus -190 \u00b0C for Si(Li), and their modified structure yields higher throughput and larger solid angle. Crucially, SDD-EDS shows nearly constant resolution (peak shape) and calibration (peak stability) across a wide range of input count rates, so peak shape and position used for fitting remain stable from major to trace peaks. This consistency allows assembling clusters of SDD detectors without significant degradation of the combined output. The figures and captions also illustrate spectral identification issues, e.g., misidentification of Pb M-family peaks in different materials and the close superposition of Mn K- and L-family peaks after scaling. While the text emphasizes improved stability and detector clustering for SDDs, it does not directly state how standard spectra transfer between different instruments or quantify detector-to-detector effects (window, dead layer, incomplete charge collection) on k-ratios for light elements below 2 keV.\n\n\n---\n\n## pqac-00000016\n\nFrom text 'ritchie2018exploringthelimits pages 4-5'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThe excerpt explains that in EDS the signals from multiple X-ray lines are integrated into a single measured peak and that each contributing line has slightly different matrix correction factors. For EDS this leads to a weighted matrix correction [ZAF]EDS computed from the individual transition weights (Wi) and their single-transition [ZAF]i values. Using complex or matrix-matched standards can reduce sensitivity to poorly known parameters because the ratio [ZAF]unk/[ZAF]std approaches unity. To handle peak interferences, DTSA-II uses additional spectra called peak-shape references \u201cwhich can be calibrated relative to the standard and fit to the unknown,\u201d and a \u201cStandard Bundle that sums standards and integrates the necessary peak-shape references.\u201d The text also notes that REE have complex L-line structures (tens of lines over a range of energies), which complicates WDS background placement but provides structure beneficial for EDS. Multiple acquisitions and summed standards are recommended to improve quality and reveal metrology issues. The authors\u2019 measurements used a multi-detector SDD setup (four independent 30 mm2 PulseTor SDDs), indicating multi-detector configurations are in practice.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016]\n\nStatus: Paper Count=25 | Relevant Papers=7 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=17 | Current Cost=$0.1059 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000017\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 17-20'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt emphasizes iterative, peak-fitting\u2013based analysis for detecting and quantifying trace elements in the presence of major-element interference. Peak fitting must include possible interfering peaks (example: TiKa/TiKb appearing in residuals when omitted); residual spectra should be inspected after stripping fitted peaks to reveal minor/trace constituents hidden beneath larger peaks. Residuals can also be used to estimate limits of detection, and detection limits may be lowered by accumulating more counts. Low-energy X-ray peaks are affected by chemical-shift and peak-shape \u2018\u2018chemical effects,\u2019\u2019 and EDS has significantly poorer spectral resolution than WDS, making interference correction more challenging for low-energy (low-Z) analyses. The text shows use of matrix-appropriate references and standards (e.g., \"Si and W as references and standards\" and \"using as standards elemental Mn and Ta, with sanbornite (BaSi2O5) for Si and Ba\") and examples where oxygen was set by stoichiometry. Together these points support strategies for low-kV EDS quantification: careful peak fitting including interfering major-element peaks, iterative re-analysis guided by residuals, increasing counts to improve detection limits, and using appropriate standards/matrix references.\n\n\n---\n\n## pqac-00000018\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 13-15'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nRelevant points for low-voltage (\u22485 keV) EDS quantification of trace Mg in an Al matrix: the incident beam energy must exceed the shell excitation energy (ideally by \u22651.25\u00d7), and 5 keV is effectively the lowest E0 that still excites at least one characteristic X-ray family for most elements. At E0 \u22645 keV, more elements become inaccessible and low-energy analysis increases the influence of surface layers and carbon contamination, which can change X-ray absorption. Trace measurements (C < 0.01) commonly involve peaks close to the continuum background and subject to overlap from much more intense major-element peaks; when a trace peak is buried under a major peak, the measurement challenge is substantially increased. Limits of detection (CDL) can be estimated from counts using CDL = [3NB1/2/(NS \u2212 NB)]CS, and practical LODs on suitably long counts can reach ~0.0002\u20130.0005 mass fraction (200\u2013500 ppm) depending on element and matrix. Mutual interferences can often be addressed with careful peak fitting. These points imply that for Mg-in-Al at 5 keV one should expect significant Al\u2013Mg overlap issues, require rigorous peak fitting and standards appropriate for low-kV geometry and surface/contamination effects, and use long counts to approach ppm-level detection.\n\n\n---\n\n## pqac-00000019\n\nFrom text 'tong2026measurementuncertaintiesof pages 8-11'.\n\nV. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.\n\nRelevant points for low\u2011kV (5 keV) EDS quantification of trace Mg in an Al matrix: EDX detectors typically have energy resolution \u2265100 eV so peaks are broad; ambiguity only occurs for peaks within ~30 eV but broad tails and fitting can still cause interference between nearby lines. Quantitative analysis requires sufficient electron overvoltage (ISO 22309:2011 recommends \u22651.8) and primary energy must exceed the X-ray energy. Detector efficiency varies strongly with X-ray energy and detector/window configuration, so elemental standards are needed for full quantification to cancel detector response differences. All quantitative work requires subtraction of Bremsstrahlung background; background fitting methods differ between software and a poor fit signals high uncertainty. Matrix (ZAF) corrections are required to account for electron backscattering, X-ray absorption and secondary fluorescence. Low\u2011energy detection is also affected by detector windows (Be absorbs <1 keV); windowless detectors are preferable but not always available. Operators must check and correct detector artefacts (sum/escape peaks) and ensure standards and acquisition conditions are appropriate for low\u2011kV analysis.\n\n\n---\n\n## pqac-00000020\n\nFrom text 'ritchie2018exploringthelimits pages 1-4'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThe excerpt discusses EDS detection limits, peak-to-background considerations, and metrology relevant to low-voltage EDS trace analysis. Limits of detection are fundamentally set by the continuum (background) relative to the characteristic signal; the same detection-limit formalism applies to EDS and WDS, but for EDS the measured intensities must be integrated over identical channel ranges on standard and unknown. Peak-to-background on EDS depends on the channel ranges used to estimate continuum and peak; optimal practice is to integrate the central FWHM (\u224876% of peak) and use equivalent ranges of continuum above and below. Modern SDDs have greatly improved throughput, resolution, and low-energy response (enabling detection down to Be-K and even Li-K), and for many measurements SDDs can match or exceed WDS in accuracy and precision. However, SDDs still generally have inferior peak-to-background ratios compared with WDS, limiting the lowest trace detection. Careful metrology and sample preparation (polish, conductive path, beam/sample geometry and working distance control) are emphasized, and standards should be measured and integrated over the same channel ranges as the unknown.\n\n\n---\n\n## pqac-00000021\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 16-18'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses quantitative EDS work performed at low beam energy (E0 = 5 keV) and highlights practical issues and methods relevant to low-kV analysis. Several tables and spectra are reported for analyses at 5 keV (e.g., borides, carbides, YBa2Cu3O7 and BaCl2 spectra), illustrating that low-energy spectra include extended low-energy families (for example, an \u201cextended Ba M-family\u201d), and that analyses used K-L2,3 or L-/M-family peaks depending on element and voltage. The text contrasts first-principles (standardless) analysis with a \u201cremote standards\u201d approach, stating that the remote standards method is tied to measurements of real materials and is inherently more accurate. It also notes a practical calibration transfer technique using a \u201cgolden detector\u201d calibrated at a beamline and a reference material. Finally, uncertainties were evaluated using NIST DTSA-II (reported as combined uncertainties), and tables give mean concentrations, RDEV, and replicate sigmas, conveying achievable precision at 5 keV. These points bear on detection limits, peak overlap and deconvolution, and standard selection for low-kV Mg-in-Al measurements.\n\n\n---\n\n## pqac-00000022\n\nFrom text 'goldstein2018quantitativeanalysisthe pages 1-4'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\nThe excerpt lays out practical requirements relevant to low-kV SEM/EDS quantification. It emphasizes that the k-ratio/matrix-correction method assumes a homogeneous bulk specimen (interaction volume ~0.5\u201310 \u03bcm; secondary fluorescence up to 10\u2013100 \u03bcm) and that specimen and standards must be measured under identical conditions (beam energy, electron dose, EDS parameters, target orientation, take-off angle). Surface preparation is critical: a highly polished, flat surface with roughness <100 nm rms (and <50 nm rms for measurements of photons <1 keV) is required; chemical polishing should be avoided and ion milling can alter near-surface composition. For spectral quality and peak fitting, consistent EDS parameters are essential; a 5 eV/channel energy width is recommended to adequately span peaks including those below 1 keV, and spectra should cover from ~100 eV up to the Duane\u2013Hunt limit. These points inform choices for low-energy (e.g., 5 keV) analyses, standard selection, peak-fitting resolution, and the need to control sample preparation and measurement geometry to minimize artifacts and allow meaningful k-ratio/matrix corrections.\n\n\n---\n\n## pqac-00000023\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 7-9'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\nThe excerpt highlights peak overlap and misidentification risks relevant to attempting low-kV (e.g., 5 keV) EDS quantification of trace Mg in an Al matrix. Table 4 shows Mg K\u03b1 (1.253 keV) and Al K\u03b1 (1.487 keV) lie in nearby energy bands, a situation prone to peak interference. Automatic peak-identification can mislabel peaks (e.g., BrL\u03b1 misidentified as AlK\u03b1) and such errors occur more frequently for minor/trace constituents. The authors recommend careful analyst review of tentative assignments, using software tools to explore alternative identifications, sequential peak identification with peak fitting and residual inspection, and adjusting beam energy when appropriate \u2014 either decreasing to reduce self-absorption or increasing to excite additional shells for confirmation. They also emphasize the value of standards-based k-ratio/matrix corrections (vs. standardless analysis), since standardless normalization can obscure clues (raw analytical total) that reveal dubious analyses. Overall, the text supports using peak fitting/residual checks, careful standard selection and standards-based quantification, beam-energy optimization, and cautious interpretation when quantifying trace Mg in an Al matrix at low beam energies.\n\n\n---\n\n## pqac-00000024\n\nFrom text 'ritchie2018exploringthelimits pages 4-5'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nRelevant points for low-kV EDS quantification (e.g., trace Mg in an Al matrix) from the excerpt: meticulous sample preparation and consistent measurement conditions are essential for accurate EDS results. Quantification uses the k-ratio method with matrix (ZAF) corrections that account for atomic number (Z), absorption (A) and secondary fluorescence (F); Z and A are typically computed from \u03c6(\u03c1z)-models. For EDS, multiple X-ray transitions are summed in an integrated peak and each transition has its own correction, so an overall weighted [ZAF]EDS must be applied. Standard selection matters: simple standards are easier but can increase dependence on poorly known parameters (e.g., mass absorption coefficients), while matrix-matched (complex) standards reduce matrix-correction dependence because [ZAF]unk/[ZAF]std approaches unity. Peak overlaps/interferences can be handled using peak-shape reference spectra (e.g., DTSA-II peak-shape references) and careful spectral fitting. Improving detection limits and precision is aided by collecting multiple spectra (N \u2248 5\u201310) of shorter live time, inter-comparing/rejecting outliers, and summing for better statistics. The excerpt also notes that complex line structure can be beneficial for EDS and gives an example dataset collected with SDD detectors (30 mm2) at 20 keV and 0.9 nA.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024]\n\nStatus: Paper Count=25 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=25 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re\u2010Usability: A Position Paper From the Nanosafety Community\nValid Text Names:\n'dumit2025challengesandfuture pages 2-2', 'dumit2025challengesandfuture pages 2-3', 'dumit2025challengesandfuture pages 3-3', 'dumit2025challengesandfuture pages 4-5', 'dumit2025challengesandfuture pages 5-5', 'dumit2025challengesandfuture pages 6-6', 'dumit2025challengesandfuture pages 6-7', 'dumit2025challengesandfuture pages 7-7', 'dumit2025challengesandfuture pages 8-8', 'dumit2025challengesandfuture pages 9-10', 'dumit2025challengesandfuture pages 9-9', 'dumit2025challengesandfuture pages 11-11', 'dumit2025challengesandfuture pages 12-12', 'dumit2025challengesandfuture pages 13-14', 'dumit2025challengesandfuture pages 14-14', 'dumit2025challengesandfuture pages 14-15', 'dumit2025challengesandfuture pages 15-15', 'dumit2025challengesandfuture pages 16-16', 'dumit2025challengesandfuture pages 17-17', 'dumit2025challengesandfuture pages 18-18'\n\nBibTex:\n@article{dumit2026challengesandfuture,\n    author = \"Dumit, Ver\u00f3nica I. and Furxhi, Irini and Nymark, Penny and Afantitis, Antreas and Ammar, Ammar and Amorim, Monica J. B. and Antunes, Dalila and Avramova, Svetlana and Battistelli, Chiara L. and Basei, Gianpietro and Bossa, Cecilia and Cimpan, Emil and Cimpan, Mihaela Roxana and Ciornii, Dmitri and Costa, Anna and Delpivo, Camilla and Dusinska, Maria and Fonseca, Ana Sofia and Friedrichs, Steffi and Hodoroaba, Vasile\u2010Dan and Hristozov, Danail and Isigonis, Panagiotis and Jeliazkova, Nina and Kochev, Nikolay and Kranjc, Eva and Maier, Dieter and Melagraki, Georgia and Papadiamantis, Anastasios G. and Puzyn, Tomasz and Rauscher, Hubert and Reilly, Katie and Jim\u00e9nez, Araceli S\u00e1nchez and Scott\u2010Fordsmand, Janeck J. and Shandilya, Neeraj and Shin, Hyun Kil and Tancheva, Gergana and van Rijn, Jeaphianne P. M. and Willighagen, Egon L. and Wyrzykowska, Ewelina and Bakker, Martine I. and Drobne, Damjana and Exner, Thomas E. and Himly, Martin and Lynch, Iseult\",\n    title = \"Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re\u2010Usability: A Position Paper From the Nanosafety Community\",\n    year = \"2026\",\n    journal = \"Advanced Sustainable Systems\",\n    volume = \"10\",\n    month = \"Dec\",\n    doi = \"10.1002/adsu.202500567\",\n    url = \"https://doi.org/10.1002/adsu.202500567\",\n    publisher = \"Wiley\",\n    issue = \"4\",\n    issn = \"2366-7486\"\n}\n\n\nAbstract:\n<jats:title>Abstract</jats:title>\n                  <jats:p>Ensuring data quality, completeness, and interoperability is crucial for progressing safety research, Safe\u2010and\u2010Sustainable\u2010by\u2010Design approaches, and regulatory approval of nanoscale and advanced materials. While the FAIR (Findable, Accessible, Interoperable, and Re\u2010usable) principles aim to promote data re\u2010use, they do not address data quality, essential for data re\u2010use for advancing sustainable and safe innovation. Effective quality assurance procedures require (meta)data to conform to community\u2010agreed standards. Nanosafety data offer a key reference point for developing best practices in data management for advanced materials, as their large\u2010scale generation coincided with the emergence of dedicated data quality criteria and concepts such as FAIR data. This work highlights frameworks, methodologies, and tools that address the challenges associated with the multidisciplinary nature of nanomaterial safety data. Existing approaches to evaluating the reliability, relevance, and completeness of data are considered in light of their potential for integration into harmonized standards and adaptation to advance material requirements. The goal here is to emphasize the importance of automated tools to reduce manual labor in making (meta)data FAIR, enabling trusted data re\u2010use and fostering safer, more sustainable innovation of advanced materials. Awareness and prioritization of these challenges are critical for building robust data infrastructures.</jats:p>\n\nRelevant Snippet:\n\u2026 The ISO standard 22029 Microbeam Analysis \u2013 EMSA/MAS file \u2026 -dimensional data file specification (HMSA)\u201d and \u201cTag image file format for Scanning Electron Microscopy\u201d have just \u2026\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024]\n\nStatus: Paper Count=26 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=25 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+                  "end_ts": 4489.069146065
+                }
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+              {
+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024]\n\nStatus: Paper Count=25 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=25 | Current Cost=$0.1554 | Disease-Target Evidence=0",
+                "name": "paper_search",
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+              {
+                "role": "assistant",
+                "content": "Let me now read some key texts directly for more specific information, and search for more papers:",
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+                    "id": "toolu_0123AygpAFvhxJmdFs7eBgmu",
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+                      "arguments": "{\"text_name_list\": [\"goldstein2018energydispersivexray pages 14-15\", \"goldstein2018energydispersivexray pages 15-16\", \"goldstein2018energydispersivexray pages 16-18\"]}",
+                      "name": "read_text"
+                    }
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+                    "id": "toolu_014GirKCBh19AkcdktvHnq5g",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Newbury Ritchie 2024 testing accuracy low beam energy 5 keV EDS certified reference materials RDEV\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_0156y4WhR8RXvWw2GXc17fKg",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"public EDS spectrum database library EMSA format microanalysis download repository\"}",
+                      "name": "paper_search"
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+                "content": "## 1. goldstein2018energydispersivexray pages 16-18 (Context ID: pqac-00000025)\n\n                                                                   \u201cImport \u2192 Raw\u201d tools to create a \u201cstack\u201d as shown in                   Detector                                                       .\u2003 Fig. 16.18.\n                                                                                        3. As imported, the orientation of the stack will depend\n                                                               upon how the data in the RAW file is organized.\n                                                                              Regardless of the original orientation, you will need to\n                                                                                 pivot the data a couple times using the \u201cImage \u2192\n                                        0.0                                                    Stack \u2192 Reslice\u201d tool. First, to identify the range of\n                                                                           channels that represent the Cu L-family and Cu K-L2,3\n                                                                                             intensities. Second, to align the spectrum data with           4\n               mm                                              the Z dimension so that the \u201cImage \u2192 Stack \u2192\n                                                                                Z-project\u201d tool can be used to create plots representing\n                                                                              the intensities in the Cu L-family and Cu K-L2,3\n                             4mm                       channels.\n                                                                                        4. The initial view of the imported spectrum will\n      . .\u200a\u200a\u200aFig. 16.16\u2003 A 3D rendering of the intensity in the Cu K line over a            usually show the data as shown in .\u2003 Fig. 16.19. In16\n           4 mm by 4 mm mapped area. Created using ImageJ-Fiji                          this view it is possible to identify the range of\n\n      . .\u200a\u200a\u200aFig. 16.17\u2003 A plot of two diag\u00ad\n            onal traverses extracted from the          300\n         3D rendering. The blue dots are                                                                                    Perp\n            perpendicular to the detector axis                                                                                                        Parallel\n                                             250          and red are parallel. Created using\n             ImageJ-Fiji\n                                             200\n\n\n                                             150                                                                                                                                                                        Intensity\n                                             100\n\n\n                                              50\n\n\n                                               0\n                                                 0           1           2           3           4           5           6\n\n                                                  mm                                                                                                       225                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n      channels to sum together for the Cu L-family and Cu   16.3.5  Count Rate Linearity\n       K-L2,3 lines. The Cu K-L2,3 lines are often quite dim.\n    5.  Using the \u201cImage \u2192 Stack \u2192 Reslice\u201d tool (see       One of the most important circuits in an X-ray pulse proces-\n       .\u2003 Fig. 16.20) rotate the stack until it looks like          sor accounts for the time during which the pulse processor is\n       .\u2003 Fig. 16.21                                       busy processing X-ray events. When the pulse processor is\n    6. Use the \u201cImage \u2192 Stack \u2192 Z-project\u201d twice            processing an X-ray, it is unavailable to process new incoming\n       (.\u2003 Fig. 16.22) to extract the range of channels           X-rays. This time is called \u201cdead-time.\u201d In contrast, the time\n       identified in .\u2003 Fig. 16.19 as associated with the Cu     during which the processor is not busy and is available is called\n       L-family and Cu K-L2,3 lines.                              \u201clive-time.\u201d The sum of \u201clive-time\u201d and \u201cdead-time\u201d is called\n    7. Convert the gray-scale image to a thermal scale using   \u201creal-time\u201d \u2013 the time you would measure using a wall clock.\n      \u201cImage \u2192 Lookup Tables \u2192 Thermal.\u201d                   For calculating the effective probe dose, live-time is the\n    8. Convert the image to a plot using \u201cAnalyze \u2192            critical parameter. The effective probe dose consists of those\n       Surface Plot\u201d                                           electrons which could produce measurable X-rays. So the\n    9.  Extract traverses from the image using the straight      effective probe dose equals the live-time times the probe cur-\n        line tool to define the traverse and then the \u201cAnalyze    rent. The effective probe dose is always less than the real\n   \u2192 Plot Profile\u201d tool to extract and plot the data.       probe dose, which is the product of the real time and the\n\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.18\u2003  Importing a RAW formatted spectrum image into\nImageJ-Fiji                                . .\u200a\u200aFig. 16.20\u2003  \u201cReslice\u201d tool used to rotate the stack\n\n\n\n\n       Cu L-family                                                               Cu K-L2,3\n\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.19\u2003 The spectrum image perspective as imported into ImageJ-Fiji. The bright strip is the Cu L-family while the much fainter band is\nCu K-L2,3           226    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                                                                  important because it is often hard to replicate the identical\n                                                                probe current but it is also important because different mate-\n                                                                                       rials measured with the same probe current will produce dif-\n                                                                            ferent dead times.\n                                                                    There really is no excuse for a modern X-ray detector not\n                                                                         to be linear. However, it is worth checking because the test\n                                                               can expose other potential problems like a non-linear or off-\n                                                                                set probe current meter.\n\n                                                                                           zz  Check 5: Count Rate Linearity with Effective Probe\n                                                                    Current\n                                                                  Equipment:\n                                   55 Faraday cup\n                                   55 Picoammeter\n                                   55 Flat, polished copper sample\n                                                                       Procedure:\n                                                                                       1. Mount the Faraday cup and the polished copper\n                                                                     sample on the stage at the same nominal working\n                                                                                   distance.\n                                                                                       2. Image the sample at the optimal working distance\n                                                               and a beam energy selected in the 15\u201325 keV\n                                                                            range.\n                                                                                    3.  Start a factor of 10 or more below the optimal probe\n                                                                              current. Measure and record the probe current using the\n                                                                    Faraday cup and the picoammeter.\n                                                                                    4. Collect a 60 live-time second spectrum from the copper\n                                                                        sample.\n                                                                                    5. Increase the probe current through a sequence of\n      . .\u200a\u200a\u200aFig. 16.21\u2003 The spectrum image was collected on a 128 by 128          approximately 10\u201320 steps from the initial probe current\n             pixel grid representing 4\u2009\u00d7 4 mm. After data rotation to view the x-y         to\n\n## 2. goldstein2018energydispersivexray pages 14-15 (Context ID: pqac-00000026)\n\n\n                              Y                                    distance\n                                                                                      \u03c8:\n                                                                                                    Elevation angle                                                         Actual\n                                  Z                     working                                                   Sample                                                                         distance\n\n\n\n\n                                                                                                 Sample tilt          222    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                                                                 per unit time. By spectral resolution we mean the width of\n                                                                   a characteristic peak, usually taken to be the Mn K-L2,3\n                                                             (K\u03b1) peak.\n                                                                  Higher throughput is desirable because it allows you to\n                                                                   use higher probe currents to produce more X-rays and pro-\n                                                              duce measured spectra with a larger number of measured\n                                                                         X-rays. Higher resolution is desirable because  it becomes\n                                                                             easier to distinguish characteristic peaks of similar energy.\n                                                             Both are virtues but one is achieved at the expense of the\n                                                                             other.\n                                                              The task of selecting a process time is the task of balanc-\n                                                                      ing good throughput with adequate resolution. At the best\n                                                                         resolution settings, throughput  is seriously compromised\n                                                           and as a result the precision of quantitative analysis is also\n                                                              compromised. At the highest throughput settings, resolution\n      . .\u200a\u200a\u200aFig. 16.14\u2003  Using a cell phone inclinometer to measure the eleva-                                                                                              is compromised and it becomes much more difficult to dis-             tion angle\n                                                                        tinguish interfering peaks.\n                                                                              Fortunately, resolution degrades relatively slowly while\n           correction. The elevation angle (usually sloppily called the  throughput increases quickly. Moderate pulse process times\n           \u201ctake-off angle\u201d) is often a configuration option that may be   tend to degrade the ultimate resolution by a few percent,\n           available to you to modify or may require a service engineer.   while increasing throughput by much larger factors. Every\n          Usually you can check the elevation angle by opening a spec-  vendor is different but typically a moderate pulse process\n         trum data file in a text editor. Most spectrum files are ASCII   time will produce both adequate resolution and excellent\n            text files and the vendors write a line containing the elevation   throughput.\n          or nominal take-off angle.                                 While some modern SDD are capable of ultimate resolu-\n           Compare the value produced by the software with the   tions of 122\u2013128 eV, compromising the resolution to 130\u2013\n           physical position of your detector relative to the beam axis.  135 eV  will produce an excellent compromise between\n          Sometimes, the correct instrument specific value of the take-\u00ad  resolution and throughput. Even a resolution of 140\u2013150 eV\n            off angle will be handwritten in the EDS vendor\u2019s documenta-   at high throughputs can produce  excellent  quantitative\n            tion. Other times, you can extract the angle from instrument   results because the precision of spectrum fitting is more\n            specific schematic diagrams from the SEM or EDS vendors.  determined by the number of measured X-rays than the\n           Regardless, it is a good idea to verify the elevation angle using   spectral resolution.\n          a protractor or a smart phone. Many smart phones contain\n          inclinometers which are accurate to within a degree and \u201cbub-                                                                                           zz  Check 2: Selecting a Process Time\n           ble level apps\u201d are available to turn the phone into a digital                                   55 Ensure that your EDS detector electronics are set to a           inclinometer. First, test the accuracy of the cell phone incli-                                                                    moderate process time that produces a good         nometer using a 30-60-90 triangle or similar reference shape.16                                                                    throughput with a resolution within 5 eV of the best         Then use the cell phone to measure the angle of the snout rela-                                                                                   resolution. Record this parameter in your electronic            tive to the angle of the column and calculate the elevation                                                                    notebook for future reference.           angle. .\u2003 Figure 16.14 shows that a cell phone measures the                                   55 Do not use an \u201cadaptive process time\u201d for           elevation angle of this detector to within half a degree (90\u00b0\u2013                                                                           standards-based quantitative analysis. Adaptive           54.5\u00b0 = 35.5\u00b0 ~ 35\u00b0 nominal value). Achieving similar accu-                                                                             process times allow the resolution to change with          racy with a protractor and a bubble level is difficult.                                                                       throughput making spectrum fitting challenging and\n                                                                                            less accurate.\n          16.3.2  Process Time\n                                                           The optimization of throughput is also confounded by an\n         The \u201cprocess time\u201d (also called the \u201cthroughput setting,\u201d   another practical limitation\u2014coincident X-rays or pulse-\u00ad\n          the \u201cdetector time constant,\u201d the \u201cresolution setting\u201d or  pileup\u2014and will be addressed in a later section.\n          other names) determines how much time the detector elec-\n           tronics dedicates to processing each incoming X-ray. A\n          longer  \u201cprocess  time\u201d  tends  to produce  lower X-ray   16.3.3  Optimal Working Distance\n         throughput but higher spectral resolution. Shorter \u201cpro-\n           cess times\u201d tend to produce higher X-ray throughput but   Nominally, the optimal working distance should be specified\n          lower spectral resolution. By throughput, we mean the   in instrument schematics. However,  it is worth checking\n       maximum number of X-rays that the detector can measure   because it may vary slightly or there may be a mistake in                                                                                                       223                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\ndesign or manufacturing. From the detector geometry sec-   detector element there is usually a window and an electron\ntion, we know that the optimal working distance is the dis-   trap. Most windows are ultrathin layers of polymer or sili-\ntance at which the axis along the detector snout intersects  con nitride mounted on a grid for mechanical strength.\nwith the electron beam axis (see .\u2003 Fig. 16.13). This working  Examples of two support grids are given in .\u2003 Fig. 16.15.\ndistance should also produce the largest flux of X-rays and be  While the grid may have an open area fraction of 75\u201380\u2009%,\nthe distance which is least sensitive to slight errors in vertical   the  silicon or carbon  grid  bars  are  often very  thick\npositioning.                                                  (0.38 mm) to enhance mechanical rigidity under the strain\n                                     \n\n## 3. goldstein2018energydispersivexray pages 15-16 (Context ID: pqac-00000027)\n\nat the optimal working distance is the dis-   trap. Most windows are ultrathin layers of polymer or sili-\ntance at which the axis along the detector snout intersects  con nitride mounted on a grid for mechanical strength.\nwith the electron beam axis (see .\u2003 Fig. 16.13). This working  Examples of two support grids are given in .\u2003 Fig. 16.15.\ndistance should also produce the largest flux of X-rays and be  While the grid may have an open area fraction of 75\u201380\u2009%,\nthe distance which is least sensitive to slight errors in vertical   the  silicon or carbon  grid  bars  are  often very  thick\npositioning.                                                  (0.38 mm) to enhance mechanical rigidity under the strain\n                                                               of up to one atmosphere of differential pressure. Off-axis\nzz  Check 3: Measuring the Optimal Working Distance       the grid bars can occlude the direct transmission of X-rays\n    1.  Select a sample like a piece of copper and mount it     from the sample to the detector element. Furthermore, the\n       perpendicular to the electron beam axis.             magnetic electron trap can also occlude X-rays from off-\n    2.  Select a beam energy of 15\u201325 keV and a moderate      axis. As a result, an EDS detector is more sensitive to X-rays\n      probe current to produce\u2009~\u200920% dead time.           produced on the snout axis than slightly off the axis. The\n    3. Move the stage\u2019s vertical axis to place the sample        result is a position dependent efficiency which peaks on\n       close to the objective lens pole piece. Be careful not     axis and decreases as the source of the X-rays is further\n       to run the sample into a detector.                  from axis.\n    4. Focus the image and record the working distance      A wide field-of-view X-ray spectrum image can demon-\n       reported by your SEM\u2019s software.                         strate the position sensitivity and can be used to ensure that\n    5.  Collect a 60 live-time second spectrum.                the detector snout and detector active element are oriented\n    6. Move the stage away from the objective lens pole        correctly.\n       piece in 1-mm steps.\n    7.  Repeat steps 4\u20136, taking the working distance             zz  Check 4: Collect a Wide Field X-ray Spectrum Image\n      through the nominal optimal working distance.              1. Mount a flat, polished piece of Cu in your SEM.\n    8.  Process the spectra. Extract the total number of              2. Image the Cu at the optimal working distance and at\n      counts in the energy range from about 100 eV to the         20\u201325 keV to excite both the K and L lines.\n     beam energy and plot this number against the                3. Find out how wide a field-of-view your SEM can\n      working distance.                                      image at the optimal working distance. The example\n    9. Determine the working distance which produces the           in .\u2003 Fig. 16.16 uses a 4-mm field-of-view.\n        largest number of counts. Since this working distance       4.  Collect a high count X-ray spectrum image from the\n       represents an inflection point, the slope will be              Cu. Acquiring at a moderate-to-high probe current\n     minimum and thus the sensitivity with respect to               for an hour or more at 256 \u00d7\u2009256-pixel image\n      working distance will also be minimized.                   dimensions should produce sufficiently high\n                                                                      signal-to-noise data.\n                                                                           5.  Process the data to extract and plot the raw\n16.3.4  Detector Orientation                                   intensities at each pixel in each of the Cu K-L2,3 and\n                                                Cu L-family lines.\nIn the previous section, we assumed that the principal axis of           1.  It is important to extract the raw intensities and\nthe detector snout is oriented to intersect with the electron            not the normalized intensities since we are\nbeam axis. In other words, the detector points towards the            looking for variation in the raw intensity as a\nsample. It is usually the EDS vendor\u2019s responsibility to ensure            function of position.\nthat the mounting flange has been designed to correctly ori-           2. The open source software ImageJ-Fiji (ImageJ\nent and position the detector. The next check will verify this.             plus additional tools) can be used to process\n   The active face of an EDS detector is a planar area that is           spectrum image data if it can be converted to a\nmounted perpendicular to the snout axis. In front of the       RAW format.\n\n\n\n                                AP3          AP5\n Thickness (\u00b5m)                      380           265\n Rib width (\u00b5m)                       59            45\n Opening width (\u00b5m)                  190           190             Thickness\n\n Open area %                    76%         78%\n                                                                                    Rib                     Opening\n Acceptance angle                     53\u00b0             72\u00b0                       width                    width\n\n. .\u200a\u200a\u200aFig. 16.15\u2003 Window support grid dimensions for two common window types (Source: MOXTEK)           224    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                6.  Plot the data to demonstrate the variation of the                nished intensities leading to low analytical totals\n                   intensity as a function of position. .\u2003 Figure 16.16              and sub-optimal quantitative results.\n               shows the map from a well-oriented detector plotted            3.  Typically, the Cu L-family peak is more sensi\u00adtive\n                using a thermal color scheme in which red                   due to absorption by the vacuum window support\n                 represents the highest intensity and blue represents                 grid\u2019s Si ribs. .\u2003 Figure 16.15 (source: Moxtek)\n                 zero intensity. .\u2003 Figure 16.17 shows traverses                 shows the design of two recent Moxtek support\n                 extracted from the .\u2003 Fig. 16.16 data on diagonals                  grids. The vertical sensitivity is usually minimized\n                 representing parallel to the detector axis and                  by orienting the grid ribs vertically.\n                perpendicular to the detector axis. Verify that the\n              most intense region in the intensity plots is in the\n                 center of the image area.                                       zz  Sidebar: Processing a \u201cRAW\u201d Spectrum Image with\n                7. Note the extent of the region of uniform efficiency.         ImageJ-Fiji\n                 Variation from ideal uniform sensitivity has                  1. Convert the X-ray spectrum image data into a RAW\n                consequences.                                                                    file. A RAW file is large binary representation of the\n                    1. Low magnification X-ray spectrum images will            data in the spectrum image. Each pixel in the\n                       suffer from reduced intensity towards the edges.          spectrum image consists of a spectrum encode in an\n                    2. Point mode X-ray spectrum acquisitions collected          integer binary format. The pixels are organized in a\n                        off the optical axis will also suffer from dimi\u00ad             continuous array row-by-\u00adrow. The size of the file is\n                                                                                      typically equal to (channel depth)\u2009\u00d7\u2009(row\n                                                                         dimension)\u2009\u00d7\u2009(column dimensions)\u2009\u00d7\u2009(2 or 4 bytes\n                                                                         per integer value).\n                                   255.0                                                                                        2. Import the RAW data file into ImageJ using the\n                                                                      \u201cImport \u2192 Raw\u201d tools to create a \u201cstack\u201d as shown in                   Detector                                                       .\u2003 Fig. 16.18.\n                                                                                        3. As imported, the orientation of the stack will depend\n                                                               upon how the data in the RAW file is organized.\n                                                                              Regardless of the original orientation, you will need to\n                                                                                 pivot the data a couple times using the \u201cImage \u2192\n             \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027]\n\nStatus: Paper Count=26 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=28 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024]\n\nStatus: Paper Count=26 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=25 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+              {
+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nJulien M Allaz. De-ma.ch: a web database for electron and x-ray microanalysis to assist electron microscope lab managers and users. Microscopy and Microanalysis, 30:489-500, May 2024. URL: https://doi.org/10.1093/mam/ozae051, doi:10.1093/mam/ozae051.\nNicholas W. M. Ritchie. Reproducible spectrum and hyperspectrum data analysis using nexl. Microscopy and Microanalysis, 28:478-495, Mar 2022. URL: https://doi.org/10.1017/s143192762200023x, doi:10.1017/s143192762200023x.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027]\n\nStatus: Paper Count=26 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=28 | Current Cost=$0.1554 | Disease-Target Evidence=0",
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+              {
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+                "tool_calls": [
+                  {
+                    "id": "toolu_013S7U99w9vd4NXF4wXpL7kV",
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+                      "arguments": "{\"question\": \"NIST DTSA-II accuracy at 5 keV low beam energy, RDEV results, number of measurements, how many percent fell within \\u00b15% RDEV at 5 keV?\"}",
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+                      "arguments": "{\"text_name_list\": [\"newbury2024testingtheaccuracy pages 1-3\", \"newbury2024testingtheaccuracy pages 3-4\", \"newbury2024testingtheaccuracy pages 4-6\"]}",
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+                "role": "tool",
+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000028\n\nFrom text 'newbury2024testingtheaccuracy pages 1-3'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nThe study evaluated the accuracy of low-beam-energy (E0 = 5 keV) electron-excited X-ray microanalysis using energy-dispersive spectrometry (EDS) with the NIST DTSA-II software and a standards-based k-ratio protocol. A total of 263 concentration measurements were made, covering 39 elements across 113 materials (including CRMs, stoichiometric compounds, minerals, and alloys). Accuracy was assessed using the relative deviation from expected value (RDEV) metric. Results show very high accuracy at 5 keV: more than 98% of the 263 measurements fell within \u00b15% RDEV, and 82% fell within -2% to 2% RDEV. DTSA-II also provides uncertainty budgets for reported concentrations, accounting for random and systematic contributions arising from X-ray counting statistics and matrix-correction factors, which underpins the reported confidence in these accuracy statistics.\n\n\n---\n\n## pqac-00000029\n\nFrom text 'newbury2024testingtheaccuracy pages 18-22'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt defines the accuracy metric RDEV as RDEV = [(measured value \u2212 expected value)/expected value] \u00d7 100%. Table 1 summarizes DTSA\u2011II results at a beam energy E0 = 5 keV, comprising 263 concentration measurements for 39 elements in 113 materials. Figure 3a shows the RDEV histogram for atomic concentrations derived from that table. For this 5 keV dataset, more than 98% of the results are captured within \u00b15% RDEV, with 82% within \u22122% to 2% RDEV. A separate raw totals histogram (sum of constituent mass concentrations) spans 0.8\u20131.2, with 67% of analyses in the 0.95\u20131.05 range. The paper notes the RDEV distribution at 5 keV is similar to that observed using conventional higher beam energies (\u226510 keV) when higher\u2011energy characteristic X\u2011rays are selected, and that Table 1 lists measured raw and normalized concentrations plus atomic concentrations and the computed RDEV values for each reported analysis.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029]\n\nStatus: Paper Count=26 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=30 | Current Cost=$0.1744 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "## 1. newbury2024testingtheaccuracy pages 4-6 (Context ID: pqac-00000030)\n\n    BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-\n          conc\n        Knownmass             0.7989     0.3158     0.6642     0.0669     0.9331     0.4492     0.5508     0.3236     0.6764     0.4890     0.5110     0.3112     0.6888     0.5399     0.4601     0.2264     0.7736     0.4007     0.5993     0.5797\n\n      Ele-ment    Cu O  Cr C  Fe  Ti  Ni  Si  Ni  Si  Ni B  Ti  Si  Ti N  Ti O  Ti  Al\n             Materialnumber    10  11  11  12  12  13  13  14  14  15  15  16  16  17  17  18  18  19  19  20\n\n\u2009continued             Material                     CuO_5kV         Cr2O3_5keV         Cr2O3_5keV       Fe3C_5kV       Fe3C_5kV        NiTi_5kVA       NiTi_5kV       NiSi_5kV       NiSi_5kV        NiSi2_5kV        NiSi2_5kV       TiB2_5kV       TiB2_5kV        TiSi2_5kV        TiSi2_5kV      TiN_5kV      TiN_5kV       TiO2_5kV       TiO2_5kV        Al3Ni_5kV\nTable\u202f1\u2002 Row      21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40 19092                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\n   %\n                       1.9    -2.8    -0.36    0.39   1.5    -1.5    -1.1   2.9    -0.50    -2.7   1.3    -3.2   3.2    -1.7   3.4    -2.2   3.7    -1.6   3.2        Atom-concRDEV       -0.73\n\n          Atomicconc             0.2482     0.6112     0.3888     0.5156     0.4844     0.5077     0.4923     0.6183     0.2573     0.1255     0.3244     0.6756     0.4839     0.5161     0.6554     0.3446     0.5264     0.2393     0.0757     0.1587\n          Atomicconcreference         0.2500     0.6000     0.4000     0.5175     0.4825     0.5000     0.5000     0.6250     0.2500     0.1250     0.3333     0.6667     0.5000     0.5000     0.6667     0.3333     0.5385     0.2308     0.0769     0.1538\n\n                                             2.0    -1.1    -1.1   2.9    -0.53    -3.6    0.38    -5.2   1.1    -3.5   1.5    -3.9   1.9    -3.4   1.4        Norm-concRDEV%   -0.57    2.80    -1.90    -0.12    0.62\n\n          mass\n           Normal-izedconc         0.4179     0.4195     0.5805     0.4978     0.5022     0.3487     0.6513     0.2893     0.2113     0.4994     0.0908     0.9092     0.1631     0.8369     0.2834     0.7166     0.1615     0.2916     0.1290     0.4179\n\n   %\n                 5.5   5.7    0.91   5.2   6.0   6.1   2.9    -2.1   1.9    -1.5    -6.4    -2.5    -5.3   1.1    -7.1    -2.3    -2.1   3.8    -1.5   3.3     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0087      \u00b10.0047      \u00b10.0110      \u00b10.0275      \u00b10.0571      \u00b10.0573      \u00b10.0013      \u00b10.0097      \u00b10.0015      \u00b10.0068      \u00b10.0372      \u00b10.0106      \u00b10.0649      \u00b10.0177      \u00b10.0988      \u00b10.0260      \u00b10.0118      \u00b10.0183      \u00b10.0008      \u00b10.0097\n\n     Rawmassconc         0.4432     0.4313     0.5969     0.5243     0.5289     0.3626     0.6773     0.2865     0.2092     0.4946     0.0882     0.8829     0.1630     0.8366     0.2728     0.6898     0.1646     0.2972     0.1315     0.4260\n\n        total\n     Raw            1.06    1.028    1.028    1.053    1.053    1.04    1.04     0.9904     0.9904     0.9904     0.9711     0.9711     0.9996     0.9996     0.9626     0.9626    1.019    1.019    1.019    1.019\n\n             Standard            NiTi    Al2O3    NiTi  Cr    Fe3C   GaN  Al   MgO  Si    BaCO3 B  Cr B  Cr B  Cr    BaCO3   CuS    Y2O3    BaCO3\n\n\n     keV                                                   7,511,728        7,732,677        7,732,677        5,937,198        5,937,198        3,807,755        3,807,755        7,412,983        7,412,983        7,412,983        3,257,829        3,257,829        3,084,682        3,084,682        2,954,279        2,954,279        8,181,180        8,181,180        8,181,180        8,181,180        0.1-5counts\n                                                                 BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-\n          conc\n        Knownmass             0.4203     0.4081     0.5919     0.4984     0.4991     0.3417     0.6583     0.2925     0.2054     0.5021     0.0942     0.9058     0.1721     0.8279     0.2937     0.7063     0.1681     0.2862     0.1335     0.4123\n\n      Ele-ment    Ni  Al  Ni  Cr  Fe N  Al O  Si  Ba B  Cr B  Cr B  Cr O  Cu Y  Ba\n             Materialnumber    20  21  21  22  22  23  23  24  24  24  25  25  26  26  27  27  28  28  28  28\n\n\u2009continued             Material                           Al3Ni_5kV         Al3Ni2_5kV         Al3Ni2_5kV           50Fe-50Cr_5kV           50Fe-50Cr_5kV       AlN_5keV       AlN_5keV                BaSi2O5_Sanbornite                BaSi2O5_Sanbornite                BaSi2O5_Sanbornite    Cr2B    Cr2B   CrB   CrB    CrB2    CrB2            YBa2Cu3O7_xtal            YBa2Cu3O7_xtal            YBa2Cu3O7_xtal            YBa2Cu3O7_xtal\nTable\u202f1\u2002 Row      41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60  J Mater Sci (2024) 59:19088\u201319111                                                                19093\n\n\n\n\n\n   %\n                       2.0    0.23    -0.15    -0.12    0.18    -2.0   2.0    -2.7   2.7    -1.4    0.69    -0.20    0.20    -0.40    0.40   1.4    -2.8    -1.3   1.3        Atom-concRDEV      -2.0\n\n          Atomicconc             0.4901     0.5099     0.4009     0.5991     0.5993     0.4007     0.4902     0.5098     0.4864     0.5136     0.3287     0.6713     0.4990     0.5010     0.4980     0.5020     0.6759     0.3241     0.4933     0.5067\n          Atomicconcreference         0.5000     0.5000     0.4000     0.6000     0.6000     0.4000     0.5000     0.5000     0.5000     0.5000     0.3333     0.6667     0.5000     0.5000     0.5000     0.5000     0.6667     0.3333     0.5000     0.5000\n\n                                                                    3.0    -1.9    0.24    -0.3    0.14    -0.49    0.28   1.9    -2.2    -1.4   1.3        Norm-concRDEV%   -3.5    0.44    0.28    -0.11    -0.19    0.11    -3.0    0.85    -3.2\n\n          mass\n           Normal-izedconc         0.1074     0.8926     0.2821     0.7179     0.3610     0.6390     0.2153     0.7847     0.3995     0.6005     0.1097     0.8903     0.3345     0.6655     0.3629     0.6371     0.5449      0.45516     0.4754     0.5246\n\n   %\n                                                     0.75   1.0    0.77   4.7    0.99   6.7   1.2   3.3    -2.9    -2.5   1.4   3.6   4.3    0.06   4.9   7.7                 2.4   6.6    11.8    11.3     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0317      \u00b10.0017      \u00b10.0066      \u00b10.0093      \u00b10.0035      \u00b10.0032      \u00b10.0011      \u00b10.0036      \u00b10.0045      \u00b10.0025      \u00b10.0052      \u00b10.0136      \u00b10.0020      \u00b10.0101      \u00b10.0018      \u00b10.0343      \u00b10.0024      \u00b10.0091      \u00b10.0030      \u00b10.0242\n\n     Rawmassconc         0.1139     0.9470     0.3144     0.8000     0.3644     0.6449     0.2236     0.8150     0.4167     0.5874     0.1131     0.9173     0.3258     0.6482     0.3698     0.6492     0.5577     0.4658     0.5055     0.5579\n\n        total\n     Raw               1.061    1.061    1.114    1.114    1.009    1.009     1.0386     1.0386    1.043    1.043     1.0303     1.0303    0.974    0.974     1.0191     1.0191     1.0234     1.0234    1.063    1.063\n\n             Standard   C  Mo  As  Te  Se  Bi   CuS  Cd  Se  Cd   MgO   CuS   ZnS    Cu2O   CuS  Fe   CuS    FeAl3   GaP  As\n\n\n     keV                                                   4,100,229        4,100,229        5,212,612        5,212,612        6,505,288        6,505,288        4,535,223   \n\n## 2. newbury2024testingtheaccuracy pages 1-3 (Context ID: pqac-00000031)\n\nJ Mater Sci (2024) 59:19088\u201319111\n\nComputation & theory\n\n\n\nTesting the accuracy of low\u2011beam\u2011energy\nelectron\u2011excited X\u2011ray microanalysis\nwith energy\u2011dispersive spectrometry\n\nDale E. Newbury1,*\u200a  and Nicholas W. M. Ritchie1\u200a\n\n1\u2009National Institute of Standards and Technology, Gaithersburg, MD 20899\u20118370, USA\n\n\n Received: 29 August 2024    ABSTRACT\n Accepted: 25 September 2024    The accuracy of electron-excited X-ray microanalysis with energy-dispersive spec-\n Published online:             trometry (EDS) has been tested in the low beam energy range, specifically at an\n 14 October 2024                incident beam energy of 5 keV, which is the lowest beam energy for which a use-\n                                  ful characteristic X-ray peak can be excited for all elements of the periodic table,\n This is a U.S. Government        excepting H and He. Elemental analysis results are reported for certified reference\n work and not under copyright     materials (CRM), stoichiometric compounds, minerals, and metal alloys of inde-\n                            pendently known or measured composition which had microscopic homogeneity protection in the US; foreign\n                                suitable for microanalysis. Two-hundred sixty-three concentration measurements copyright protection may ap-\n                                 for 39 elements in 113 materials were determined following the k-ratio protocol and ply, 2024\n                            using the EDS analytical software NIST DTSA-II. The accuracy of the results, as\n                              characterized by the relative deviation from expected value (RDEV) metric, was such\n                                that more than 98% of the results were found to be captured within a range of \u00b15%\n                       RDEV, while 82% of the results fell in the range -2% to 2% RDEV.\n\nIntroduction                                     Because of the strong dependence of the electron range\n                                            on the incident beam energy, R \u2248E0 1.66\u200a, the spatial\nElectron-excited X-ray microanalysis with energy-    resolution of the measurement can be significantly\ndispersive spectrometry (EDS) is a spatially resolved   improved by reducing the beam energy to the lowest\nelemental characterization technique that is widely   value compatible with achieving useful X-ray excita-\napplied in the physical, biological, and forensic sci-    tion for all elements to be measured in the specimen.\nences, technology, failure analysis, etc. [1]. \u201cConven-   As detailed in a previous paper [2], \u201clow-beam-energy\ntional\u201d analytical strategy involves selecting the inci-    microanalysis\u201d involves choosing the beam energy in\ndent beam energy, \u00adE0, to be 10 keV or higher to excite    the range \u00adE0 \u2264 5 keV. \u00adE0 = 5 keV is the lowest beam\nanalytically useful characteristic X-rays from all ele-   energy for which an analytically useful characteristic\nments of the periodic table, with the exception of H   X-ray can be excited for all elements except H and He.\nand He, which do not produce characteristic X-rays.   However, even with a choice of \u00adE0 = 5 keV, less familiar\n\n\nHandling Editor: C. Barry Carter.\n\nAddress correspondence to E-mail: dale.newbury@nist.gov\nE-mail Addresses: nicholas.ritchie@nist.gov\n\n                                                                     https://doi.org/10.1007/s10853-024-10285-4\n\n\n\n           Vol:.(1234567890) J Mater Sci (2024) 59:19088\u201319111                                                                19089\n\n\nlow photon energy characteristic X-rays must be used    energy-dispersive spectrometry for a beam energy\nfor several elements, e.g., the Ti L-family (\u2248 0.45 keV)    of \u00adE0 = 5 keV. Analysis followed the standards-based\ninstead of the Ti K-family (4.5 keV) and the Ba M-fam-    measurement protocol, in which each element in the\nily (0.6\u20131.1 keV) instead of the Ba L-family (4.467 keV).    sample is measured relative to that same element\nAs the beam energy is lowered below 5 keV, elements    present at a known concentration in a \u201cstandard\u201d,\nare progressively lost to analysis due to inadequate or    which can be a pure element, a binary stoichiometric\nno excitation [2].                               compound, or an elemental mixture such as a glass\n  When an unknown material is analyzed, the abso-    available as a CRM [1].\nlute accuracy of the analytical results cannot be known\ndue to uncertainty in the various parameters neces-\nsary to calculate the matrix correction factors. Robust\nanalytical practice requires that an uncertainty budget   Materials and methods\nbe associated with each reported elemental concen-\ntration, such as that provided by the NIST DTSA-II    All materials analyzed are listed individually in\nsoftware platform [3]. DTSA-II attaches to each con-    Table 1, summary of results. Materials and sources\ncentration value an uncertainty budget that includes    analyzed in this study include:\nthe contribution of the random component due to the\ncharacteristic X-ray measurement statistics (from the     1.  National Institute of Standards and Technology\nunknown and the standard) as well as an estimation       (NIST) Standard Reference Materials (SRM) spe-\nof the systematic components that arise from the prin-         cially developed to be homogeneous on the micro-\ncipal matrix correction corrections for electron scat-        scopic scale so as to be suitable for microanalysis\ntering and energy loss (the \u201cZ\u201d factor) and the self-        applications:\nabsorption of X-rays (the \u201cA\u201d factor). This uncertainty         (1) SRM 470 K411 glass (O-Mg-Si-Ca-Fe)\nbudget can then be used to describe a \u201cconfidence         (2) SRM 470 K412 glass (O-Mg-Al-Si-Ca-Fe)\nrange\u201d within which the true concentration value can         (3) SRM 479 (Fe-Cr-Ni Stainless Steel)\nbe expected to reside [4\u20136].                                       (4) SRM 481, Gold-Silver alloys (nominal 20, 40,\n  The general \u201daccuracy\u201d of electron-excited X-ray              60, and 80 weight percent)\nmicroanalysis can be estimated by analyzing \u201cchal-         (5) SRM 482, Gold-Copper alloys (nominal 20, 40,\nlenge specimens\u201d whose compositions are known              60, and 80 weight percent)\nfrom independent analysis so that the measured         (6) SRM 1871 K456 glass (O-Si-Pb)\nvalue can be reasonably compared to a known refer-         (7) SRM 1872 K453 glass (O-Ge-Pb)\nence value. A limited number of microanalysis-qual-         (8) SRM 1873 K458 glass (O-Si-Zn-Ba)\nified certified reference materials (CRM) are avail-         (9) SRM 1875 K496 glass (O-Mg-Al-P)\nable from national measurement institutions, such     2.  European Commission, Community Bureau of Ref-\nas the National Institute of Standards and Technol-       erence\nogy (U.S.A.). Additional challenge specimens can be         (1)  Fe3C (CRM BCR-726)\nderived from materials whose composition is sharply\nconstrained by their stoichiometric nature and which     3.  Reagent compounds, e.g., \u00adBaTiO3, PbS, \u00adMoS2\ndo not exhibit a range of solid solubility, e.g., com-        (source: Alfa Aesar, Tewksbury, MA 01876)).\npounds such as \u00adFeS2, CuS, \u00adFe2O3, etc. A second criti-     4.  Stoichiometric binary compounds, e.g., TiN, \u00adTiO2,\ncal criterion is that these challenge specimens must        \u00adCr2N, etc., with surfaces prepared for microanaly-\nalso be homogeneous on a microscopic scale, a con-         sis (source: Geller Microanalytical Laboratory,\ndition which can be confirmed by a systematic sur-        Topfield, MA 01983)\nvey of the material by \u201cpoint beam\u201d random sam-     5.  Minerals of known composition and micro-\npling or by area scanning /compositional mapping      homogeneity, e.g., albite, arsenopyrite, cal-\nto examine microstructural compositional details.         cite, chalcopyrite, cinnabar, cryolite, dolomite,\nThe current study has undertaken analysis of a wide        fluorapatite, galena, jadeite, kyanite, hematite,\nrange of challenge specimens to develop an analyti-        magnetite, pyrite, rhodonite, scheelite, willemite,\ncal history sufficient to make an estimate of the accu-        wollastonite, zircon (source: SPI (West Chester, PA,\nracy of electron-excited X-ray microanalysis with        19381-0656, USA) ) 19090                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\n   %\n                                        2.3    -4.8   4.6    -3.5    -0.16    0.98    0.86    -2.3   1.3    -1.5   1.5    -0.67   2.7    -0.36    -2.6    -1.7        Atom-concRDEV      0.37    -4.5    0.89    -4.1\n\n          Atomicconc              0.9282     0.0718     0.8297     0.1703     0.6863     0.3137     0.4538     0.5462     0.8620     0.1380     0.7385     0.2615     0.5552     0.4448     0.3175     0.6825     0.2001     0.7016     0.0984     0.4913\n          Atomicconcreference         0.9248     0.0752     0.8224     0.1776     0.6706     0.3294     0.4340     0.5660   \n\n## 3. newbury2024testingtheaccuracy pages 3-4 (Context ID: pqac-00000032)\n\n81-0656, USA) ) 19090                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\n   %\n                                        2.3    -4.8   4.6    -3.5    -0.16    0.98    0.86    -2.3   1.3    -1.5   1.5    -0.67   2.7    -0.36    -2.6    -1.7        Atom-concRDEV      0.37    -4.5    0.89    -4.1\n\n          Atomicconc              0.9282     0.0718     0.8297     0.1703     0.6863     0.3137     0.4538     0.5462     0.8620     0.1380     0.7385     0.2615     0.5552     0.4448     0.3175     0.6825     0.2001     0.7016     0.0984     0.4913\n          Atomicconcreference         0.9248     0.0752     0.8224     0.1776     0.6706     0.3294     0.4340     0.5660     0.8633     0.1367     0.7322     0.2678     0.5483     0.4517     0.3129     0.6871     0.1949     0.7041     0.1010     0.5000\n\n                 1.0    -3.9   2.0    -3.0   4.4    -2.9   6.6    -1.6    -0.26    0.86   1.3    -1.9   1.7    -1.1   1.7    -0.44   2.7    -0.31    -2.5    -2.7        Norm-concRDEV%\n\n          mass\n           Normal-izedconc         0.8067     0.1933     0.6112     0.3888     0.4138     0.5862     0.2114     0.7886     0.7738     0.2262     0.6073     0.3927     0.4061     0.5939     0.2030     0.7970     0.1879     0.7078     0.1043     0.1956\n\n   %\n                                                                                                                 8.1   5.7    -4.8                 1.7    -3.3   2.8    -2.3   4.2    -3.1   5.2    -2.9   1.1   2.2   1.5    -1.7   1.6    -1.2   2.2    0.01    11.4     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0117      \u00b10.0026      \u00b10.0175      \u00b10.0040      \u00b10.0177      \u00b10.0043      \u00b10.0122      \u00b10.0031      \u00b10.0054      \u00b10.0027      \u00b10.0068      \u00b10.0036      \u00b10.0069      \u00b10.0038      \u00b10.0047      \u00b10.0029      \u00b10.0181      \u00b10.0424      \u00b10.0108      \u00b10.0012\n\n     Rawmassconc         0.8120     0.1946     0.6160     0.3918     0.4128     0.5848     0.2086     0.7782     0.7841     0.2292     0.6084     0.3934     0.4057     0.5934     0.2040     0.8006     0.2038     0.7677     0.1131     0.1915\n\n        total\n     Raw                  1.0066     1.0066     1.0078     1.0078     0.9975     0.9975     0.9868     0.9868    1.013    1.013    1.002    1.002     0.9991     0.9991    1.005    1.005    1.085    1.085    1.085     0.9793\n\n             Standard      Cu  Au  Cu  Au  Cu  Au  Cu  Au  Ag  Au  Ag  Au  Ag  Au  Ag  Au  Cr  Fe    NiSi   MgO\n\n\n     keV                                                   6,705,457        6,705,457        6,532,544        6,532,544        6,376,277        6,376,277        6,305,887        6,305,887        4,778,550        4,778,550        5,070,877        5,070,877        5,486,996        5,486,996        6,015,553        6,015,553        6,491,256        6,491,256        6,491,256        9,844,586keV  0.1-5counts\n5\n=\n\u00adE0\nat\n                                                                 BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad                Analyticalplatform                       JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-Analysis\nfor    conc\n        Knownmass              0.7985     0.2012     0.5992     0.4010     0.3964     0.6036     0.1983     0.8015     0.7758     0.2243     0.5993     0.4003     0.3992     0.6005     0.1996     0.8005    0.183    0.710    0.107     0.2011\nResults\n       Ele-ment     Cu  Au  Cu  Au  Cu  Au  Cu  Au  Ag  Au  Ag  Au  Ag  Au  Ag  Au  Cr  Fe  Ni O\nAnalytical   Materialnumber  1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 9  10\nof\n\u2009Compilation                                                                              Au20Cu80_5kV           Au20Cu80_5kV           Au40Cu60_5kV           Au40Cu60_5kV           Au60Cu40_5kV           Au60Cu40_5kV           Au80Cu20_5kV           Au80Cu20_5kV           Au20Ag80_5kV           Au20Ag80_5kV           Au40Ag60_5kV           Au40Ag60_5kV           Au60Ag40_5kV           Au60Ag40_5kV           Au80Ag20_5kV           Au80Ag20_5kV             less_Steel_5keV             less_Steel_5keV             less_Steel_5keV             Material                      SRM482_      SRM482_      SRM482_      SRM482_      SRM482_      SRM482_      SRM482_      SRM482_      SRM481_      SRM481_      SRM481_      SRM481_      SRM481_      SRM481_      SRM481_      SRM481_           SRM479_Stain-           SRM479_Stain-           SRM479_Stain-      CuO_5kV\nTable\u202f1\u2002 Row   1 2 3 4 5 6 7 8 9  10  11  12  13  14  15  16  17  18  19  20  J Mater Sci (2024) 59:19088\u201319111                                                                19091\n\n\n\n\n\n   %\n                 1.7    0.88    -1.3    -2.5    0.83    -2.8   2.8    -0.23    0.23    -1.4   2.8    -1.1   2.3   1.1    -2.2    -0.90    0.90    -0.10    0.19    0.24        Atom-concRDEV\n\n          Atomicconc             0.5087     0.6053     0.3947     0.2438     0.7562     0.4862     0.5138     0.4988     0.5012     0.6573     0.3427     0.6591     0.3409     0.6739     0.3261     0.4955     0.5045     0.6661     0.3339     0.7518\n          Atomicconcreference         0.5000     0.6000     0.4000     0.2500     0.7500     0.5000     0.5000     0.5000     0.5000     0.6667     0.3333     0.6667     0.3333     0.6667     0.3333     0.5000     0.5000     0.6667     0.3333     0.7500\n\n                       1.5   2.3    -7.2    0.21    -3.0   2.5    -0.31    0.15    -2.1   2.1    -2.3   1.0   1.5    -1.8    -1.4    0.40    -0.17    0.12    0.41        Norm-concRDEV%   0.69\n\n          mass\n           Normal-izedconc         0.8044     0.3205     0.6795     0.0649     0.9351     0.4356     0.5644     0.3226     0.6774     0.4785     0.5215     0.3040     0.6960     0.5481     0.4519     0.2233     0.7767     0.4000     0.6000     0.5821\n\n   %\n                                                                                                                            6.5                                                                                                                        0.70    -2.6    19.0    21.1    -1.1    -0.85                       -1.4    -8.6    -7.8   2.8   6.3    15.6    22.2    -1.6    -1.2   4.2   8.6    14.8    18.6     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0032      \u00b10.0098      \u00b10.0306      \u00b10.0155      \u00b10.0044      \u00b10.0394      \u00b10.0232      \u00b10.0026      \u00b10.0151      \u00b10.0030      \u00b10.0097      \u00b10.0495      \u00b10.0251      \u00b10.0004      \u00b10.0256      \u00b10.0832      \u00b10.0763      \u00b10.0305      \u00b10.0115      \u00b10.0046\n\n     Rawmassconc         0.7878     0.2888     0.6121     0.0688     0.9916     0.5192     0.6729     0.3182     0.6681     0.5094     0.5551     0.3517     0.8171     0.5437     0.4438     0.2695     0.9375     0.3961     0.5942     0.6173\n\n        total\n     Raw                  0.9793     0.9008     0.9008    1.059    1.059    1.192    1.192     0.9857     0.9857    1.065    1.065    1.174    1.174     0.9919     0.9919    1.207    1.207     0.9903     0.9903    1.06\n\n             Standard      Cu O  Cr C  Fe  Ti  Ni  Si    NiTi  Si    NiTi B  Ti  Si  Ti   GaN    TiSi2 O  Ti  Al\n\n\n     keV                                                   9,844,586        5,268,245        5,268,245        3,585,708        3,585,708         12,088,360         12,088,360        7,329,688        7,329,688        5,908,406        5,908,406        4,130,925        4,130,925        6,011,950        6,011,950        2,518,085        2,518,085        5,391,466        5,391,466        7,511,728        0.1-5counts\n                                                                 BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad         BrukerQuad                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-     \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032]\n\nStatus: Paper Count=26 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=33 | Current Cost=$0.1744 | Disease-Target Evidence=0",
+                "name": "read_text",
+                "tool_call_id": "toolu_01X2qzVE6cp9iUKPWBL1uVh6",
+                "info": {
+                  "start_ts": 4564.760746304,
+                  "end_ts": 4618.189018834
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Excellent. Now let me look at additional specific information and collect cited papers:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01MdPzYiwbwhaiFWoSVyBdxN",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{}",
+                      "name": "collect_cited_papers_in_evidence"
+                    }
+                  },
+                  {
+                    "id": "toolu_0158Z2mioMoToKMUGybguiH8",
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+                "content": "Artifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032]\n\nStatus: Paper Count=30 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=33 | Current Cost=$0.1744 | Disease-Target Evidence=0",
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+                "tool_call_id": "toolu_01MdPzYiwbwhaiFWoSVyBdxN",
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+                "content": "## 1. newbury2024testingtheaccuracy pages 6-8 (Context ID: pqac-00000033)\n\n  0.1139     0.9470     0.3144     0.8000     0.3644     0.6449     0.2236     0.8150     0.4167     0.5874     0.1131     0.9173     0.3258     0.6482     0.3698     0.6492     0.5577     0.4658     0.5055     0.5579\n\n        total\n     Raw               1.061    1.061    1.114    1.114    1.009    1.009     1.0386     1.0386    1.043    1.043     1.0303     1.0303    0.974    0.974     1.0191     1.0191     1.0234     1.0234    1.063    1.063\n\n             Standard   C  Mo  As  Te  Se  Bi   CuS  Cd  Se  Cd   MgO   CuS   ZnS    Cu2O   CuS  Fe   CuS    FeAl3   GaP  As\n\n\n     keV                                                   4,100,229        4,100,229        5,212,612        5,212,612        6,505,288        6,505,288        4,535,223        4,535,223        5,493,373        5,493,373        7,363,940        7,363,940        6,343,848        6,343,848        4,590,580        4,590,580        4,624,933        4,624,933        7,547,321        7,547,321        0.1-5counts\n                                                                 BrukerQuad         BrukerQuad         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         BrukerQuad         BrukerQuad         Bruker2019         Bruker2019                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-\n          conc\n        Knownmass             0.1113     0.8887     0.2813     0.7187     0.3617     0.6383     0.2219     0.7781     0.4126     0.5874     0.1118     0.8882     0.3354     0.6646     0.3647     0.6353     0.5345     0.4655     0.4820     0.5180\n\n      Ele-ment  C  Mo  As  Te  Se  Bi S  Cd  Se  Cd O  Cu S  Cu S  Fe S  Fe  Ga  As\n             Materialnumber    29  29  30  30  31  31  32  32  33  33  34  34  35  35  36  36  37  37  38  38\n\n\u2009continued             Material         MoC   MoC         As2Te3_5kV         As2Te3_5kV         Bi2Se3_5kV         Bi2Se3_5kV      CdS_5kV      CdS_5kV       CdSe_5kV       CdSe_5kV       Cu2O_5kV       Cu2O_5kV       CuS_5keV       CuS_5keV       FeS_5keV       FeS_5keV        FeS2_5keV        FeS2_5keV       GaAs_5kV       GaAs_5kV\nTable\u202f1\u2002 Row      61  62  63  64  65  66  67  68  69  70  71  72  73  74  75  76  77  78  79  80 19094                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\n   %\n                       1.5    -0.64    0.64    -1.0   2.0    0.04    -0.04    -0.92    0.92   0.4    -0.4    -1.9   1.9    0.07    -0.15   1.3    -1.3    0.83    -1.3        Atom-concRDEV      -1.5\n\n          Atomicconc             0.4924     0.5076     0.4968     0.5032     0.6601     0.3399     0.5002     0.4998     0.4954     0.5046     0.5020     0.4980     0.4903     0.5097     0.6672     0.3328     0.5067     0.4933     0.6050     0.3950\n          Atomicconcreference         0.5000     0.5000     0.5000     0.5000     0.6667     0.3333     0.5000     0.5000     0.5000     0.5000     0.5000     0.5000     0.5000     0.5000     0.6667     0.3333     0.5000     0.5000     0.6000     0.4000\n\n                                                                                          1.5    0.09    -0.11   1.6    -1.1   1.5    -0.63        Norm-concRDEV%   -2.1    0.92    -0.80    0.46    -2.0    0.89    0.03    -0.02    -1.4    0.38    0.58    -0.4    -2.4\n\n          mass\n           Normal-izedconc         0.3012     0.6988     0.3612     0.6388     0.2996     0.7004     0.3629     0.6371     0.2112     0.7888     0.2775     0.7225     0.3720     0.6280     0.5331     0.4669     0.4059     0.5941     0.3050     0.6950\n\n   %\n                       -6.5    -3.6   2.2   3.5    -7.9    -5.2    -6.8    -6.9    -0.14   1.7    0.04    -0.79    -3.1    0.69    -5.6    -5.8   1.5    -1.1   8.3   6.1     Raw-concRDEV\n\n           DTSA_IIUnc_Budget          \u00b10.0023      \u00b10.0043      \u00b10.0177      \u00b10.0054      \u00b10.0165      \u00b10.0165      \u00b10.0202      \u00b10.0086      \u00b10.0086      \u00b10.0159      \u00b10.0029      \u00b10.0026      \u00b10.0043      \u00b10.0022      \u00b10.0240      \u00b10.0011      \u00b10.0047      \u00b10.0023      \u00b10.0103      \u00b10.0370\n\n     Rawmassconc         0.2876     0.6673     0.3720     0.6579     0.2815     0.6581     0.3380     0.5933     0.2139     0.7989     0.2760     0.7184     0.3691     0.6232     0.5028     0.4403     0.4055     0.5936     0.3256     0.7419\n\n        total\n     Raw                  0.9549     0.9549     1.0299     1.0299     0.9395     0.9395     0.9312     0.9312     1.0128     1.0128     0.9944     0.9944     0.9923     0.9923     0.9431     0.9431     0.9991     0.9991     1.0675     1.0675\n\n             Standard                              Ca5(PO4)3F    GaAS   GaP  Sb    SiO2  Ge  Ge  Te   MgO  Ni  Se    PbTe  Te    PbSe   NiO  Si  Se  Sn   MgO  Fe\n\n\n     keV                                                   6,615,542        6,615,542        5,581,455        5,581,455        6,110,745        6,110,745        5,500,042        5,500,042        5,846,515        5,846,515        6,608,981        6,608,981        5,606,222        5,606,222        5,109,005        5,109,005        5,447,221        5,447,221        4,963,883        4,963,883        0.1-5counts\n\n                                                                 Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019         Bruker2019                Analyticalplatform                      JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-         JEOL8500f-\n          conc\n        Knownmass             0.3076     0.6924     0.3641     0.6359     0.3058     0.6942     0.3628     0.6372     0.2142     0.7858     0.2759     0.7241     0.3811     0.6189     0.5326     0.4674     0.3995     0.6005     0.3006     0.6994\n\n      Ele-ment  P  Ga  Ga  Sb O  Ge  Ge  Te O  Ni  Se  Pb  Te  Pb O  Si  Se  Sn O  Fe\n             Materialnumber    39  39  40  40  41  41  42  42  43  43  44  44  45  45  46  46  47  47  48  48\n\n\u2009continued             Material                        GaP_5keV       GaP_5keV        GaSb_5keV        GaSb_5keV        GeO2_5keV        GeO2_5keV       GeTe_5kV       GeTe_5kV       NiO_5keV       NiO_5keV       PbSe_5kV       PbSe_5kV       PbTe_5kV       PbTe_5kV       SiO2_5kV       SiO2_5kV       SnSe_5kV       SnSe_5kV        Fe2O3_5kV        Fe2O3_5kV\nTable\u202f1\u2002 Row      81  82  83  84  85  86  87  88  89  90  91  92  93  94  95  96  97  98  99   100  J Mater Sci (2024) 59:19088\u201319111                                                                19095\n\n\n\n\n\n   %\n                 1.2    -0.11    -2.6    0.90    -1.2   3.8    -1.1   3.6    -0.58    0.11    -3.0    1.10    0.24    -2.7    -0.01    0.21   3.3    -1.2   3.2    -1.1        Atom-concRDEV\n\n          Atomicconc             0.0858     0.9142     0.2471     0.7529     0.7500     0.2500     0.7611     0.2389     0.1532     0.8468     0.2666     0.7334     0.9197     0.0803     0.9527     0.0473     0.2744     0.7256     0.2580     0.7420\n          Atomicconcreference         0.0848     0.9152     0.2538     0.7462     0.7591     0.2409     0.7693     0.2307     0.1541     0.8459     0.2748     0.7252     0.9175     0.0825     0.9528     0.0472     0.2656     0.7344     0.2500     0.7500\n\n                 1.2    -0.05    -2.7    0.82    -2.4   2.5    -2.2   2.3    -0.65    0.05    -3.1   1.0    0.64    -2.3     -0.020    0.15   3.7    -0.84   3.6    -0.67        Norm-concRDEV%\n\n          mass\n           Normal-izedconc         0.0412     0.9588     0.2245     0.7755     0.4942     0.5058     0.5053     0.4947     0.0768     0.9232     0.2435     0.7565     0.7879     0.2121     0.8655     0.1345     0.2589     0.7411     0.1609     0.8391\n\n   %\n                                                                                     6.4   3.3   2.9   3.1    27.1    21.5   8.6   6.2                                                     0.24   5.3    -1.6   3.0   4.1   4.9   7.6    12.2                 7.1\n\n## 2. newbury2024testingtheaccuracy pages 22-24 (Context ID: pqac-00000034)\n\n  nential dependence of X-ray absorption on the path\n\n\n\n\n\nFigure 5\u2002 \u2009NiTi measured at \u00adE0 = 15 keV (red) and peak fitting residual spectrum (blue).19108                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\n\n\n\nFigure 6\u2002 \u2009NiTi measured at \u00adE0 = 10 keV (red) and peak fitting residual spectrum (blue).\n\n\n\n\n\nFigure 7\u2002 \u2009NiTi measured at \u00adE0 = 5 keV (red) and peak fitting residual spectrum (blue). J Mater Sci (2024) 59:19088\u201319111                                                                19109\n\n\n\n\n\nFigure 8\u2002 \u2009NiTi: a comparison of peak fitting residual spectra measured at \u00adE0 = 15 keV (red), 10 keV (blue) and 5 (keV (green); b all\npeak fitting residual spectra scaled to the region 1.1 keV \u2013 1.2 keV (yellow).\n\n                                                        of the X-ray absorption edge structure that exists\n                                              under the characteristic X-ray peaks. As the beam\n                                                 energy is reduced, the beam penetrates the sample\n                                                             less and the generated Bremsstrahlung X-rays pass\n                                               through less material and fewer are absorbed on\n                                                         either side of the absorption edge. The magnitude\n                                                         of the edge structure is a function of the magnitude\n                                                         of the absorption which will be lower due to shorter\n                                                    absorption path length at lower beam energies. The\n                                                           result is a less distinctive absorption edge structure\n                                             which is easier for the peak fitting process to han-\n                                                            dle. This absorption structure is more complex for\n                                                     the multi-edge L-family and M-family X-rays that\n                                            must be used in low-beam-energy operation. The\n                                                             effect of lowering the beam energy on the quality\n                                                         of the peak fitting is shown in Figures 5, 6, 7, and 8\n                                                           for the intermetallic compound NiTi. The \u201cpeak fit-Figure 9\u2002 \u2009Histogram of the raw analytical total (mass concentra-\n                                                        ting residual spectrum\u201d at \u00adE0 = 5 keV shows muchtion) from DTSA-II for \u00adE0 = 5 keV.\n                                                reduced structure around the absorption edge ener-\n                                                       gies for the Ti L-family and the Ni L-family com-\nlength, the absorption correction is reduced, leading    pared to the residuals at \u00adE0 = 15 keV and \u00adE0 = 10 keV.\nto reduced RDEV. A second advantage of reducing    Moreover, the residual spectrum at \u00adE0 = 5 keV shows\nthe self-absorption of X-rays by operating at low    a physically realistic X-ray continuum background\nbeam energy is the reduction in the relative height     after stripping the characteristic X-ray peaks, while\n                                                     the residual spectra at \u00adE0 = 15 keV and \u00adE0 = 10 keV19110                                                                                                J Mater Sci (2024) 59:19088\u201319111\n\n\ninclude ranges of non-physical zero intensity in the    be differences in the conductive coatings applied to\nX-ray continuum. While the residual is a very use-    insulating materials. It should be noted, however,\nful tool for evaluating the spectrum fit process, it    that normalization of the raw mass concentrations\nshould always be remembered that the residual is    or calculation of atomic concentrations from the\na somewhat artificial construct. The residual rep-   raw mass concentrations compensates for the sig-\nresents an estimate of the continuum signal in the     nificant deviation of the analytical total from unity.\nunknown which is computed by subtracting, from   An additional factor that can affect low-beam-energy\nthe unknown spectrum, the characteristic intensity    analysis is the effect of electron channeling on the\nextracted from the standard spectrum multiplied by     characteristic X-ray emission, as reported by Meisen-\nthe k-ratio. The quality of the residual depends on    kothen et al. [16]. Differences between the sample\nmany factors including the quality of the modeling   and the standards in the removal of surface damage\nof the continuum (and thus the characteristic-only    that arises from mechanical polishing, which modi-\nintensity) in the standard, differential absorption     fies the degree of electron channeling, can influence\nof the various lines in the peak in the standard and    the analytical total.\nsample and bonding-induced shifts in characteristic       Finally, it must be remembered that the materi-\nX-ray energies.                                             als whose compositions were measured as challenge\n   If the same low-energy lines we selected at 5 keV    specimens to produce the RDEV histogram of Fig-\nhad been used at higher beam energies, we would    ure 3 were carefully examined to exclude those mate-\nexpect to see less accurate results. These lines can be     rials with unacceptably thick surface layers which\nused at low beam energies, where the beam does not   would significantly compromise the measured com-\npenetrate deep into the sample leading to a relatively    position. Thus, when considering the accuracy of\nsmall absorption correction despite the large mass    low-beam-energy microanalysis applied to the anal-\nabsorption coefficients typically associated with low-    ysis of practical materials, it should be noted that\nenergy X-rays. At higher beam energies where the    the reality of the sample condition that the analyst is\nbeam penetrates deeper, the absorption correction     likely to encounter on an unknown may significantly\nand the associated uncertainty are larger resulting in    compromise the accuracy that is achievable. In par-\nsignificantly poorer measurements. This is particularly     ticular, the analyst may encounter a surface layer,\ntrue for the L-lines of transition metals in which the   due to environmental reactions such as oxidation or\nL2-M2 transition is well known to show anomalously     sulfidation, whose thickness is a substantial fraction\nlarge self-absorption in pure metals [12\u201314].              of the electron range. This situation creates a com-\n  The raw analytical total, which is the sum of the    posite specimen where the interaction volume of the\nmeasured mass concentrations for all constituents,   beam effectively samples two or more different mate-\nincluding any such as oxygen calculated by the     rials. The basic assumption of the k-ratio protocol\nmethod of assumed stoichiometry, is a useful inter-     for quantitative analysis is that the excited volume\nnal consistency indicator in the conventional beam     is uniform in composition. When this condition is\nenergy analysis regime, where the raw analytical    not met, substantial error is likely to occur. Robust\ntotal typically lies within the range 0.98\u20131.02 [15].    analytical practice should include careful examina-\nA deviation in the raw analytical total significantly    tion for the possibility of such surface anomalies\nbelow 0.98 is likely to be an indication that an ele-    by measuring spectra by sequentially lowering the\nment is present in the material that is not included   beam energy from a starting value in the \u201cconven-\nin the element suite for the analysis, which can be a    tional\u201d range, \u00adE0 \u2265 10 keV, down into the low-beam-\nvaluable tool for the analyst. The histogram of raw    energy regime, \u00adE0 \u2264 5 keV, which can reveal surface\nanalytical totals observed at \u00adE0 = 5 keV in this study,    anomalies, as illustrated in Figure 1.\nas shown in Figure 9, reveals a much broader range.\nAlthough the majority of analytical totals cluster\naround unity, totals as low as 0.8 and as high as 1.2   Funding\u2003\nare encountered, despite the careful vetting of the\nmaterials for surface anomalies. The source of this   Open access funding provided by the National Insti-\nmuch broader range of analytical totals is likely to     tutes of Health. This study was funded by National\n                                                              Institute of Standards and Technology. J Mater Sci (2024) 59:19088\u201319111                                                                19111\n\n\nData availability\u2002                                                     [ 7]  Ritchie N, Filip V (2011) Semantics for high speed aut\n\n## 3. goldstein2018energydispersivexray pages 18-20 (Context ID: pqac-00000035)\n\n   current. Measure and record the probe current using the\n                                                                    Faraday cup and the picoammeter.\n                                                                                    4. Collect a 60 live-time second spectrum from the copper\n                                                                        sample.\n                                                                                    5. Increase the probe current through a sequence of\n      . .\u200a\u200a\u200aFig. 16.21\u2003 The spectrum image was collected on a 128 by 128          approximately 10\u201320 steps from the initial probe current\n             pixel grid representing 4\u2009\u00d7 4 mm. After data rotation to view the x-y         to approximately 2 times the optimal probe current.\n             plane, the first energy slice, 1 out of 1024, is shown. It appears black         Collect a 60 live-time second spectrum at each probe\n           because it contains no counts                                       current and measure and record the probe current using\n                                                                         the Faraday cup. A plot of such a measurement sequence\n                                                                                                  is shown in .\u2003 Fig. 16.23 (upper).\n                                                                                    6. Integrate the total number of counts in the range of\n                                                                      channels representing the Cu K-L2,3 characteristic peak.\n16                                                              (You don\u2019t need to background correct the integral.) Plot\n                                                                         the measured intensity divided by the probe current\n                                                                            against the measured probe current. The result should\n                                                                 be a horizontal line, as shown in .\u2003 Fig. 16.23 (lower).\n                                                                                       1.  If the line is not horizontal, the problem may be in the\n                                                                              detector or in the probe current measurement.\n                                                                                       2. The probe current measurement could be non-linear\n                                                                meaning the plot of the measured probe current to\n                                                                              true probe current is not a straight line.\n                                                                                       3.  Alternatively, the probe current may have a zero\n                                                                                              offset. The zero offset can be measured by blanking\n                                                                            the beam and recording the measured current at zero\n      . .\u200a\u200a\u200aFig. 16.22\u2003  Extracting the Cu L-family lines from the spectrum              true current. Subsequent probe current measurement\n            planes 89 to 97                                                can be offset by this value.\n\n         probe current, due to the loss of useful electrons during the\n          dead-time.                                                   16.3.6\u2002 Energy Calibration Linearity\n                   It is very important for accurate quantitative analysis that\n          the measured X-ray intensity is linear with respect to the   Consistent energy  calibration  is  critically important  for\n            effective probe dose. Twice the effective probe dose should   reproducible quantitative analysis. Pick a nominal channel\n         produce twice the measured  intensity. Not only  is  this  width (5-eV/channel will work fine in almost all cases) and                                                                                                        227                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n. .\u200a\u200a\u200aFig. 16.23\u2003 The number of\nX-rays recorded in the spectrum             3,000,000\nshould scale linearly with the                                      f(x) = 35876.1202787172x\ndose (the product of live-time                          R2 = 0.9999923818\nand probe current)                         2,500,000\n\n                                         2,000,000\n\n\n                                         1,500,000                                                                                        Counts                                                                   Det 2\n                                         1,000,000                                                                   Linear (Det 2)\n\n\n                                         500,000\n\n\n                                           0\n                                            0    10   20   30   40   50   60   70   80   90\n                                                              Probe dose (nA.s)\n\n\n                                      36,050\n\n                                      36,000\n                                      35,950\n\n                                      35,900\n\n                                      35,850                                                                                      (nA.s)\n              / 35,800\n                                      35,750                                                                Det 2                                                                                      Counts\n                                      35,700\n\n                                      35,650\n                                      35,600\n\n                                      35,550\n                                         0        0.2       0.4        0.6       0.8       1        1.2       1.4\n                                                                 Probe current (nA)\n\n\n\nuse this value for all your data acquisition. Before each day\u2019s   energy. Two points are sufficient to unambiguously calibrate\nmeasurements ensure that the detector is calibrated consis-   a linear function. The calibration (peak position) and resolu-\ntently by following the same protocol to check and, if neces-   tion (peak shape) should be constant with input count rate\nsary, recalibrate your detector.                                 (or dead-time), as shown in .\u2003 Fig. 16.24.\n  On a modern pulse processor, calibration is usually per-     To a very high degree, modern EDS detectors are linear.\nformed using the EDS vendor\u2019s software. The software will  However if you look carefully in the mid-range of energies,\nprompt you to collect a spectrum from an established mate-  you many notice the KLM markers may be misaligned by a\nrial. The software will examine the spectrum and extract the   channel or two. This is evidence that your detector is not per-\npositions of various characteristic X-ray features. The soft-   fectly linear but this need not represent a true performance\nware will then perform an internal adjustment to center these   problem.\nfeatures in the correct channels. Most modern pulse proces-      Since energy calibration is so critical but is also one of\nsors perform a continuous zero offset calibration using a  many parameters that should be measured as part of a com-\n\u201czero strobe pulse\u201d the pulse processor adds to the signal   plete EDS Quality Control (QC) program, the validation will\nstream for diagnostic purposes. Thus the only parameter  be discussed in a later section.\nthey usually adjust when performing a calibration is an elec-\ntronic gain. Usually, this involves identifying a single high\nenergy characteristic line (like the Mn K-L2,3 or the Cu K-L2,3)   16.3.7  Other Items\nand adjusting the gain until this feature is centered on the\nappropriate channel. The calibration is thus a two-point cali-   zz  Light Transparency and IR Cameras\nbration\u2014either a low energy characteristic line or the zero  Most (but not all) modern EDS detectors have a vacuum\nstrobe at low energy and a second characteristic line at high   tight window that is opaque to infrared and visible light.          228    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.24\u2003 The position and\n           widths of the characteristic peaks\n           should not vary with probe cur-\n             rent                               15 000\n\n                                                                                                                 Counts 10 000\n\n                                             5 000\n\n\n\n                                                0\n                  \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035]\n\nStatus: Paper Count=30 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=36 | Current Cost=$0.1744 | Disease-Target Evidence=0",
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+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035]\n\nStatus: Paper Count=30 | Relevant Papers=9 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=36 | Current Cost=$0.1744 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036]\n\nStatus: Paper Count=30 | Relevant Papers=10 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=37 | Current Cost=$0.1839 | Disease-Target Evidence=0",
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+                "content": "## 1. giunto2025harnessingautomatedsemeds pages 4-6 (Context ID: pqac-00000037)\n\nnd lab-synthesized samples of known compositions spanning elements from nitrogen to bis-\n 66  muth, AutoEMXSp achieves atomic fraction measurements with relative deviations typically below 5\u201310%\n 67  and resolves minor or intermixed phases with high con\ufb01dence. This study lays the groundwork for fully\n 68  automated, high-throughput SEM-EDS compositional analysis of as-deposited powder materials, paving\n 69  the way for its integration into modern autonomous laboratories for accelerated materials discovery and\n 70  optimization.\n\n71 2 Results\n\n72  2.1 Framework for automated powder compositional analysis\n\n 73  Fully automated compositional analysis of as-deposited powders is achieved through a framework consisting\n 74  of four primary components: (1) autonomous SEM particle localization and EDS spectra acquisition, (2)\n 75  accurate EDS quanti\ufb01cation, (3) automated \ufb01ltering of unreliable measurements, and (4) machine learning-\n 76  based analysis of the resulting compositional data. This framework is implemented in a Python-based\n 77  software package, AutoEMXSp (Automated Electron Microscopy X-ray Spectroscopy), and demonstrated\n 78  on a cost-e\ufb00ective desktop SEM-EDS system (Thermo\ufb01sher Phenom XL G2). We present the AutoEMXSp\n 79  work\ufb02ow, schematized in Fig. 1 and described in detail in the Methods.\n 80    AutoEMXSp requires only two inputs (Fig. 1a): the sample position on the microscope stage, and the set\n 81  of elements present in the sample. Optionally, the user may provide candidate phase compositions, whose\n 82  presence is then evaluated by direct comparison with the measured compositions in the \ufb01nal step of the\n 83  work\ufb02ow.\n 84      1. Autonomous EDS acquisition. Operation begins once a powder sample is dispersed onto a carbon\n 85  tape (C-tape) stub and loaded into the SEM. AutoEMXSp \ufb01rst detects the C-tape region (Fig. 1b) and\n 86  subdivides it into a grid, with each tile de\ufb01ning a stage position for particle search. Particles are segmented\n 87  by intensity thresholding of SEM images and \ufb01ltered by size (Fig. 1c), favoring those larger than 2 \u00b5m to\n 88  reduce the mass e\ufb00ect illustrated in Extended Data Fig. 1. For each randomly-selected particle, up to \ufb01ve\n 89  EDS spot spectra are acquired (Fig. 1d); points are spaced su\ufb03ciently far apart to avoid X-ray generation\n\n\n                                                   2 90  volume overlap and are selected away from edges to minimize substrate signal contamination. Typically,\n 91  one hundred spectra of 50,000 counts each are collected per sample, with total acquisition times ranging\n 92  from 20 to 45 minutes.\n\n\n   AutoEMXSp           b C-tape detection          c   Particle localization\n\n     a       Stub position: (x, y)\n                                 Input\n         Elements: In, O\n\n       (Cnd. phases: In2O, In2O3)                                                                                               50 \u03bcm\n\n\n\n    g Cluster analysis              f  Filtering           e EDS          d Spot selection\n\n     O\n                                        Substrate signal\n                     p1                     contamination\n                                      Excessive X-ray\n                                                                                      wIn: 83%\n                        p2                  absorption\n                                                                  wO: 16%                                    Poor fit\n                                     High analytical                                          5 \u03bcm\n                                   In                 total error\n\n\n                h         In (at%)  O (at%)    Cnd. phases\n                                                    Phase composition      Output               p1 40.2\u00b10.5  59.8\u00b11.1 \u2192 In2O3 (CS: 98%)\n                                                                        identification\n                             p2 67.5\u00b10.8  32.5\u00b11.3 \u2192 In2O (CS: 93%)\n\n     Fig. 1: AutoEMXSp work\ufb02ow for powder compositional analysis. Operation begins after the\n     sample is loaded into the SEM. (a) The only required inputs are the SEM stub coordinates on the stage\n     and the elements present in the sample; optionally, the user may also provide candidate phase compositions\n     expected in the material. Automated EDS spectra acquisition is performed through (b) C-tape detection\n     and subdivision into frames, (c) particle segmentation and localization, and (d) selection of positions for\n    EDS spot measurements on individual particles. (e) The acquired spectra are \ufb01tted, and the composition\n      at each spot is quanti\ufb01ed in terms of elemental mass fractions wi. (f) Compositional data are \ufb01ltered, and\n     (g) analyzed using a k-means clustering algorithm to (h) identify the number and composition of phases\n      present in the sample.\n\n\n\n\n 93      2. Particle spectra quanti\ufb01cation. For each acquired EDS spectrum, AutoEMXSp quanti\ufb01es local\n 94  composition in the form of elemental mass fractions wi (Fig. 1e), using a modi\ufb01ed peak-to-background\n 95  (P/B) method to correct for geometry-induced artifacts. Conventional EDS quanti\ufb01cation of wi assumes\n 96  that measured peak intensities originate from a \u2018bulk\u2019 sample\u2014i.e., \ufb02at, su\ufb03ciently large to fully contain\n 97  the X-ray generation volume. In contrast, the P/B method exploits the fact that, to \ufb01rst order, the P/B\n 98  ratio of intensities is independent of geometry and thus approximately equal for particle and bulk samples\n 99  of identical composition [20, 27]:\n\n                                                           Pi,p100                                           \u2243Pi,b                                              (1)\n                                                       Bi,p    Bi,b\n\n101  Here, P and B denote peak and background intensities, with subscripts p and b referring to particle and\n102  bulk spectra, respectively. Rearranging Eq. (1) yields a geometry-corrected, bulk-equivalent peak intensity\n\n\n                                                   3103  (I\u2217i ) suitable for conventional quanti\ufb01cation models developed for bulk, polished samples:\n\n104                                          I\u2217i = Pi,b \u2243Pi,p  \u00b7 Bi,b                                        (2)\n                                                              Bi,p\n\n\n105  While Pi,p and Bi,p are extracted directly from the measured particle spectrum, Bi,b\u2014the background\n106  intensity for a hypothetical bulk sample of identical composition\u2014is unknown and must be estimated.\n107      Pi,p can be accurately obtained through Gaussian \ufb01tting of characteristic peaks. In contrast, extracting\n108  Bi,p is more challenging due to the often complex background shape underneath the peaks, in\ufb02uenced by\n109  X-ray absorption edges and detector artifacts\u2014particularly below 2 keV, as shown in Extended Data Fig. 2.\n110  In spectra with fewer than several hundred thousand counts, the background signal is low and su\ufb00ers from\n111  poor signal-to-noise; this makes Bi,p prone to \ufb01tting errors that propagate directly into the computed P/B\n112  ratio and ultimately to the quanti\ufb01ed elemental compositions. Accurate modeling of the background shape\n113   is therefore essential to the P/B method. To this end, AutoEMXSp employs physically and empirically\n114  grounded models that account for continuum X-ray generation [32, 33], X-ray absorption [34\u201336], electron\n115  backscattering [37], and detector response function [38]. We further introduce two key re\ufb01nements: a revised\n116  absorption model that captures the geometry-dependent X-ray path lengths within particles (Extended\n117  Data Fig. 3), and an attenuation term that avoids overestimation of continuum X-rays at low energies\n118  (E < 1 keV) for heavy elements (Extended Data Fig. 4). These re\ufb01nements enable signi\ufb01cantly more\n119  accurate determination of Bi,p in particle EDS spectra and, critically, the quanti\ufb01cation of light elements\n120  with low-energy characteristic X-rays, such as N, O and F.\n121     Another key challenge in applying the P/B method lies in the accurate estimation of Bi,b. This quantity\n122   is typically derived from an empirical model for continuum X-ray generation fB, expressed as Bi,b(E) =\n123  fB( \u00afZ, E), where fB  is a function of energy E and the sample\u2019s average atomic number \u00afZ [27, 28, 39].\n124  However, we \ufb01nd that commonly employed empirical formulations of fB, introduced in Refs. [32, 40\u201342],\n125  have been obtained neglecting the e\ufb00ect of the electron stopping power (S), which governs energy dissipation\n126  of the incident electron beam and strongly depends on \u00afZ. This omission introduces substantial errors in\n127  the estimation of Bi,b when the compositions of the standard and the measured sample di\ufb00er signi\ufb01cantly\n128  (see Extended Data Fig. 5), likely explaining why previous implementations of the P/B method relied\n129  on compositionally matched standards [24\u201326]. Instead, we incor\n\n## 2. giunto2025harnessingautomatedsemeds pages 7-10 (Context ID: pqac-00000038)\n\ny Fig. 7\n 200  and 8). Elemental frequency across all samples is shown in Fig. 3a; the benchmark compositions span 38\n 201  elements, ranging from nitrogen (Z = 7) to bismuth (Z = 83), primarily consisting of oxide, phosphate,\n 202  and silicate chemistries. For each element, standard reference P/B values were obtained from bulk polished\n 203  samples of the pure metallic form when available, or otherwise from simple binary or ternary compounds.\n 204  The accuracy of AutoEMXSp is quanti\ufb01ed using the relative deviation from expected value (RDEV ) of the\n 205  measured elemental atomic fraction (ni):\n\n                                                         ni \u2212ni,nominal\n 206                         RDEV =                                                       (3)\n                                                               ni,nominal\n\n\n                                                    5                   a      Single-phase wulfenite (PbMoO4)\n\n\n\n\n\n                                       PbMoO4\n\n\n\n                    Pb (at%) Mo (at%) O (at%) dRMS(at%) Cnd.   CScnd\n                         16.9\u00b11.2  16.1\u00b10.8  67.0\u00b11.5    2.1  PbMoO4  0.97\n\n\n                 b                Intermixed\n                                NaAlSiO4 + LiMn1.5Ni0.5O4\n\n\n\n\n                                 NaAlSiO4\n                                                           LiMn1.5Ni0.5O4\n\n\n\n\n\n                           Si (w%)  Mn (w%) O (w%) dRMS(w%)  Mixture   CSmix\n                         11.8\u00b13.3  22.6\u00b19.0  37.6\u00b12.5  10.8   NaAlSiO4 +  0.83\n                                                                              LiMn1.5Ni0.5O4\nFig. 2: Examples of AutoEMXSp compositional analyses. 3D plots of AutoEMXSp compositional\nmeasurements for (a) a single-phase wulfenite mineral (PbMoO4) and (b) a (sub)micron-scale two-phase\nmixture of NaAlSiO4 and LiMn1.5Ni0.5O4 [46]. Axes represent elemental (a) atomic or (b) mass fractions of\nthe plotted compositions (green dots = valid compositions; black triangles = discarded compositions). Clus-\nter centroids, indicating the average composition within each cluster, are marked by red crosses. The light\nred uncertainty ellipsoid represents the standard deviations of elemental fractions (\u03c3i), with principal axes\nlengths equal to 2\u03c3i. The tables summarize the measured compositions and the RMS of point-to-centroid\ndistances (dRMS), along with the corresponding phase or phase mixture identi\ufb01ed by AutoEMXSp, and the\nassociated con\ufb01dence scores (CScnd for single candidate phases, CSmix for two-phase mixtures). In (b), a\nsubset of three elemental mass fractions is displayed, su\ufb03cient to illustrate the large standard deviations\ncharacteristic of mixed-phase measurements. Full measurements are reported in Supplementary Fig. 3a.\nDiscarded compositions are omitted from this panel for clarity. The 2D projection onto the Si-Mn plane\nfacilitates visualization of the compositional measurements in a two-phase mixture as a linear combination\nof the two parent phase compositions.\n\n\n\n\n\n                                              6207  where ni,nominal represents the atomic fraction extracted from the nominal compound stoichiometry. Each\n208  acquired spectrum thus yields multiple RDEV values\u2014one per element detected. With the P/B method,\n209  composition measurement errors may stem from imprecise \ufb01tting, substrate signal contamination, and\n210  inherent limitations of the P/B approximation.\n211      Fig. 3b reports the distribution of 8226 RDEV values obtained from all 2483 individual spectra retained\n212  after AutoEMXSp \ufb01ltering, showing that 61.3% (84.4%) of the measured ni exhibit RDEV < 5% (10%). A\n213  non-negligible tail with RDEV > 10% highlights the risk of outlier-driven errors when only a few spectra\n214  are analyzed per sample. Substantially improved measurement accuracy is achieved by extracting atomic\n215  fractions at the cluster centroids (Fig. 3c), where 75.8% (93.6%) of RDEV values fall below 5% (10%). This\n216  improvement underscores the advantage of the AutoEMXSp strategy, which aggregates multiple spectra in\n217  clusters to average their compositions, mitigating random variability and yielding more reliable estimates.\n218  Furthermore, we highlight that the 73 RDEV values obtained from low-Z elements (N, O, F; lighter color-\n219  ing) follow similar accuracy trends as heavier elements. We note that analogous trends were observed when\n220  analyzing separately the three groups of samples\u2014i.e, minerals, commercial powders and lab-synthesized\n221  materials (Extended Data Fig. 7).\n\n\n    a\n\n\n\n\n\n         All valid spectra post-filtering          Cluster centroids                Cluster centroids\n         b                 N,O,F        c                        d          RDEV > 10%\n                                Other\n                              elements\n           61.3%                        75.8%                         71.2%\n                          84.4%                        93.6%                          90.3%\n\n\n\n\n\n     Fig. 3: Performance of AutoEMXSp benchmarked on single-phase powder samples. a, Peri-\n      odic table showing the frequency of each element\u2019s occurrence across all 74 analyzed samples; generated\n     using pymatviz [48]. b, Histogram of elemental atomic fraction (ni) relative deviation from expected value\n    (RDEV ) measured in all 2483 spectra retained after AutoEMXSp\u2019s \ufb01ltering step. Light-colored counts\n      highlight measurements of low-Z elements (N, O, F). Dark and light green bands indicate values within 5%\n     and 10% relative deviation, respectively; labeled percentages report the fraction of values in each range. c,\n     Histogram of RDEV values for ni measured at cluster centroids. d, Histogram of absolute deviation from\n     expected values (ADEV s) for centroid compositions; purple counts denote ni with RDEV > 10%. Dark\n     and light green bands indicate values within 1 at% and 2 at%, respectively.\n\n\n\n222     Absolute deviations from the expected value (ADEV , de\ufb01ned as = ni \u2212ni,nominal) for centroid com-\n223  positions are shown in Fig. 3d, with 71.2%/90.3%/95.8% of values measured within 1/2/3 at%, indicating\n\n\n                                                   7 224  generally modest absolute errors. Typically, ADEV values are larger for binary compounds, as discussed\n 225  in Extended Data Fig. 8. In Fig. 3d, we highlight that among the 15 reported centroid ni values with\n 226 RDEV > 10% (purple counts), 12 have ADEV < 1 at%, suggesting that large relative errors primarily\n 227  occur at low concentrations (< 10 at%) where absolute deviations remain small. Finally, we assess the\n 228  measurement uncertainty delivered by AutoEMXSp for single-phase samples. Excluding lab-synthesized\n 229  materials to minimize the in\ufb02uence of compositional inhomogeneity (Extended Data Fig. 9), we \ufb01nd that\n 230  48.1% (91.2%) of measured ni exhibit standard deviations \u03c3i < 1 at% (< 2 at%), corresponding to relative\n 231  uncertainties below 5% (10%) in 66.2% (95.6%) of cases, as shown in Extended Data Fig. 9.\n 232      Overall, the results demonstrate high compositional measurement accuracy for single-phase samples,\n 233  providing robust experimental data for ML-based analyses to resolve phase compositions in multi-phase\n 234  materials.\n\n 235  2.3 Versatility across compositionally complex and diverse powders\n\n 236  The proposed framework enables composition analysis across a broad spectrum of powder samples, spanning\n 237  signi\ufb01cant diversity in phase content and chemistry. Representative examples are illustrated in Fig. 4.\n 238  Owing to its re\ufb01ned spectral \ufb01tting routines and standard-based EDS quanti\ufb01cation, AutoEMXSp can\n 239  accurately measure complex multi-element compositions, such as the K-412 NIST standard (Fe: 3.1 at%, Mg:\n 240  10.6 at%, Ca: 6.0 at%, Al: 4.0 at%, Si: 16.8 at%, O: 59.4 at%; Fig. 4a), where peak overlapping complicates\n 241  accurate background \ufb01tting (Extended Data Fig. 2). The method also remains e\ufb00ective in the presence of\n 242  undetectable elements in low weight fraction, such as Li in Li3NiCoMnO6 (Fig. 4b).\n 243    The high measurement accuracy of AutoEMXSp enables the identi\ufb01cation of distinct phases with simi-\n 244   lar compositions within multi-phase samples. This is demonstrated in Fig. 4c, where a three-phase mixture\n 245  of MnO, Mn2O3, and Fe2O3 is correctly resolved despite the presence of chemically similar input candi-\n 246  date compositions such as MnO2, Mn3O4, and FeO. The close compositional proximity of Mn3O4 to the\n 247  green cluster centroid reduces the con\ufb01dence score (CScnd) for Mn2O3 (see Methods), yet the correct phase\n 248  composition is identi\ufb01ed. Additionally, a key strength of AutoEMXSp lies in its sensitivity to minority\n 249  phases. By employing the k-means clustering algorithm, which is density-independent, clusters consisting\n 250  of as few as one or two points can be isolated, enabling identi\ufb01cation of phases present \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=39 | Current Cost=$0.1839 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "## 1. dumit2025challengesandfuture pages 9-10 (Context ID: pqac-00000036)\n\nmputational modeling requires measures to ensure     als\u2019 physicochemical characterization.[111] Similarly, as the CRED                                            Conditions\nthe reliability and predictivity of its output. In the past years, the    evaluation method lacks nano-speci\ufb01c guidance, particularly for\nnanosafety \ufb01eld has served as a testing ground for the develop-    evaluation of ecotoxicity studies, the nanoCRED criteria were\nment of data-driven prediction models, leading to the creation of    developed[112] and implemented in the Science in Risk As-\nmore re\ufb01ned and detailed scoring concepts. The Klimisch score   sessment and Policy (SciRAP) project as a basis for judging\nrepresented the foundation for these developments, incorporat-   whether a study is adequate for chemical risk assessment.[11]\ning nano-speci\ufb01c criteria, as will be discussed in the following   In addition, the SciRAP in vitro  tool[113] was extended with\nsections.                                                        nanomaterial-relevant criteria, covering 38 criteria for report-\n                                                              ing quality, 19 criteria for methodological quality, and 4 guid-\n                                                           ance items to evaluate relevance. It supports harmonized eval-\n5.2. Nanomaterial-Speci\ufb01c Quality Criteria                         uation of nanomaterial in vitro toxicity studies and promotes                                                                   transparent, structured use of such data in the regulatory hazard                                                                                                                                                                                                                                              (https://onlinelibrary.wiley.com/terms-and-conditions)\nDi\ufb00erent  activities  for evaluating and labeling data  quality    assessment.[11]                                                             on\nhave been initiated. The Nanomaterial Data Curation Initia-     The development of data quality scoring systems has been an                      Wiley\ntive (NDCI), a project of the National Cancer Informatics Pro-    iterative process with many frameworks interlinked and build-                          Online\ngram Nanotechnology Working Group (NCIP NanoWG), ex-   ing upon one another (Figure 2). Card & Magnuson (2010)[114]\nplores the di\ufb00erent aspects of data curation within the de-   published a two-step method to assess the quality of studies ex-                               Library\nvelopment of informatics approaches to understanding nano-   amining the toxicity of nanomaterials, by using ToxRTool[101] to             for\n                                                                                                                                                                                                                                                                                                                                                                                 rulesmaterial behavior.[104] The initiative has published a series of   rank study reliability based on the adequacy of design, docu-\n                                                                                                                                                    of\narticles, one of which focuses on data quality and complete-   mentation of methods, materials, and results, and by determin-                  use;\nness as critical sub-topics in nanomaterial data curation.[9] An-   ing the completeness of physicochemical parameters being in-         OA\nother initiative is the establishment of the European Registry    vestigated. Building on this foundation, an approach to evaluate                                   articles\nof Materials.[105,106] Existing metadata reporting standards sup-   nanomaterial data quality was developed in the H2020 project             are\nport the documentation of experimental conditions and protocols   GUIDEnano.[115] This method aimed to minimize reliance on ex-\nfor bio-nano studies (MIRIBEL[107]) and material characteristics    pert judgement by modifying 1) the ToxRtool to evaluate the qual-                                   governed\n(MINChar[108] and MIAN[109]), as well as reporting focused on     ity of both human toxicity and ecotoxicity studies, and 2) the study         by\nspeci\ufb01c experiments such as nanomaterials protein corona deter-    of Langdon et al.,[116] which is adapted to all the environmental             the\nmination (MINBE[110]). Additionally, a NanoTox Metadata List[39]   compartments. Based on the GUIDEnano[115] and DaNa criteria                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  applicablewas elaborated to report the toxicological context of a study. The    checklist,[117] Kokalj et al.[118] developed assessment criteria for\nneed to assess nanomaterial data quality has led to adaptation    the quality of studies tailored to (nano)plastics safety research. In                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              Creative\n                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     CommonsAdv. Sustainable Syst. 2026, 10, e00567        e00567 (9 of 18)     \u00a9 2025 The Author(s). Advanced Sustainable Systems published by Wiley-VCH GmbH\n                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     License                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            23667486,\n                                                                                                                                                                                                                                                                                                                                                                                   2026,\nwww.advancedsciencenews.com                                                                  www.advsustainsys.com          4,\nthe approach published by Comandella et al.,[119] completeness of    nal template design. The resulting (meta)data template provides                                                Downloaded\nphysicochemical data on nanomaterials is assessed by assigning  \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036]\n\nStatus: Paper Count=30 | Relevant Papers=10 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=37 | Current Cost=$0.1839 | Disease-Target Evidence=0",
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+              {
+                "role": "assistant",
+                "content": "Let me now update the plan and continue gathering evidence on remaining topics:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01HErKQw25o1ja6tuEfc4Jwk",
+                    "type": "function",
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+                      "arguments": "{\"plan_objective_id\": 1, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 1,\\n  \\\"objective\\\": \\\"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\\\",\\n  \\\"rationale\\\": \\\"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\\\",\\n  \\\"evaluation\\\": \\\"Multiple citations provide comprehensive list of required metadata for standard spectra.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_018dKtGyHZ78RnXpQHfVEh1i",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 2, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 2,\\n  \\\"objective\\\": \\\"Research transferability of standard spectra between instruments - detector variation, published methodologies\\\",\\n  \\\"rationale\\\": \\\"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\\\",\\n  \\\"evaluation\\\": \\\"Sufficient evidence gathered on transferability challenges and published methodologies.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_01LUNsQ58xGhPsHUqs7d57hK",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 3, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 3,\\n  \\\"objective\\\": \\\"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\\\",\\n  \\\"rationale\\\": \\\"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\\\",\\n  \\\"evaluation\\\": \\\"Sufficient evidence with numerical accuracy figures.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_01Btxo21YBAmma85FD4efXF3",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 6, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 6,\\n  \\\"objective\\\": \\\"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\\\",\\n  \\\"rationale\\\": \\\"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \\u00b15% RDEV, 82% within \\u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\\\",\\n  \\\"evaluation\\\": \\\"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01HErKQw25o1ja6tuEfc4Jwk",
+                "info": {
+                  "start_ts": 4918.332153139,
+                  "end_ts": 4918.33941302
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_018dKtGyHZ78RnXpQHfVEh1i",
+                "info": {
+                  "start_ts": 4918.339476441,
+                  "end_ts": 4918.340028872
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01LUNsQ58xGhPsHUqs7d57hK",
+                "info": {
+                  "start_ts": 4918.340061278,
+                  "end_ts": 4918.340539165
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \u00b15% RDEV, 82% within \u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\",\n      \"evaluation\": \"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01Btxo21YBAmma85FD4efXF3",
+                "info": {
+                  "start_ts": 4918.340600173,
+                  "end_ts": 4918.340958927
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me look for information on physical standards and public repositories:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_017yoxpw43hPbCVRJN9gHktc",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"question\": \"What physical standards are used for Al, Si, Mg in EPMA and EDS analysis? Which NIST SRMs are relevant (SRM 470 K-glasses, SRM 481, 482, 2063a)? What compound standards are used for Mg (MgO, periclase, forsterite, spinel)? Is pure Mg metal usable as an EPMA standard?\"}",
+                      "name": "gather_evidence"
+                    }
+                  },
+                  {
+                    "id": "toolu_01EhgpJ2DAaHT13QuSVLT1hR",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"question\": \"What are the standards used at 5 keV in the Newbury and Ritchie 2024 study? What standards did they use for Mg, Al, Si specifically?\"}",
+                      "name": "gather_evidence"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000039\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 5-6'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt shows EPMA/EDS analyses using both pure-element and oxide standards. For Al (in SRM 2062) the authors used pure element standards (Table 7: \"Pure Element Standards; Al K ...\"). Si is analyzed in different sample types; for glasses (SRM 470 K411 and K412) the analyses use oxide standards rather than pure elements (\"Oxide Standards Except for Fe\"). SRM 470 (K\u2011glass; K411 and K412) is explicitly used for glass analyses; SRM 2062 (Al\u2013Ti\u2013Nb\u2013W alloy) and SRM 483 (Fe\u20133Si transformer steel) are also included in these tables. Mg is treated as an oxide in the glass analyses: oxygen was either by assumed stoichiometry or \"O Directly Analyzed (MgO)\" (Tables 8b, 9b), indicating MgO was used as a compound standard/oxygen standard in these DTSA\u2011II analyses. The excerpt does not mention NIST SRM 481, 482, or 2063a, nor does it mention compound standards such as periclase, forsterite, or spinel, and it does not state whether pure Mg metal was used or recommended as an EPMA standard. Further sources should be consulted for recommendations on periclase/forsterite/spinel or the acceptability of pure Mg metal as a standard.\n\n\n---\n\n## pqac-00000040\n\nFrom text 'newbury2024testingtheaccuracy pages 14-16'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nTable 1 (pages 14\u201316) lists the analytical standards used in this study. For Mg-containing materials the table repeatedly lists MgO as the standard. For Si-bearing materials the standard shown is SiO2, and for Al the table shows Al2O3 as a standard. The table also cites NIST SRM identifiers used in the study: entries labelled SRM470_K411_O- and SRM470_K412_O- appear in the material/standard columns, and the text explicitly mentions EDS spectra of NIST SRM 482 (Au40-Cu60) recorded at multiple beam energies. Sample preparation notes indicate materials were mounted, polished and (for non-conductors) coated with an approximately 10 nm carbon layer. The excerpt does not mention SRM 481 or SRM 2063a, nor does it list compound Mg standards such as periclase, forsterite, or spinel, nor any use of pure Mg metal as an EPMA standard\u2014those details are not present in the provided pages.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=41 | Current Cost=$0.2112 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
+                "tool_call_id": "toolu_017yoxpw43hPbCVRJN9gHktc",
+                "info": {
+                  "start_ts": 4955.347283287,
+                  "end_ts": 4987.695527357
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000041\n\nFrom text 'newbury2024testingtheaccuracy pages 14-16'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nTable 1 (continued) shows the standards used for the 5 keV analyses. In the block of columns labeled with materials ending in \u201c_5keV\u201d the Standard row lists GaP, MgO, MgO, SiO2, CaF2, K412, MgO, MgO, Al2O3, SiO2, CaF2, K411. The corresponding Ele-ment row maps those standards to elements: P, O, Mg, Si, Ca, Fe, O, Mg, Al, Si, Ca, Fe. Thus for the 5 keV measurements shown in this portion of the table (materials such as Mg-Al-P_5keV, Mg-Al-Si-Ca-Fe_5keV, Si-Pb_5keV), the standards assigned to Mg are MgO, to Al is Al2O3, and to Si is SiO2. The table therefore indicates repeated use of MgO for Mg standards and SiO2 and Al2O3 for Si and Al standards within the 5 keV dataset.\n\n\n---\n\n## pqac-00000042\n\nFrom text 'newbury2024testingtheaccuracy pages 1-3'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nThe study tested EDS microanalysis at an incident beam energy of 5 keV and implemented a standards-based, k-ratio measurement protocol using the NIST DTSA-II software. The authors analyzed a broad set of reference materials suitable for microanalysis, including NIST Standard Reference Materials (SRMs), certified reference materials (CRMs), reagent compounds, stoichiometric binary compounds, and well-characterized minerals. The NIST SRMs listed explicitly include SRM 470 K411 glass (composition O-Mg-Si-Ca-Fe) and SRM 470 K412 glass (composition O-Mg-Al-Si-Ca-Fe), along with other SRMs (e.g., SRM 479 stainless steel, SRM 481/482 metal alloys, SRM 1871\u20131875 series glasses). Reagent and stoichiometric compounds and mineral standards were also used as challenge specimens. From the excerpt, SRM 470 K411 and SRM 470 K412 are the explicit glass standards containing Mg, Si (K411) and Mg, Al, Si (K412), and these materials were included among the standards used in the 5 keV analyses.\n\n\n---\n\n## pqac-00000043\n\nFrom text 'newbury2024testingtheaccuracy pages 16-18'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt states that standards for analysis were a suite of pure elements (examples given include Si) and, where pure elements were incompatible or unstable under the vacuum/beam, stoichiometric compounds were used (example given: MgO). Non-conductive standards were coated with an ~10 nm carbon layer. The paper shows examples of spectra recorded at 5 keV (e.g., NIST SRM 482 (Au40-Cu60)), and it notes that some materials (example: AlN) were excluded because C and O became significant at reduced beam energies. The excerpt therefore indicates Mg was analyzed using a stoichiometric compound standard (MgO) and Si was included among the pure-element standards. The excerpt does not explicitly state which standard was used for Al.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=44 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
+                "tool_call_id": "toolu_01EhgpJ2DAaHT13QuSVLT1hR",
+                "info": {
+                  "start_ts": 4955.423241282,
+                  "end_ts": 5024.116549652
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now I have substantial evidence. Let me do a few more targeted searches and then prepare the answer:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_013Xyr6QH35xVpVC82morYnx",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"text_name_list\": [\"goldstein2018quantitativeanalysisthe pages 6-8\", \"goldstein2018quantitativeanalysisthe pages 8-9\"]}",
+                      "name": "read_text"
+                    }
+                  },
+                  {
+                    "id": "toolu_0164vD694gdqqzYoWCCo4hYn",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"text_name_list\": [\"newbury2019electronexcitedxraymicroanalysis pages 8-10\"]}",
+                      "name": "read_text"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "## 1. goldstein2018quantitativeanalysisthe pages 8-9 (Context ID: pqac-00000045)\n\nAnalysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n         20.3 Examples of the k-ratio/Matrix              the error budget. In this analysis and the analyses reported\n             Correction Protocol with DTSA II            below, the relative deviation from the expected value (RDEV)\n           (Newbury and Ritchie 2015b)                    (also referred to as \u201crelative error\u201d) is calculated with the\n                                                                       \u201cexpected\u201d value taken as the stoichiometric formula value or\n          20.3.1  Analysis of Major Constituents            the value obtained from an \u201cabsolute\u201d analytical method, just\n                 (C\u2009>\u20090.1 Mass Fraction) with                 as in gravimetric analysis:\n               Well-\u00adResolved Peaks                                                                                         \uf8ee ( Analyzed value \u2212 expected value ) \uf8f9\n                                                  RDEV = \uf8ef                                 \uf8fa \u00d7 100%    (20.3)\n         The EDS spectra of the minerals pyrite (FeS2) and troilite               \uf8f0         expected value         \uf8fb\n          (FeS) measured at E0\u2009=\u200920 keV with a dead-time of\u2009~\u200910\u2009% are\n        shown in .\u2003 Fig. 20.4 and feature well separated peaks for the  Optimizing Analysis Strategy\n         Fe K- and L- families and the S K-family. These spectra were                                                           The DTSA II analysis report includes for each analyzed ele-\n          analyzed with Fe and CuS serving both as peak-fitting refer-                                                         ment the ZAF factors and the estimated uncertainties in\n          ences and as standards. CuS is chosen for the S reference and                                                                        these factors as well as uncertainties due to the counting sta-\n          standard rather than elemental S since CuS is stable under                                                                                          tistics associated with the measurements of the unknown and\n           electron bombardment while elemental S is not stable. The                                                                           of the standard (Ritchie and Newbury 2012). Careful exami-\n         spectrum for FeS and the residual spectrum after peak-fitting                                                                     nation of these factors can be used to refine the analytical\n           are also shown in .\u2003 Fig. 20.4. The results for seven replicate                                                                           strategy to optimize the measurement. Reducing the uncer-\n           analyses are listed in .\u2003 Table 20.1 (FeS) and .\u2003 Table 20.2 (FeS2)   tainty due to the counting statistics requires increasing the\n          along with the ZAF correction factors and the \u00adcomponents of                                                                        dose. The absorption factor A is strongly influenced by the\n\n\n\n             a  180 000                                                                                                                                                FeS_20kV10n9%DT_50s\n                                                                                                                                                FeS_20kV10n9%DT_50s\n                160 000\n                                                                                     E0 = 20 KeV\n                140 000                                                                           FeS\n                120 000                                                      FeS2\n                                   Counts 10080 000000\n\n                 60 000\n\n                 40 000\n\n                 20 000\n\n                      0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                  Photon energy (keV)\n\n           b\n                 14 000                                                                                                            FeS_20kV10n9%DT_50s\n                                                                                                                                                 Residual_FeS_20kV10n9%DT_50s\n\n                 12 000\n                                                                           E0 = 20 KeV\n                 10 000                                          FeS\n                                                                                   Fitting residual\n                                   Counts   8 00020              6 000\n\n                  4 000\n\n                  2 000\n\n                      0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                  Photon energy (keV)\n\n\n      . .\u200a\u200a\u200aFig. 20.4\u2003  a SDD-EDS spectra of Pyrite (FeS2) (blue) and meteoritic Troilite (FeS (red) at E0\u2009=\u200920 keV. b NIST DTSA-II analysis of FeS using Fe and\n          CuS as peak-fitting references and as standards. The original spectrum (red) and the residual spectrum after peak-fitting (blue) are shown                                                                                                               317                                      20\n20.3 \u00b7 Examples of the k-ratio/Matrix Correction Protocol with DTSA II\n\n\n\n  . .\u200a\u200a\u200aTable 20.1\u2003  Analysis of FeS (meteoritic troilite) at E0\u2009=\u200920 keV     . .\u200a\u200a\u200aTable 20.3\u2003  Analysis of FeS at E0\u2009=\u200910 keV with CuS and Fe as\n    with CuS and Fe as fitting references and standards Integrated              fitting references and standards Integrated spectrum count,\n    spectrum count, 0.1\u201320 keV\u2009=\u20097,048,000; uncertainties expressed         0.1\u201310 keV\u2009=\u20095,630,000; uncertainties expressed in mass\n    in mass fraction. Analysis performed with Fe K-L2,3 and S K-L2,3              fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.5052        0.4948              Cav (atom frac)                     0.503           0.497\n\n    Z-correction                        0.977          0.95               Z-correction                       0.973           0.937\n\n    A-correction                        1.118          0.983              A-correction                      1.041           0.997\n\n    F-correction                        1.003         1                  F-correction                       1.001          1\n\n   \u03c3 (7 replicates)                     0.00075       0.00075         \u03c3 (7 replicates)                    0.00056         0.00056\n     \u03c3Rel (%)                             0.15\u2009%         0.15\u2009%                \u03c3Rel (%)                            0.11\u2009%           0.11\u2009%\n   RDEV (%)                           1.00\u2009%       \u22121.00\u2009%          RDEV (%)                          0.59\u2009%        \u22120.59\u2009%\n\n   C (mass frac, single analysis)         0.3699        0.6305          C (mass frac, single analysis)        0.3627          0.6257\n\n    Counting error, std                 0.00020       0.0003           Counting error, std                0.0002          0.0008\n\n    Counting error, unk                 0.00020       0.0007           Counting error, unk                0.0003          0.0018\n\n    A-factor error                       0.0017        0.0002             A-factor error                     0.0006          4.10E-05\n\n    Z-factor error                       2.20\u00d7105      4.10\u00d710\u20136           Z-factor error                      2.20\u00d710\u20135       1.30\u00d710\u20136\n\n   Combined errors                   0.0017        0.0008          Combined errors                  0.0007          0.0019\n\n\n\n  . .\u200a\u200a\u200aTable 20.2\u2003  Analysis of FeS2 (pyrite) at E0\u2009=\u200920 keV with CuS      . .\u200a\u200a\u200aTable 20.4\u2003  Analysis of FeS2 at E0\u2009=\u200910 keV with CuS and Fe as\n   and Fe as fitting references and standards Integrated spectrum             fitting references and standards Integrated spectrum count,\n    count, 0.1.\u201320 keV\u2009=\u20097,765,000; uncertainties expressed in mass          0.1\u201310 keV\u2009=\u20096,253,000); uncertainties expressed in mass\n     fraction. Analysis performed with Fe K-L2,3 and S K-L2,3                       fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.6726        0.3274              Cav (atom frac)                     0.671           0.329\n\n    Z-correction                        0.957          0.928              Z-correctio\n\n## 2. goldstein2018quantitativeanalysisthe pages 6-8 (Context ID: pqac-00000046)\n\nin the center of the Faraday cup aperture\n                                                        opening, the primary beam electrons as well as all BSEs\nwhere A is the active area of the detector and r is the distance  and SEs generated at the inner surfaces are collected with\nfrom the X-ray source on the specimen to the detector. Some   very little loss through the small aperture, so that the cur-\nEDS  systems  are mounted on  a  retractable arm  that   rent flowing to the electrical ground is the total incident\nenables the analyst to choose the value of r. A consistent and  beam current.           314    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n          20.2.4  Choosing the Beam Current            SDD-EDS, a more conservative counting strategy is sug-\n                                                                          gested, such that the beam current is chosen so that the\n           After the analyst has chosen the EDS time constant, the   dead-\u00adtime on the most highly excited standard of interest,\n           detector solid angle (for a retractable detector), and the beam   for example, Al or Si, is less than 10\u2009%. Despite the opera-\n           energy, the beam current should be chosen so as to give a   tion of the anti-coincidence function, SDD-EDS systems\n          reasonable detector throughput, as expressed by the system   typically show evidence of coincidence peaks above a dead-\n          dead-time. .\u2003 Figure 20.2 shows the relationship between the  time of 10\u2009% from highly excited parent peaks, as illustrated\n          input count rate (ICR) of X-rays that arrive at the detector   in .\u2003 Fig. 20.3, which shows the in-growth of an extensive\n         and the output count rate (OCR) of photons that are actually   set of coincidence peaks from several parent peaks. If it is\n           stored in the measured spectrum. The OCR initially rises lin-  important to measure low intensity X-ray peaks that cor-\n           early with the ICR, but as photons arrive at a progressively  respond to minor or trace constituents that occur in spec-\n           greater rate at the detector, photon coincidence begins to   tral regions affected by coincidence peaks, then choosing\n          occur and the anti-coincidence function begins to reject   the low dead-\u00adtime to minimize coincidence will be an\n           these coincidence events, reducing the OCR. Eventually a  important issue in selecting the general analytical condi-\n       maximum OCR value is reached beyond which the OCR   tions. If there is no interest in measuring X-ray peaks of\n          decreases with increasing ICR, eventually falling to zero   possible constituents that occur in the region of coinci-\n           (\u201cparalyzable dead-time\u201d). A useful measure of the activity  dence peaks, then these regions can be ignored and a\n            state of the EDS detector is the system \u201cdead-time\u201d which is  counting strategy that involves higher dead-time operation\n          defined as                                             can be used.\n                                                          Once the analytical conditions (EDS time constant, solid\n                                               100    (20.2)   angle, beam energy, and beam current appropriate to the                Dead-time ( % ) = \uf8ee\uf8f0 (                           ICR \u2212 OCR ) / ICR \uf8f9\uf8fb\u2217\n                                                                 complete suite of standards) have been chosen, these condi-\n      A classic strategy with the low throughput Si(Li)-EDS is to   tions should be used for all standards and unknowns to\n           select a beam current on a highly excited pure element such   achieve the basic measurement consistency required for the\n           as Al or Si that produces a dead-time of 30\u2009% or less. With   k-ratio/matrix corrections protocol.\n\n\n\n      . .\u200a\u200a\u200aFig. 20.2\u2003  Output count rate\n           (OCR) vs. input count rate for an\n          SDD-EDS array of four 10-mm2                                  30 mm2 SDD at medium throughtput\n            detectors\n                                                  200,000\n                                                                                                                        Ideal response\n                                                                                                         (no deadtime)\n\n                                                  160,000\n                                                                                                                                                                                                    (counts/s)\n                                                  120,000\n                                                                              Rate\n                                                                                                  Count\n                                                    80,000\n                                                                                                                      Output\n\n                                                    40,000\n20\n\n                                                   0\n                                                     0          40,000        80,000       120,000       160,000      200,000\n                                                                                     Input Count Rate (counts/s)                                                                                                               315                                      20\n20.2 \u00b7 Instrumentation Requirements\n\n\n\n\n   a\n     3 500 000                                                                                                    K412_20kV5nAMED5eV40kHz3DT_5ks\n\n     3 000 000                                  SRM470 Glass K412\n                                                           E0 = 20 keV\n                                                  Deadtime = 3%\n     2 500 000\n\n\n     2 000 000       Counts\n     1 500 000\n\n\n     1 000 000\n\n     5 000 000\n\n\n            0\n                0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                       Photon energy (keV)\n\n  b\n                                                                                                                     K412_20kV5nAMED5eV40kHz3DT_5ks\n\n      100 000\n\n\n       80 000\n\n\n       60 000       Counts\n\n\n       40 000\n\n\n       20 000\n\n\n            0\n               0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                       Photon energy (keV)\n\n   c                                                                                                                       K412_20kV5nA40kHz_3DT\n                                                                                      Al+Al                                                                        K412_20kV50nA387kHz_29DT\n\n                                                                         SRM470 Glass K412                                                      Si+O                Si+Mg;      Si+Si                                           E0 = 20 keV\n                                                                                Deadtime = 3%\n                                                                                Deadtime = 29%         Counts\n                                                                                                                                     Mg+Ca      Si+Ca\n\n\n\n\n\n       0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0         10.0\n                                                      Photon energy (keV)\n\n\n. .\u200a\u200a\u200aFig. 20.3\u2003 SDD-EDS spectra of NIST SRM (glass K412, E0\u2009=\u200920 keV: a, b at 3\u2009% dead-time (red); c 3\u2009% (red) and 29\u2009% dead-time (blue), showing\nin-growth of coincidence peaks           316    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n         20.3 Examples of the k-ratio/Matrix              the error budget. In this analysis and the analyses reported\n             Correction Protocol with DTSA II            below, the relative deviation from the expected value (RDEV)\n           (Newbury and Ritchie 2015b)                    (also referred to as \u201crelative error\u201d) is calculated with the\n                                                                       \u201cexpected\u201d value taken as the stoichiometric formula value or\n          20.3.1  Analysis of Major Constituents            the value obtained from an \u201cabsolute\u201d analytical method, just\n                 (C\u2009>\u20090.1 Mass Fraction\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=47 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "read_text",
+                "tool_call_id": "toolu_013Xyr6QH35xVpVC82morYnx",
+                "info": {
+                  "start_ts": 5066.357680303,
+                  "end_ts": 5080.289543007
+                }
+              },
+              {
+                "role": "tool",
+                "content": "## 1. newbury2019electronexcitedxraymicroanalysis pages 8-10 (Context ID: pqac-00000044)\n\n                                       1.0037                                          0.6646                                  0.3354\n\n       RDEV (%)                                                                             \u22120.32                                      0.63\n\n       \u03c3 (seven replicates)                          0.0131                                         0.00222                                0.00222\n\n       \u03c3 relative (%)                                   1.3                                                0.33                                      0.66\n\n                                                          S (Mass Concentration) Ideal = 0.4006            Mo (Mass Concentration) Ideal = 0.5994\n\n\n         Single analysis                        1.0010                          0.3971                                              0.6039\n\n       RDEV (%)                                                        \u22120.87                                                  0.75\n\n        k uncertainty                                                             0.0006, 0.15%                                          0.0014, 0.23%\n\n         A-factor uncertainty                                                       0.0006, 0.15%                                          0.0007, 0.12%\n\n         Z-factor uncertainty                                                     0.000028, 0.0001%                                    0.000045, 0.0001%\n\n       Combined uncertainty                                                    0.0008, 0.20%                                          0.0016, 0.26%\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X      Microscopy and Microanalysis                                                                                           9\n\n\n\n\n\n         Fig. 4. EDS spectrum of SrWO4 (E0 = 10 keV) showing the region of the Sr L-family and the W M-family; lower, the peak fitting residual spectrum (blue) after fitting\n         for Sr and W.\n\n\n      repeat the analysis and include Ti in the suite of elements for   which qualitative and quantitative analyses with the construction\n       analysis.                                                             of peak fitting residual spectrum are applied iteratively (Newbury\n                                           & Ritchie, 2018). After each round of peak fitting, the residual spec-\n                                                              trum is inspected to discover any previously unrecognized peaks\n       Iterative Qualitative\u2013Quantitative Analysis to Discover Hidden\n                                                              and to assign them to the correct elements using the characteristic\n     Peaks\n                                                                  peak markers. Note that discontinuities in the continuum back-\n      This example of NIST microanalysis glass K2496 illustrates the   ground caused by absorption edges and broadened by the detector\n       basis for a robust analytical strategy for EDS microanalysis in    function into peak-like structures can also be detected.\n\n\n       Table 12. Analysis of SrWO4 [E0 = 10 keV; SrF2 and W Used as Fitting References (Sr L-family and W M-family) and as Standards; Oxygen Was Calculated by the\n      Method of Assumed Stoichiometry; Values in Atom Concentration; Combined Uncertainties as Estimated from NIST DTSA-II].\n\n                             Raw Analytical Total         O (Atomic Concentration by                  Sr (Atomic           W (Atomic\n         Parameter                 (Mass Concentration)                   Stoichiometry)                      Concentration)               Concentration)\n\n\n        Mean                              1.0017                              0.6660                             0.1678                       0.1661\n\n        RDEV (%)                                                        \u22120.10                                 0.68                       \u22120.33\n\n        \u03c3 (seven replicates)                0.0019                             0.00053                           0.00065                      0.00033\n\n        \u03c3 relative (%)                       0.19                                 0.80                                 0.39                           0.20\n\n                                            O (Mass Concentration)              Sr (Mass Concentration)        W (Mass Concentration)\n                                                                           Ideal = 0.1908                         Ideal = 0.2612                          Ideal = 0.5480\n\n\n          Single analysis                     1.0029                      0.1913                         0.2627                              0.5489\n\n        RDEV (%)                                                        0.27                             0.58                                  0.16\n\n         k uncertainty                                                                                       0.0007, 0.27%                         0.0009, 0.16%\n\n           A-factor uncertainty                                                                                0.0093, 3.5%                          0.0077, 1.4%\n\n           Z-factor uncertainty                                                                               2.7\u00d710\u22125, 0.010%                     5.8\u00d710\u22125, 0.011%\n\n        Combined uncertainty                                                                              0.0093, 3.5%                          0.0078, 1.4%\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X     10                                                                                 Dale E. Newbury and Nicholas W.M. Ritchie\n\n\n\n\n\n        Fig. 5. EDS spectrum of the mineral Benitoite (BaTiSi3O9) (E0 = 10 keV) showing the region of the Ti K-family and the Ba L-family; lower, the peak fitting residual\n      spectrum (blue) after fitting for Ti and Ba.\n\n\n\n         Additionally, when the standards-based intensity ratio proto-    analytical total provide important information, especially a low\n      col is applied for quantitative analysis, the raw (unnormalized)    total which should be considered as a possible indicator of a miss-\n      analytical total, which is the sum of all elemental concentrations    ing element(s).\n     including oxygen calculated by the method of assumed stoichi-    An example of iterative qualitative\u2013quantitative analysis  is\n     ometry,  is determined. As discussed above, deviations in the   presented in Figure 8 and Table 15 for the analysis of NIST\n\n\n\n      Table 13. Analysis of Benitoite (BaTiSi3O9) [E0 = 10 keV; Ti and Sanbornite (BaSi2O5) Used as Fitting References (Si K-family, Ti K-family, and Ba L-family) and as\n      Standards; Oxygen Was Calculated by the Method of Assumed Stoichiometry; Values in Atom Concentration; Combined Uncertainties as Estimated from NIST\n       DTSA-II].\n\n                           Raw Analytical Total      O (Atomic Concentration             Si (Atomic               Ti (Atomic           Ba (Atomic\n        Parameter                 (Mass Concentration)              Stoichiometry)              Concentration)         Concentration)         Concentration)\n\n\n       Mean                             0.9991                        0.6425                     0.2143                  0.0708                0.0723\n\n       RDEV (%)                                                   \u22120.05                          0.0                  \u22120.84                    1.3\n\n       \u03c3 (seven replicates)                                             0.000049                   0.00013                0.00019               0.00013\n\n       \u03c3 relative                                                  0.008%                  0.06%                0.26%               0.18%\n\n                            O (Mass Concentration)        Si (Mass Concentration)          Ti (Mass Concentration)       Ba (Mass Concentration)\n                                                  Ideal = 0.3482                  Ideal = 0.2038                    Ideal = 0.1158                     Ideal = 0.3321\n\n         Single analysis       0.9995               0.3473                  0.2033                        0.1147                         0.3347\n\n       RDEV (%)                             \u22120.26                  \u22120.25                       \u22120.95                            0.78\n\n        k uncertainty                                                         0.0001, 0.05%                  0.0004, 0.35%                   0.0011, 0.32%\n\n         A-factor          \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=45 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "read_text",
+                "tool_call_id": "toolu_0164vD694gdqqzYoWCCo4hYn",
+                "info": {
+                  "start_ts": 5066.358385922,
+                  "end_ts": 5076.70606513
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me update the remaining plan objectives and create the artifacts:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_012fetPhMSnahqoMA7t6K9o1",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 4, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 4,\\n  \\\"objective\\\": \\\"Research physical standards suppliers and certified reference materials for Al, Si, Mg\\\",\\n  \\\"rationale\\\": \\\"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"Newbury & Ritchie 2024 lists NIST SRMs (470 K411/K412, 479, 481, 482, 1871-1875). They used MgO for Mg, Al2O3 for Al, SiO2 for Si at 5 keV. The paper lists SPI (West Chester, PA) for minerals, Geller Microanalytical Laboratory (Topsfield, MA) for stoichiometric compounds, Alfa Aesar for reagent compounds. Newbury & Ritchie 2015 describes use of MgO, KCl, FeS2, GaP, CaF2 as compound standards. Additional supplier information (Astimex, MAC, Ted Pella) from expert knowledge.\\\",\\n  \\\"evaluation\\\": \\\"Concrete supplier names and standards identified with sufficient detail from the literature.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_013xnvkza6w1rdE9aM8kNgtr",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 5, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 5,\\n  \\\"objective\\\": \\\"Research public repositories of EDS/EPMA spectra\\\",\\n  \\\"rationale\\\": \\\"Question 5 asks about downloadable spectrum libraries in EMSA format\\\",\\n  \\\"status\\\": \\\"completed\\\",\\n  \\\"result\\\": \\\"NIST DTSA-II includes a built-in standards database. The ISO 22029 EMSA/MAS format is the standard format. No large publicly downloadable measured EDS standards library was identified in the literature beyond the DTSA-II internal database. The de-ma.ch web database (Allaz 2024) and Zenodo deposits exist but were not obtainable for detailed review. Remote standards approach described by Newbury & Ritchie.\\\",\\n  \\\"evaluation\\\": \\\"Key resources identified; limitations in publicly available measured standard spectra documented.\\\"\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 lists NIST SRMs (470 K411/K412, 479, 481, 482, 1871-1875). They used MgO for Mg, Al2O3 for Al, SiO2 for Si at 5 keV. The paper lists SPI (West Chester, PA) for minerals, Geller Microanalytical Laboratory (Topsfield, MA) for stoichiometric compounds, Alfa Aesar for reagent compounds. Newbury & Ritchie 2015 describes use of MgO, KCl, FeS2, GaP, CaF2 as compound standards. Additional supplier information (Astimex, MAC, Ted Pella) from expert knowledge.\",\n      \"evaluation\": \"Concrete supplier names and standards identified with sufficient detail from the literature.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \u00b15% RDEV, 82% within \u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\",\n      \"evaluation\": \"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_012fetPhMSnahqoMA7t6K9o1",
+                "info": {
+                  "start_ts": 5135.110758985,
+                  "end_ts": 5135.113155531
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 lists NIST SRMs (470 K411/K412, 479, 481, 482, 1871-1875). They used MgO for Mg, Al2O3 for Al, SiO2 for Si at 5 keV. The paper lists SPI (West Chester, PA) for minerals, Geller Microanalytical Laboratory (Topsfield, MA) for stoichiometric compounds, Alfa Aesar for reagent compounds. Newbury & Ritchie 2015 describes use of MgO, KCl, FeS2, GaP, CaF2 as compound standards. Additional supplier information (Astimex, MAC, Ted Pella) from expert knowledge.\",\n      \"evaluation\": \"Concrete supplier names and standards identified with sufficient detail from the literature.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"completed\",\n      \"result\": \"NIST DTSA-II includes a built-in standards database. The ISO 22029 EMSA/MAS format is the standard format. No large publicly downloadable measured EDS standards library was identified in the literature beyond the DTSA-II internal database. The de-ma.ch web database (Allaz 2024) and Zenodo deposits exist but were not obtainable for detailed review. Remote standards approach described by Newbury & Ritchie.\",\n      \"evaluation\": \"Key resources identified; limitations in publicly available measured standard spectra documented.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \u00b15% RDEV, 82% within \u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\",\n      \"evaluation\": \"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_013xnvkza6w1rdE9aM8kNgtr",
+                "info": {
+                  "start_ts": 5135.113222685,
+                  "end_ts": 5135.113772505
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me create a summary artifact and then compose the final answer:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01ALNMFNcJzbhppB8hRRwLaV",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"artifact_type\": \"table\", \"description\": \"Create a table summarizing the required metadata for an EDS standard spectrum to be usable in standards-based k-ratio quantification, with columns for: Metadata Parameter, Description/Purpose, and EMSA/MAS Keyword (where applicable). Include: beam energy, probe current, live time, take-off angle, detector window parameters, energy calibration (zero and gain), FWHM at Mn Ka, process time, standard composition and traceability, date, contamination/coating state, detector-to-specimen distance, tilt, azimuth. Note that this information is derived from Goldstein et al. 2018 (Scanning Electron Microscopy and X-ray Microanalysis, 4th ed.), the EMSA/MAS spectrum file format (ISO 22029), and Newbury & Ritchie 2015.\"}",
+                      "name": "create_artifact"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "### Artifact (ID artifact-00)\n\n| Metadata Parameter | Description/Purpose | EMSA/MAS Keyword (where applicable) |\n|---|---|---|\n| Beam energy / accelerating voltage | Required because k-ratios are valid only when unknown and standard are measured under the same excitation conditions; changes ionization cross-sections, overvoltage, depth of generation, and matrix corrections. (pqac-00000000, pqac-00000002, pqac-00000005, pqac-00000022) | `#BEAMKV` |\n| Probe current | Needed to document electron dose and to verify reproducibility/linearity of X-ray intensity; rigorous k-ratio work should measure current with a Faraday cup/picoammeter. (pqac-00000000, pqac-00000013, pqac-00000035, pqac-00000046) | `#PROBECUR` |\n| Live time | Dose in EDS is probe current \u00d7 live time; live time, not real time, determines effective dose because dead time removes useful counts. (pqac-00000000, pqac-00000013, pqac-00000025, pqac-00000035) | `#LIVETIME` |\n| Real time / dead time | Important to assess pulse pile-up/coincidence and detector operating regime; Newbury & Ritchie recommend conservative operation around ~10% dead time for standards-based work, especially when weak peaks sit near coincidence/tail artifacts. (pqac-00000006, pqac-00000013, pqac-00000035, pqac-00000046) | `#REALTIME`, `#DEADTIME` |\n| Detector elevation / take-off angle | Required geometric parameter for absorption correction; should match between unknown and standard and be verified physically if necessary. (pqac-00000000, pqac-00000002, pqac-00000013, pqac-00000026) | often `#ELEVANGLE` or vendor-specific |\n| Detector azimuth angle | Needed because detector orientation changes X-ray path length and effective efficiency; should be fixed and recorded for reusable standards. (pqac-00000000, pqac-00000013) | often vendor-specific / not always standardized |\n| Specimen tilt | Changes take-off geometry and absorption; Goldstein/Newbury specify tilt should be controlled, preferably zero for bulk standards unless intentionally used. (pqac-00000000, pqac-00000013, pqac-00000022) | often `#XTILTSTGE`, `#YTILTSTGE` or vendor-specific |\n| Detector-to-specimen distance / working distance | Sets solid angle and count rate; must be reproducible between standard and unknown. Off-axis position also changes apparent low-energy efficiency because of window-grid/trap shadowing. (pqac-00000000, pqac-00000002, pqac-00000027) | often `#WORKING`, `#DISTANCE` or vendor-specific |\n| Detector active area / solid angle | Needed to interpret count rate and portability of archived spectra; different detector geometries change throughput and sensitivity. (pqac-00000000, pqac-00000002, pqac-00000015) | usually not in classic MSA core keywords; vendor-specific |\n| Detector window type and thickness | Critical below ~2 keV because polymer/SiN vs Be windows transmit low-energy X-rays very differently; affects Mg K, Al K, O K, etc. (pqac-00000009, pqac-00000010, pqac-00000019, pqac-00000027) | usually vendor-specific / not a required classic MSA keyword |\n| Window support grid / electron trap details | Off-axis shadowing and low-energy attenuation can change intensity and background, especially for light elements. (pqac-00000027) | vendor-specific |\n| Detector dead layer / front contact / Si absorption characteristics | Needed when comparing detectors or simulating spectra because fluorescence in dead layer, escape peaks, and efficiency roll-off alter low-energy response. (pqac-00000009, pqac-00000011) | vendor-specific |\n| Detector response function / incomplete charge collection behavior | Essential for fitting trace peaks under tails; low-energy tailing and peak-shape differences are detector-specific and limit transferability of standard spectra. (pqac-00000009, pqac-00000012, pqac-00000037) | not represented in classic MSA keyword set |\n| Energy calibration zero offset | Required so standard and unknown spectra align channel-for-channel for integrated-peak k-ratios and peak fitting. (pqac-00000022, pqac-00000035) | `#OFFSET` |\n| Energy calibration gain / channel width | Required to define energy-per-channel; Goldstein recommends fixed channel width (e.g., 5 eV/channel) and consistent calibration. (pqac-00000022, pqac-00000035) | `#XPERCHAN`, sometimes paired with `#OFFSET` |\n| Number of channels / energy range | Needed to reconstruct spectrum and assure same fitting range; spectra should span low-energy region through the Duane\u2013Hunt limit. (pqac-00000022, pqac-00000035) | `#NPOINTS`, `#XUNITS` |\n| Energy resolution / FWHM at Mn K\u03b1 | Peak overlap sensitivity depends on detector resolution; should be documented because different FWHM values change deconvolution and low-energy tail contributions. (pqac-00000026, pqac-00000010, pqac-00000011) | often `#MNFWHM` or vendor-specific |\n| Process time / shaping time / time constant | Must be fixed; adaptive process time is specifically discouraged for standards-based quantification because it changes peak shape and resolution. (pqac-00000000, pqac-00000013, pqac-00000026) | often `#TIMECNST` or vendor-specific |\n| Count total / integrated counts | High-count spectra are needed for robust MLLS fitting and trace-level overlap correction; archive the total counts or dose associated with the standard. (pqac-00000006, pqac-00000007, pqac-00000017) | `#DATATYPE` with counts array; total counts often derived or vendor-specific |\n| Standard identity | The material used as the standard must be named explicitly so composition, homogeneity, and suitability can be checked. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | `#SAMPLE` |\n| Standard composition | Required because k-ratio denominator must correspond to a known concentration in the standard. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | no single core keyword; usually comment/header text |\n| Certification / traceability | For rigorous work, the standard composition should be certified or independently established and microscopically homogeneous. (pqac-00000002, pqac-00000003, pqac-00000042) | usually comment/header text |\n| Date/time of acquisition | Needed for traceability, detector stability checks, and QA of archived reusable standards. (pqac-00000000, pqac-00000013) | `#DATE`, `#TIME` |\n| Operator / instrument identifier | Supports QA and cross-checking of archived standards; important when spectra are reused. (pqac-00000013) | `#OWNER`, `#TITLE`, vendor-specific instrument fields |\n| Specimen surface preparation state | Surface roughness/topography directly affects low-energy X-rays; for photons below ~1 keV surfaces should be extremely flat, and standards/unknowns should be prepared similarly. (pqac-00000002, pqac-00000007, pqac-00000022) | usually comment/header text |\n| Coating material and thickness | Carbon or metal coatings absorb low-energy X-rays; mismatch between standard and unknown coatings can cause significant error at low kV. (pqac-00000004, pqac-00000007, pqac-00000034) | usually comment/header text |\n| Contamination / oxidation / tarnish state | Surface films create composite specimens and strongly bias low-energy analysis; should be documented, especially for reactive standards like Mg-bearing materials. (pqac-00000003, pqac-00000018, pqac-00000034) | usually comment/header text |\n| Vacuum / chamber conditions | Useful for assessing contamination growth and detector performance stability during acquisition. (pqac-00000018, pqac-00000034) | vendor-specific |\n| Peak-family / line selection used for quantification | EDS often quantifies whole line families rather than a single line; the selected family must be known to interpret k-ratios and matrix corrections. (pqac-00000005, pqac-00000016, pqac-00000024) | usually analysis metadata, not core MSA |\n| Background/fit model or peak-shape reference linkage | Particularly valuable for trace-overlap cases, because usability of a stored standard also depends on the associated peak-shape references and fitting strategy. (pqac-00000016, pqac-00000017, pqac-00000023) | not in classic MSA core; DTSA-II/project metadata |\n| QA status / same-conditions verification | Archived standards are reusable only if a QA protocol confirms the unknown was measured under the same beam energy, dose, and EDS parameters. (pqac-00000000, pqac-00000013) | not a classic MSA keyword; external QA record |\n\n\n*Table: This table summarizes the metadata that must accompany an EDS standard spectrum for rigorous standards-based k-ratio quantification. It combines the practical requirements emphasized by Goldstein/Newbury/Ritchie with the fields typically represented in the EMSA/MAS .msa format and notes where classic MSA keywords are incomplete for modern detector-response details.*\n\nArtifact IDs that may be injected into the answer: [artifact-00]\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=47 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "create_artifact",
+                "tool_call_id": "toolu_01ALNMFNcJzbhppB8hRRwLaV",
+                "info": {
+                  "start_ts": 5182.036432442,
+                  "end_ts": 5211.214982695
+                }
+              },
+              {
+                "role": "assistant",
+                "content": null,
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_013Dk6gnt6nGCbaXL2Vrg2Ub",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"artifact_type\": \"table\", \"description\": \"Create a table of physical standards suppliers and certified reference materials relevant to Al, Si, and Mg for electron probe microanalysis / SEM-EDS. Include columns for: Supplier/Source, Product/CRM, Catalogue/SRM Number, Elements/Composition, and Notes. Include:\\n- NIST SRM 470 (K411 glass: O-Mg-Si-Ca-Fe; K412 glass: O-Mg-Al-Si-Ca-Fe)\\n- NIST SRM 481 (Au-Ag alloys)\\n- NIST SRM 482 (Au-Cu alloys)  \\n- NIST SRM 479 (Fe-Cr-Ni stainless steel)\\n- NIST SRM 483 (Fe-3Si transformer steel)\\n- NIST SRM 2063a (thin film)\\n- NIST SRM 1871-1875 (K-glass series)\\n- Geller MicroAnalytical Laboratory (Topsfield, MA) for stoichiometric binary compounds like MgO, Al2O3, SiO2\\n- SPI Supplies (West Chester, PA) for minerals (periclase, forsterite, dolomite, spinel, etc.)\\n- Astimex Standards Ltd (Toronto, Canada) for pure element and compound standard mounts\\n- Ted Pella Inc for microanalysis standards\\n- Micro-Analysis Consultants (MAC) (St Ives, UK) for mineral and synthetic standards\\n- P&H Developments for standards\\n- Alfa Aesar for reagent-grade compounds\\n- MgO as the recommended compound standard for Mg\\n- Note about pure Mg metal oxidation problem\\n- Smithsonian microbeam standards collection for minerals\\nFrom the Newbury & Ritchie 2024 paper data.\"}",
+                      "name": "create_artifact"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "### Artifact (ID artifact-01)\n\n| Supplier/Source | Product/CRM | Catalogue/SRM Number | Elements/Composition | Notes |\n|---|---|---|---|---|\n| NIST | Glass for microanalysis, K411 | SRM 470 K411 | O-Mg-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; useful as a multi-element glass containing Mg and Si. (pqac-00000031, pqac-00000042) |\n| NIST | Glass for microanalysis, K412 | SRM 470 K412 | O-Mg-Al-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; directly relevant to Al-Mg-Si calibration and overlap studies. (pqac-00000031, pqac-00000042) |\n| NIST | Gold-silver alloy set | SRM 481 | Au-Ag alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study as a certified alloy series suitable for microanalysis challenge specimens and standards work. (pqac-00000031, pqac-00000042) |\n| NIST | Gold-copper alloy set | SRM 482 | Au-Cu alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study; Newbury & Ritchie also discuss spectra of SRM 482 at multiple beam energies. (pqac-00000031, pqac-00000034, pqac-00000042) |\n| NIST | Stainless steel CRM | SRM 479 | Fe-Cr-Ni stainless steel | Explicitly listed in the 5 kV study among NIST microanalysis challenge materials. (pqac-00000031, pqac-00000042) |\n| NIST | Transformer steel CRM | SRM 483 | Fe-3Si steel | Mentioned by Newbury & Ritchie 2019 as an EPMA/EDS reference material in quantitative work. (pqac-00000039) |\n| NIST | Thin-film microanalysis SRM | SRM 2063a | Thin film; composition not verified here | Relevant NIST microanalysis SRM class, but exact composition/details were not verified in the retrieved sources; include only after checking the current NIST certificate. |\n| NIST | K-glass / oxide glass series | SRM 1871, 1872, 1873, 1875 | SRM 1871 K456: O-Si-Pb; SRM 1872 K453: O-Ge-Pb; SRM 1873 K458: O-Si-Zn-Ba; SRM 1875 K496: O-Mg-Al-P | Explicitly listed in the 5 kV study as microanalysis-qualified SRMs. SRM 1875 is especially relevant because it contains Mg and Al. (pqac-00000031, pqac-00000042) |\n| Geller MicroAnalytical Laboratory (Topsfield, MA, USA) | Stoichiometric binary compounds prepared for microanalysis | Vendor product line; specific catalogue IDs not verified here | MgO, Al2O3, SiO2, TiN, TiO2, Cr2N, etc. | Explicitly named by Newbury & Ritchie 2024 as a source of stoichiometric compounds with surfaces prepared for microanalysis. Recommended route for MgO, Al2O3, SiO2 standards. (pqac-00000031, pqac-00000040) |\n| SPI Supplies (West Chester, PA, USA) | Mineral standards / well-characterized minerals | Vendor product line; specific catalogue IDs not verified here | Minerals such as calcite, dolomite, fluorapatite, wollastonite, zircon; user-requested examples periclase/forsterite/spinel should be checked in current catalog | Explicitly named by Newbury & Ritchie 2024 as a source of minerals of known composition and micro-homogeneity used in the challenge set. (pqac-00000031, pqac-00000042) |\n| Astimex Standards Ltd (Toronto, Canada) | Mounted pure-element and compound microanalysis standards | Vendor product line; specific catalogue IDs not verified here | Pure Al, Si, alloys, oxides, silicates, custom mounts | Common EPMA/SEM-EDS supplier, but specific products were not verified in the retrieved literature; check current catalog for Al, Si, Mg-bearing mounts before purchase. |\n| Ted Pella, Inc. | Microanalysis standards and mounts | Vendor product line; specific catalogue IDs not verified here | Pure elements, compounds, calibration mounts | Widely used supplier, but no product-specific verification in retrieved sources; confirm current catalog details. |\n| Micro-Analysis Consultants (MAC), St Ives, UK | Mineral and synthetic EPMA standards | Vendor product line; specific catalogue IDs not verified here | Silicates, oxides, sulfides, synthetic compounds | Common EPMA standards source, but exact catalog entries were not verified in retrieved sources. |\n| P&H Developments | Electron microprobe standards | Vendor product line; specific catalogue IDs not verified here | Mineral and synthetic standards | Named by user request; no product-specific verification found in retrieved sources, so verify directly with supplier. |\n| Alfa Aesar (now Thermo Fisher chemicals) | Reagent compounds | Reagent-grade products; specific catalogue IDs not verified here | BaTiO3, PbS, MoS2 and other compounds | Explicitly named by Newbury & Ritchie 2024 as source of reagent compounds used as challenge specimens; reagent grade is not automatically a microanalysis standard, so homogeneity/prep must be checked. (pqac-00000031, pqac-00000040) |\n| Smithsonian microbeam standards collection | Mineral reference materials | Collection-level resource; no single catalogue number | Mineral standards, including Mg-bearing silicates/carbonates depending on collection | Valuable institutional standards resource, but not documented in the retrieved contexts; verify access and material list directly with Smithsonian microbeam facility. |\n| Recommended Mg standard chemistry | MgO (periclase chemistry) | Not a single catalog number | Mg and O | Newbury & Ritchie\u2019s 5 kV study repeatedly used MgO as the Mg standard; their standards table maps Mg to MgO at 5 kV. This is the best-supported Mg standard in the retrieved sources. (pqac-00000040, pqac-00000041, pqac-00000043) |\n| Recommended Al standard chemistry | Al2O3 | Not a single catalog number | Al and O | In the 5 kV study, Al was standardized with Al2O3 in the standards table; practical if oxide standards are already in the block. (pqac-00000040, pqac-00000041) |\n| Recommended Si standard chemistry | SiO2 or pure Si | Not a single catalog number | Si and O, or Si | The 5 kV study shows SiO2 used as a Si standard in multiple entries; Newbury & Ritchie also note that pure Si can be used among pure-element standards. (pqac-00000040, pqac-00000041, pqac-00000043) |\n| Caution on pure Mg metal | Pure Mg metal | Not recommended as first-choice standard for routine low-kV SEM-EDS | Mg metal, rapidly oxidizing surface | Not directly evaluated in the retrieved papers, but the literature retrieved strongly supports substitution with MgO; this is consistent with the practical oxidation/contamination problem for Mg metal and the repeated use of stoichiometric compounds when pure elements are unstable. (pqac-00000003, pqac-00000005, pqac-00000043) |\n\n\n*Table: This table summarizes physical standards sources and certified reference materials relevant to Al, Si, and Mg SEM-EDS/EPMA work, emphasizing items explicitly documented in the Newbury & Ritchie 2024 5 kV study. It distinguishes directly verified standards from commonly used suppliers whose current catalogue details should still be checked before procurement.*\n\nArtifact IDs that may be injected into the answer: [artifact-00, artifact-01]\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046]\n\nStatus: Paper Count=30 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=47 | Current Cost=$0.2350 | Disease-Target Evidence=0",
+                "name": "create_artifact",
+                "tool_call_id": "toolu_013Dk6gnt6nGCbaXL2Vrg2Ub",
+                "info": {
+                  "start_ts": 5264.997456878,
+                  "end_ts": 5283.989548657
+                }
+              },
+              {
+                "role": "assistant",
+                "content": null,
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01AtT5WP7fdQH8qk1W2dWvxH",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 7, \"updated_plan_objective_json\": \"{\\n  \\\"id\\\": 7,\\n  \\\"objective\\\": \\\"Create summary artifacts and submit final answer\\\",\\n  \\\"rationale\\\": \\\"Compile all findings into a comprehensive, well-cited answer\\\",\\n  \\\"status\\\": \\\"in-progress\\\",\\n  \\\"result\\\": null,\\n  \\\"evaluation\\\": null\\n}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research EDS standard spectrum metadata requirements, EMSA/MAS .msa format specification, and Goldstein et al. requirements\",\n      \"rationale\": \"Question 1 asks specifically about what metadata must accompany a standard spectrum and cites the EMSA/MAS format spec and Goldstein textbook\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed evidence from Newbury & Ritchie 2015, Goldstein et al. 2018, Tong & Mingard 2026, and Newbury & Ritchie 2019 on required metadata. The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 lists NIST SRMs (470 K411/K412, 479, 481, 482, 1871-1875). They used MgO for Mg, Al2O3 for Al, SiO2 for Si at 5 keV. The paper lists SPI (West Chester, PA) for minerals, Geller Microanalytical Laboratory (Topsfield, MA) for stoichiometric compounds, Alfa Aesar for reagent compounds. Newbury & Ritchie 2015 describes use of MgO, KCl, FeS2, GaP, CaF2 as compound standards. Additional supplier information (Astimex, MAC, Ted Pella) from expert knowledge.\",\n      \"evaluation\": \"Concrete supplier names and standards identified with sufficient detail from the literature.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"completed\",\n      \"result\": \"NIST DTSA-II includes a built-in standards database. The ISO 22029 EMSA/MAS format is the standard format. No large publicly downloadable measured EDS standards library was identified in the literature beyond the DTSA-II internal database. The de-ma.ch web database (Allaz 2024) and Zenodo deposits exist but were not obtainable for detailed review. Remote standards approach described by Newbury & Ritchie.\",\n      \"evaluation\": \"Key resources identified; limitations in publicly available measured standard spectra documented.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \u00b15% RDEV, 82% within \u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\",\n      \"evaluation\": \"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"in-progress\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01AtT5WP7fdQH8qk1W2dWvxH",
+                "info": {
+                  "start_ts": 5328.515742824,
+                  "end_ts": 5328.519705772
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now I have comprehensive evidence. Let me submit the final answer:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01QRDUASBjwGnxzdisGYZDLF",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"answer\": \"# Standards-Based k-Ratio Quantification for Low-kV SEM-EDS of AlSi10Mg: A Comprehensive Technical Guide\\n\\n## 1. What Is an EDS Standard Spectrum, Informationally?\\n\\nAn EDS standard spectrum is far more than an array of channel counts. For it to be usable in standards-based k-ratio quantification, a standard spectrum must be accompanied by a comprehensive set of metadata that documents the exact conditions under which it was acquired, so that the fundamental ratio k = I_unknown / I_standard is meaningful. The k-ratio protocol requires that unknown and standard be measured \\\"under identical conditions of beam energy, known dose, and detector efficiency\\\" (pqac-00000005). Specifically, the following metadata must be recorded and archived with each standard spectrum:\\n\\n**Instrumental parameters:** beam energy (accelerating voltage), probe current (measured with a Faraday cup and digital picoammeter for rigorous work), live time and real time (to calculate effective dose and dead time), and the EDS detector's process time/time constant (which must remain fixed\\u2014adaptive process time is explicitly discouraged for standards-based work) (pqac-00000000, pqac-00000026). The dead time should be kept below approximately 10% to minimize coincidence artifacts, which grow significantly above ~15% dead time (pqac-00000007, pqac-00000046).\\n\\n**Geometric parameters:** detector elevation (take-off) angle, detector azimuthal angle, specimen tilt (preferably zero), detector-to-specimen distance (which sets the solid angle), and the detector active area (pqac-00000000, pqac-00000002, pqac-00000013).\\n\\n**Detector characterization:** window type and thickness (polymer/Moxtek AP3/AP5 vs. Be vs. windowless), support grid geometry and open area fraction (typically 76\\u201380%), detector dead layer thickness, energy resolution (FWHM at Mn K\\u03b1, typically 122\\u2013150 eV for modern SDDs), and the energy calibration (zero offset and gain, typically 5 eV/channel) (pqac-00000009, pqac-00000026, pqac-00000027, pqac-00000035).\\n\\n**Standard material parameters:** the identity and known composition of the standard (whether certified by an independent method), its microscopic homogeneity (confirmed by EPMA), and its certification traceability (e.g., NIST SRM certificate) (pqac-00000003). When pure elements are incompatible with vacuum or suffer oxidation/beam damage, stoichiometric compounds are substituted\\u2014e.g., MgO for Mg, KCl for K and Cl, FeS\\u2082 for S, GaP for Ga and P, CaF\\u2082 for Ca and F (pqac-00000005).\\n\\n**Sample condition parameters:** surface preparation state (highly polished, not chemically etched; surface roughness <50 nm rms for measurements of photons below 1 keV), coating material and thickness (typically ~8\\u201310 nm carbon), and contamination/oxidation/tarnish state (pqac-00000002, pqac-00000004, pqac-00000007, pqac-00000022).\\n\\n**Administrative parameters:** date and time of acquisition, operator, and instrument identifier (pqac-00000000, pqac-00000013).\\n\\n**The EMSA/MAS .msa format (ISO 22029)** is the standardized spectrum data file format for microbeam analysis, originally defined by Fiori, Swyt, and others and adopted as ISO 22029 \\\"Microbeam Analysis \\u2013 EMSA/MAS Standard File Format for Spectral-Data Exchange\\\" (pqac-00000036). Its required keywords include `#FORMAT`, `#VERSION`, `#TITLE`, `#DATE`, `#TIME`, `#OWNER`, `#NPOINTS`, `#NCOLUMNS`, `#XUNITS`, `#YUNITS`, `#DATATYPE`, `#XPERCHAN`, `#OFFSET`, `#SIGNALTYPE`, and `#SPECTRUM`. Optional but analytically critical keywords include `#BEAMKV`, `#PROBECUR`, `#LIVETIME`, `#REALTIME`, `#ELEVANGLE`, `#AZIMANGLE`, and `#XTILTSTGE`/`#YTILTSTGE`. Notably, the classic EMSA/MAS keyword set does not include dedicated fields for detector window type, dead layer thickness, incomplete charge collection parameters, or FWHM at Mn K\\u03b1\\u2014these must be recorded in comment fields or external documentation. Scott, Wight, and Thorne (2002, Microsc. Microanal. 8:646\\u2013647) proposed extending the format to XML-based \\\"EMSA/MAS 2.0,\\\" but the original ASCII format remains dominant.\\n\\nThe following table summarizes the complete metadata requirements:\\n\\n<artifact id=\\\"artifact-00\\\"/>\\n\\n## 2. Are Standard Spectra Transferable Between Instruments?\\n\\n**The short answer is: generally no, not without significant correction, especially for low-energy lines below ~2 keV.**\\n\\nThe fundamental problem is that the k-ratio protocol requires that unknown and standard spectra be acquired under identical conditions. The stability of modern SDD-EDS detectors permits reuse of previously measured, stored standard spectra on the *same* instrument, provided a quality-assurance protocol confirms that the unknown was measured under the same documented conditions (beam energy, dose, and EDS parameters) (pqac-00000000, pqac-00000013). SDDs show nearly constant resolution and calibration across a wide range of input count rates, which enables practical spectrum archiving on a given instrument (pqac-00000015).\\n\\nHowever, cross-instrument transfer faces several detector-specific barriers:\\n\\n**Resolution differences:** Different SDDs have different FWHM values (typically 122\\u2013150 eV at Mn K\\u03b1), which change peak shapes and the extent of tails under adjacent peaks\\u2014directly relevant to the Al K\\u03b1 tail under Mg K\\u03b1 in your case (pqac-00000010, pqac-00000011, pqac-00000026).\\n\\n**Window transmission:** The choice of window material (polymer/SiN vs. Be vs. windowless) dramatically affects transmission below ~2 keV. Moxtek AP3 and AP5 windows have different thicknesses (380 \\u00b5m vs. 265 \\u00b5m ribs), rib widths, and acceptance angles, creating different low-energy efficiencies (pqac-00000027). Be windows absorb essentially all X-rays below ~1 keV, making spectra taken with Be-window detectors incomparable to those from polymer-window detectors for light-element lines (pqac-00000019).\\n\\n**Silicon dead layer and incomplete charge collection (ICC):** Scholze and Procop modeled the EDS spectral response accounting for statistical and electronic noise, ICC (which causes peak tailing on the low-energy side), escape effects, and fluorescence from the front contact/dead layer (pqac-00000009). These processes are detector-specific and alter both peak shapes and the continuum particularly at low energies. The ICC tailing is the precise artifact creating your Al K\\u03b1 tail under Mg K\\u03b1.\\n\\n**Published \\\"standards transfer\\\" methodologies:** Newbury and Ritchie describe a \\\"remote standards standardless\\\" approach in which a library of standard measurements made on another instrument supplies standard intensities, with calculated corrections applied for beam energy and spectrometer efficiency differences. However, they note that no dose calibration is attempted in this approach, so the raw analytical total has no validity and normalization is required\\u2014thereby removing important diagnostic indicators of geometric or other deviations (pqac-00000012). Newbury and Ritchie (2019) also reference a \\\"golden detector\\\" calibration-transfer technique (from Alvisi et al., 2006), in which a detector calibrated at a synchrotron beamline is used with a carefully chosen reference material to transfer the calibration to other instruments\\u2014an approach they note is inherently more accurate than purely first-principles standardless methods (pqac-00000014, pqac-00000021).\\n\\n**Quantitative accuracy penalty:** When comparing measured and DTSA-II simulated spectra for bulk K411 at 20 keV (a surrogate for cross-instrument transfer using a modeled detector response), Newbury and Ritchie found discrepancies ranging from +1.2% for Fe K\\u03b1 to +19% for Mg K, with the low-energy region showing systematically larger deviations (pqac-00000008, pqac-00000012). This +19% discrepancy for Mg K specifically underscores the severity of the problem for your Mg K\\u03b1 / Al K\\u03b1 overlap situation.\\n\\n**Practical recommendation:** For your specific case (trace Mg K\\u03b1 at 1.254 keV under the tail of the dominant Al K\\u03b1 at 1.487 keV), standard spectra should be acquired on your own EDAX Octane Plus SDD on your Apreo SEM under the same conditions as your unknowns. Cross-instrument transfer of standards is not recommended for this challenging low-energy overlap problem.\\n\\n## 3. Simulated / Synthetic Standards\\n\\nNIST DTSA-II includes built-in spectrum simulation tools (based on NISTMonte, a Monte Carlo electron trajectory simulator) that can generate synthetic standard spectra from first-principles physics to yield absolute intensities (pqac-00000008). The simulation models electron scattering, X-ray generation, self-absorption, secondary fluorescence, and the detector response function.\\n\\n**Published accuracy assessments:**\\n\\nWhen Newbury and Ritchie (2015) used DTSA-II simulated standards to analyze NIST microanalysis glass K2496 at 10 keV, the resulting concentrations were very close to the as-synthesized values, with RDEV values of approximately \\u22121.0% to +1.7% for the constituent elements and precision metrics of ~0.08\\u20131.8% relative (pqac-00000006). This demonstrates that simulated standards can provide accurate quantification for moderate-to-high-energy X-ray lines in well-controlled measurements.\\n\\nHowever, for bulk K411 at 20 keV, a direct comparison of measured and simulated spectra (without scaling) showed discrepancies of +1.2% for Fe K\\u03b1 up to +19% for Mg K (pqac-00000008). The systematically larger error at low photon energies (Mg K at 1.254 keV) reflects the difficulty of accurately modeling the detector response\\u2014particularly ICC, dead layer absorption, and window transmission effects\\u2014in the sub-2 keV energy range.\\n\\n**Where simulated standards are acceptable:** Simulated standards are most useful when a flat, bulk reference of the desired composition is unavailable\\u2014for example, when analyzing irregularly shaped particles or microstructural features. DTSA-II can simulate a bulk reference spectrum from an estimated composition, with a first normalized analysis serving as that estimate (pqac-00000008, pqac-00000012). For higher-energy lines (>2 keV) and well-characterized detector parameters, simulated standards can approach the accuracy of measured standards.\\n\\n**Where simulated standards specifically fail:** The simulation's accuracy critically depends on the fidelity of the detector response model. Key failure modes include:\\n- **Low-energy peak tailing and ICC:** The incomplete charge collection process, which creates low-energy tails on peaks, is detector-specific and difficult to parameterize accurately from first principles. Giunto et al. (2025) note that detector artifacts \\\"particularly below 2 keV\\\" complicate background fitting and quantification (pqac-00000037).\\n- **Contamination layers and surface effects:** Real specimens accumulate carbon contamination and may have oxidation layers; these are not included in the simulation but strongly affect low-energy X-ray intensities (pqac-00000034).\\n- **Absorption edge structure:** The continuum under characteristic peaks contains absorption edge structures that are broadened by the detector function; at higher beam energies, the peak fitting residuals show non-physical zero-intensity regions, indicating modeling limitations (pqac-00000034).\\n\\n**For your specific case:** A simulated Al standard would not accurately reproduce the ICC tail that extends from Al K\\u03b1 into the Mg K\\u03b1 region on your specific Octane Plus detector. This tail is the dominant suspected source of your Mg over-estimation, and it is highly detector-specific. A measured Al standard acquired on your own detector is essential to characterize this tail empirically.\\n\\n## 4. Where to Obtain Physical Standards for Al, Si, and Mg\\n\\nThe following table provides a comprehensive listing of standards suppliers and CRMs relevant to your Al-Si-Mg system:\\n\\n<artifact id=\\\"artifact-01\\\"/>\\n\\n**Standards used in the Newbury & Ritchie 2024 study at 5 keV:** At E\\u2080 = 5 keV, their Table 1 explicitly documents the use of **MgO** as the standard for Mg, **Al\\u2082O\\u2083** for Al, and **SiO\\u2082** (or pure Si) for Si (pqac-00000040, pqac-00000041, pqac-00000043). Their materials sources included NIST SRMs (SRM 470 K411/K412, SRM 479, SRM 481, SRM 482, SRM 1871\\u20131875 series), minerals from SPI Supplies (West Chester, PA), stoichiometric compounds from Geller MicroAnalytical Laboratory (Topsfield, MA), and reagent compounds from Alfa Aesar (pqac-00000031, pqac-00000042).\\n\\n**On pure Mg metal as a standard:** Newbury and Ritchie consistently use MgO rather than pure Mg metal for their Mg standard (pqac-00000005, pqac-00000040, pqac-00000041, pqac-00000043). The general principle stated is that when pure elements are \\\"incompatible with vacuum or suffer electron-beam damage,\\\" stoichiometric compounds are substituted (pqac-00000003, pqac-00000005). Pure Mg metal oxidizes rapidly, forming a surface MgO layer that grows under the electron beam and in ambient air; this creates a composite specimen that violates the homogeneity assumption of the k-ratio protocol. The EPMA community conventionally uses MgO (periclase), MgAl\\u2082O\\u2084 (spinel), Mg\\u2082SiO\\u2084 (forsterite), or CaMg(CO\\u2083)\\u2082 (dolomite) as Mg standards, with MgO being the simplest and most widely used.\\n\\n**Specific additional suppliers (not directly verified in the retrieved literature but well-established in the EPMA community):**\\n- **Astimex Standards Ltd** (Toronto, Canada): Supplies mounted pure-element and compound standard blocks commonly used in EPMA laboratories.\\n- **Micro-Analysis Consultants (MAC)** (St. Ives, UK): Supplies mineral and synthetic microanalysis standards.\\n- **Ted Pella, Inc.**: Distributes microanalysis standards and specimen preparation supplies.\\n- **P&H Developments**: Supplies EPMA standard materials.\\n- **Smithsonian microbeam standards collection**: Curated mineral standards used by the Smithsonian Institution's microbeam facility and distributed to the community.\\n\\n*Note: Specific catalogue identifiers for Astimex, MAC, Ted Pella, and P&H Developments were not verified in the retrieved literature and should be confirmed with the vendors' current catalogues.*\\n\\n## 5. Public Repositories of EDS/EPMA Spectra\\n\\n**NIST DTSA-II internal standards database:** The DTSA-II software distribution (freely available from NIST at https://www.nist.gov/services-resources/software/nist-dtsa-ii) includes a built-in standards/k-ratio database. This database contains reference data for standard spectra and compositions used in the k-ratio quantification engine. However, these are primarily used as the software's internal reference framework for matrix corrections rather than as a downloadable library of measured spectra transferable to other instruments (pqac-00000012, pqac-00000014).\\n\\n**EMSA/MAS format (ISO 22029):** The standard data exchange format for microbeam analysis spectra is the EMSA/MAS .msa ASCII format, now codified as ISO 22029 (pqac-00000036). This format is supported by DTSA-II and most vendor software for import/export of EDS spectra.\\n\\n**Key limitation on transferability of archived spectra:** Even when spectra are available in .msa format from repositories or community resources, they are generally usable only as **reference/identification spectra** (for qualitative comparison and peak identification) rather than as quantification standards on a different instrument. This is because the spectra encode the detector-specific response function (resolution, tailing, efficiency) of the instrument on which they were acquired (pqac-00000009, pqac-00000010, pqac-00000012). Newbury and Ritchie's \\\"remote standards\\\" approach can partially address this limitation by applying corrections for spectrometer efficiency differences, but the raw analytical total loses validity and normalization is required (pqac-00000012).\\n\\n**Other resources:**\\n- **de-ma.ch web database** (Allaz, 2024, Microsc. Microanal. 30:489\\u2013500): A web database for electron and X-ray microanalysis to assist lab managers and users. The detailed contents were not fully verified in the retrieved literature.\\n- **NEXL** (Ritchie, 2022, Microsc. Microanal. 28:478\\u2013495): Ritchie's reproducible spectrum and hyperspectrum data analysis framework using a defined data format.\\n- **University of Oregon CAMCOR**: Maintains standard block documentation that can serve as a community reference but is not a downloadable spectral library.\\n- **Zenodo/Figshare deposits**: Individual researchers occasionally deposit EDS datasets; these should be evaluated case-by-case for usability as quantification standards.\\n\\n**Practical conclusion:** No large, publicly downloadable library of measured EDS standard spectra exists that would be directly usable as quantification standards on an arbitrary instrument. The most reliable path remains acquiring your own standards on your own detector.\\n\\n## 6. The Specific Low-kV Case: 5 kV Mg K\\u03b1 in an Al-Rich Matrix\\n\\n**The analytical challenge:** At 5 kV, Mg K\\u03b1 (1.254 keV) and Al K\\u03b1 (1.487 keV) are separated by only ~233 eV. With a typical SDD FWHM of ~55\\u201365 eV at these energies, the peaks are nominally resolved, but the Al K\\u03b1 peak\\u2014which is enormously intense in an 84+ wt% Al matrix\\u2014generates a low-energy tail due to incomplete charge collection that extends beneath the much smaller Mg K\\u03b1 peak. Your measured Mg concentration (0.9\\u20131.6 wt% vs. specification 0.20\\u20130.45 wt%) represents a 2\\u20134\\u00d7 overestimate that is entirely consistent with inadequate characterization of this Al K\\u03b1 low-energy tail artifact in a standardless quantification framework.\\n\\n**Accuracy demonstrated at 5 keV with the k-ratio protocol:** Newbury and Ritchie (2024) systematically tested accuracy at E\\u2080 = 5 keV using NIST DTSA-II with the standards-based k-ratio protocol, making 263 concentration measurements for 39 elements in 113 materials. More than 98% of their results fell within \\u00b15% RDEV, and 82% fell within \\u00b12% RDEV (pqac-00000028, pqac-00000029). This demonstrates that high-accuracy quantification at 5 keV is achievable with proper standards and protocol. Their analytical platform was a JEOL 8500f with a Bruker Quad SDD array (pqac-00000030, pqac-00000031).\\n\\n**Standards selection for Al, Si, Mg at 5 keV:** In the 5 keV study, MgO was used as the Mg standard, Al\\u2082O\\u2083 as the Al standard, and SiO\\u2082 as the Si standard (pqac-00000040, pqac-00000041). These compound standards avoid the surface oxidation problem of pure Mg metal and provide reliable, reproducible compositions.\\n\\n**Practical recommendations for your measurement:**\\n\\n1. **Acquire a measured Al standard spectrum on your own detector.** This is the single most important step to characterize the detector-specific Al K\\u03b1 low-energy tail under Mg K\\u03b1. The Al standard spectrum (pure Al metal or Al\\u2082O\\u2083) serves as both a quantification standard and a peak-shape reference for the MLLS fitting in DTSA-II (pqac-00000016, pqac-00000017, pqac-00000023). In DTSA-II, this is accomplished by setting up a \\\"Standard Bundle\\\" that combines the standard spectrum with peak-shape references (pqac-00000016).\\n\\n2. **Consider acquiring a \\\"blank\\\" spectrum from pure Al** (or an Al-Si binary alloy with no Mg) specifically to characterize and subtract the Al K\\u03b1 tail contribution under the Mg K\\u03b1 region. This provides an empirical characterization of the ICC tailing on your specific Octane Plus detector. The peak fitting residual spectrum after fitting Al should show whether any counts remain in the Mg K\\u03b1 region (pqac-00000017, pqac-00000023).\\n\\n3. **Collect high-count spectra.** For trace-level Mg (0.2\\u20130.45 wt% is in the minor/trace boundary), long acquisition times are needed to improve counting statistics and detection limits. Detection limits scale as C_DL = [3 \\u00d7 N_B^(1/2) / (N_S \\u2212 N_B)] \\u00d7 C_S, and practical LODs can reach ~200\\u2013500 ppm with sufficient counts (pqac-00000018). Total spectrum counts of 3\\u201310 million (0.1\\u20135 keV range) were typical in the Newbury & Ritchie 5 keV study (pqac-00000030, pqac-00000031).\\n\\n4. **Use conservative dead time (~10%).** At 5 kV in an Al-rich matrix, the Al K\\u03b1 peak will be extremely intense. Coincidence peaks (Al+Al at ~2.97 keV, Al+Si, etc.) become significant above ~10\\u201315% dead time and can distort the continuum shape in the fitting region. Choose beam current to keep dead time below 10% on the most highly excited standard (pqac-00000007, pqac-00000046).\\n\\n5. **Surface preparation is critical.** At 5 kV, the electron range is very short (~200\\u2013300 nm in Al), so surface roughness, oxidation, and carbon contamination have a proportionally larger effect. Surface roughness should be <50 nm rms for measurements of photon energies below 1 keV, and the same preparation/coating protocol must be applied to both standards and unknowns (pqac-00000002, pqac-00000007, pqac-00000022). Carbon coatings should be ~8\\u201310 nm and matched between standard and unknown; mismatched coating thickness introduces significant error at low beam energies (pqac-00000004).\\n\\n6. **Inspect the peak fitting residual spectrum.** After fitting Al and Si peaks, inspect the residual spectrum in the Mg K\\u03b1 region to verify whether a genuine Mg peak remains above the fitted background, and whether the residual shows any systematic structure indicating inadequate tail modeling (pqac-00000017, pqac-00000023).\\n\\n7. **The raw analytical total is diagnostic.** When using the k-ratio protocol (not normalized), the raw analytical total should fall near 1.00 (typically 0.98\\u20131.02 at conventional beam energies). At 5 keV, a broader range of 0.8\\u20131.2 is observed even for carefully vetted materials (pqac-00000029, pqac-00000034). A total significantly deviating from unity signals potential problems (missing elements, surface layers, or fitting artifacts).\\n\\n8. **Verify with a known Mg-bearing reference material.** Analyze NIST SRM 470 K412 glass (which contains Mg, Al, Si, Ca, Fe, and O) at 5 keV to validate your Mg measurement against the certified composition before analyzing the AlSi10Mg alloy. This serves as an independent accuracy check for the specific Al-Mg overlap situation on your instrument.\\n\\n**Root cause of your Mg overestimate:** In standardless quantification, the vendor's built-in peak model may not accurately represent the ICC tail of Al K\\u03b1 on your specific Octane Plus detector, leading to systematic misattribution of Al K\\u03b1 tail counts to the Mg K\\u03b1 channel. Switching to standards-based k-ratio quantification with DTSA-II, using a measured Al standard from your own detector as both standard and peak-shape reference, should dramatically reduce this systematic error by empirically capturing the actual detector response (pqac-00000012, pqac-00000014).\\n\"}",
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The EMSA/MAS format (ISO 22029) was identified but detailed keyword list not available in retrieved papers - will use expert knowledge for the format specification details.\",\n      \"evaluation\": \"Multiple citations provide comprehensive list of required metadata for standard spectra.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research transferability of standard spectra between instruments - detector variation, published methodologies\",\n      \"rationale\": \"Question 2 asks about cross-instrument standard reuse, detector response differences, and published transfer methodologies\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from multiple sources: Newbury & Ritchie 2015 on stored standards reuse, Newbury & Ritchie 2011/2019 on remote standards and golden detector approach (Alvisi et al. 2006), Tsuji et al. 2010 on detector response modeling including Scholze and Procop, Ritchie et al. 2018 on detector physics variations.\",\n      \"evaluation\": \"Sufficient evidence gathered on transferability challenges and published methodologies.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research simulated/synthetic standards accuracy - DTSA-II, NISTMonte, Ritchie's papers\",\n      \"rationale\": \"Question 3 asks about Monte Carlo simulated standards and their accuracy vs measured standards\",\n      \"status\": \"completed\",\n      \"result\": \"Found evidence from Newbury & Ritchie 2011 showing DTSA-II simulated vs measured spectra differ by +1.2% (Fe Ka) to +19% (Mg K). Newbury & Ritchie 2015 showed simulated standard analysis of K2496 glass with RDEV within a few percent. Giunto et al. 2025 discusses detector response modeling including ICC. Multiple sources note simulated standards are useful when physical standards unavailable but have limitations at low energy.\",\n      \"evaluation\": \"Sufficient evidence with numerical accuracy figures.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research physical standards suppliers and certified reference materials for Al, Si, Mg\",\n      \"rationale\": \"Question 4 asks for specific CRM suppliers, catalog numbers, and Mg standard alternatives\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 lists NIST SRMs (470 K411/K412, 479, 481, 482, 1871-1875). They used MgO for Mg, Al2O3 for Al, SiO2 for Si at 5 keV. The paper lists SPI (West Chester, PA) for minerals, Geller Microanalytical Laboratory (Topsfield, MA) for stoichiometric compounds, Alfa Aesar for reagent compounds. Newbury & Ritchie 2015 describes use of MgO, KCl, FeS2, GaP, CaF2 as compound standards. Additional supplier information (Astimex, MAC, Ted Pella) from expert knowledge.\",\n      \"evaluation\": \"Concrete supplier names and standards identified with sufficient detail from the literature.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research public repositories of EDS/EPMA spectra\",\n      \"rationale\": \"Question 5 asks about downloadable spectrum libraries in EMSA format\",\n      \"status\": \"completed\",\n      \"result\": \"NIST DTSA-II includes a built-in standards database. The ISO 22029 EMSA/MAS format is the standard format. No large publicly downloadable measured EDS standards library was identified in the literature beyond the DTSA-II internal database. The de-ma.ch web database (Allaz 2024) and Zenodo deposits exist but were not obtainable for detailed review. Remote standards approach described by Newbury & Ritchie.\",\n      \"evaluation\": \"Key resources identified; limitations in publicly available measured standard spectra documented.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-kV (5 kV) quantification specifics for Mg Ka in Al matrix\",\n      \"rationale\": \"Question 6 asks about the specific analytical challenge of trace Mg in Al at low voltage\",\n      \"status\": \"completed\",\n      \"result\": \"Newbury & Ritchie 2024 tested 263 measurements at 5 keV: >98% within \u00b15% RDEV, 82% within \u00b12% RDEV. Multiple papers describe peak overlap issues at low energy, need for careful surface preparation (<50 nm rms roughness), carbon coating effects, detection limit formulas, and standard selection guidance.\",\n      \"evaluation\": \"Strong quantitative evidence from the 2024 paper plus procedural guidance from multiple sources.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Compile all findings into a comprehensive, well-cited answer\",\n      \"status\": \"in-progress\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
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+                    "arguments": "{\"answer\": \"# Standards-Based k-Ratio Quantification for Low-kV SEM-EDS of AlSi10Mg: A Comprehensive Technical Guide\\n\\n## 1. What Is an EDS Standard Spectrum, Informationally?\\n\\nAn EDS standard spectrum is far more than an array of channel counts. For it to be usable in standards-based k-ratio quantification, a standard spectrum must be accompanied by a comprehensive set of metadata that documents the exact conditions under which it was acquired, so that the fundamental ratio k = I_unknown / I_standard is meaningful. The k-ratio protocol requires that unknown and standard be measured \\\"under identical conditions of beam energy, known dose, and detector efficiency\\\" (pqac-00000005). Specifically, the following metadata must be recorded and archived with each standard spectrum:\\n\\n**Instrumental parameters:** beam energy (accelerating voltage), probe current (measured with a Faraday cup and digital picoammeter for rigorous work), live time and real time (to calculate effective dose and dead time), and the EDS detector's process time/time constant (which must remain fixed\\u2014adaptive process time is explicitly discouraged for standards-based work) (pqac-00000000, pqac-00000026). The dead time should be kept below approximately 10% to minimize coincidence artifacts, which grow significantly above ~15% dead time (pqac-00000007, pqac-00000046).\\n\\n**Geometric parameters:** detector elevation (take-off) angle, detector azimuthal angle, specimen tilt (preferably zero), detector-to-specimen distance (which sets the solid angle), and the detector active area (pqac-00000000, pqac-00000002, pqac-00000013).\\n\\n**Detector characterization:** window type and thickness (polymer/Moxtek AP3/AP5 vs. Be vs. windowless), support grid geometry and open area fraction (typically 76\\u201380%), detector dead layer thickness, energy resolution (FWHM at Mn K\\u03b1, typically 122\\u2013150 eV for modern SDDs), and the energy calibration (zero offset and gain, typically 5 eV/channel) (pqac-00000009, pqac-00000026, pqac-00000027, pqac-00000035).\\n\\n**Standard material parameters:** the identity and known composition of the standard (whether certified by an independent method), its microscopic homogeneity (confirmed by EPMA), and its certification traceability (e.g., NIST SRM certificate) (pqac-00000003). When pure elements are incompatible with vacuum or suffer oxidation/beam damage, stoichiometric compounds are substituted\\u2014e.g., MgO for Mg, KCl for K and Cl, FeS\\u2082 for S, GaP for Ga and P, CaF\\u2082 for Ca and F (pqac-00000005).\\n\\n**Sample condition parameters:** surface preparation state (highly polished, not chemically etched; surface roughness <50 nm rms for measurements of photons below 1 keV), coating material and thickness (typically ~8\\u201310 nm carbon), and contamination/oxidation/tarnish state (pqac-00000002, pqac-00000004, pqac-00000007, pqac-00000022).\\n\\n**Administrative parameters:** date and time of acquisition, operator, and instrument identifier (pqac-00000000, pqac-00000013).\\n\\n**The EMSA/MAS .msa format (ISO 22029)** is the standardized spectrum data file format for microbeam analysis, originally defined by Fiori, Swyt, and others and adopted as ISO 22029 \\\"Microbeam Analysis \\u2013 EMSA/MAS Standard File Format for Spectral-Data Exchange\\\" (pqac-00000036). Its required keywords include `#FORMAT`, `#VERSION`, `#TITLE`, `#DATE`, `#TIME`, `#OWNER`, `#NPOINTS`, `#NCOLUMNS`, `#XUNITS`, `#YUNITS`, `#DATATYPE`, `#XPERCHAN`, `#OFFSET`, `#SIGNALTYPE`, and `#SPECTRUM`. Optional but analytically critical keywords include `#BEAMKV`, `#PROBECUR`, `#LIVETIME`, `#REALTIME`, `#ELEVANGLE`, `#AZIMANGLE`, and `#XTILTSTGE`/`#YTILTSTGE`. Notably, the classic EMSA/MAS keyword set does not include dedicated fields for detector window type, dead layer thickness, incomplete charge collection parameters, or FWHM at Mn K\\u03b1\\u2014these must be recorded in comment fields or external documentation. Scott, Wight, and Thorne (2002, Microsc. Microanal. 8:646\\u2013647) proposed extending the format to XML-based \\\"EMSA/MAS 2.0,\\\" but the original ASCII format remains dominant.\\n\\nThe following table summarizes the complete metadata requirements:\\n\\n<artifact id=\\\"artifact-00\\\"/>\\n\\n## 2. Are Standard Spectra Transferable Between Instruments?\\n\\n**The short answer is: generally no, not without significant correction, especially for low-energy lines below ~2 keV.**\\n\\nThe fundamental problem is that the k-ratio protocol requires that unknown and standard spectra be acquired under identical conditions. The stability of modern SDD-EDS detectors permits reuse of previously measured, stored standard spectra on the *same* instrument, provided a quality-assurance protocol confirms that the unknown was measured under the same documented conditions (beam energy, dose, and EDS parameters) (pqac-00000000, pqac-00000013). SDDs show nearly constant resolution and calibration across a wide range of input count rates, which enables practical spectrum archiving on a given instrument (pqac-00000015).\\n\\nHowever, cross-instrument transfer faces several detector-specific barriers:\\n\\n**Resolution differences:** Different SDDs have different FWHM values (typically 122\\u2013150 eV at Mn K\\u03b1), which change peak shapes and the extent of tails under adjacent peaks\\u2014directly relevant to the Al K\\u03b1 tail under Mg K\\u03b1 in your case (pqac-00000010, pqac-00000011, pqac-00000026).\\n\\n**Window transmission:** The choice of window material (polymer/SiN vs. Be vs. windowless) dramatically affects transmission below ~2 keV. Moxtek AP3 and AP5 windows have different thicknesses (380 \\u00b5m vs. 265 \\u00b5m ribs), rib widths, and acceptance angles, creating different low-energy efficiencies (pqac-00000027). Be windows absorb essentially all X-rays below ~1 keV, making spectra taken with Be-window detectors incomparable to those from polymer-window detectors for light-element lines (pqac-00000019).\\n\\n**Silicon dead layer and incomplete charge collection (ICC):** Scholze and Procop modeled the EDS spectral response accounting for statistical and electronic noise, ICC (which causes peak tailing on the low-energy side), escape effects, and fluorescence from the front contact/dead layer (pqac-00000009). These processes are detector-specific and alter both peak shapes and the continuum particularly at low energies. The ICC tailing is the precise artifact creating your Al K\\u03b1 tail under Mg K\\u03b1.\\n\\n**Published \\\"standards transfer\\\" methodologies:** Newbury and Ritchie describe a \\\"remote standards standardless\\\" approach in which a library of standard measurements made on another instrument supplies standard intensities, with calculated corrections applied for beam energy and spectrometer efficiency differences. However, they note that no dose calibration is attempted in this approach, so the raw analytical total has no validity and normalization is required\\u2014thereby removing important diagnostic indicators of geometric or other deviations (pqac-00000012). Newbury and Ritchie (2019) also reference a \\\"golden detector\\\" calibration-transfer technique (from Alvisi et al., 2006), in which a detector calibrated at a synchrotron beamline is used with a carefully chosen reference material to transfer the calibration to other instruments\\u2014an approach they note is inherently more accurate than purely first-principles standardless methods (pqac-00000014, pqac-00000021).\\n\\n**Quantitative accuracy penalty:** When comparing measured and DTSA-II simulated spectra for bulk K411 at 20 keV (a surrogate for cross-instrument transfer using a modeled detector response), Newbury and Ritchie found discrepancies ranging from +1.2% for Fe K\\u03b1 to +19% for Mg K, with the low-energy region showing systematically larger deviations (pqac-00000008, pqac-00000012). This +19% discrepancy for Mg K specifically underscores the severity of the problem for your Mg K\\u03b1 / Al K\\u03b1 overlap situation.\\n\\n**Practical recommendation:** For your specific case (trace Mg K\\u03b1 at 1.254 keV under the tail of the dominant Al K\\u03b1 at 1.487 keV), standard spectra should be acquired on your own EDAX Octane Plus SDD on your Apreo SEM under the same conditions as your unknowns. Cross-instrument transfer of standards is not recommended for this challenging low-energy overlap problem.\\n\\n## 3. Simulated / Synthetic Standards\\n\\nNIST DTSA-II includes built-in spectrum simulation tools (based on NISTMonte, a Monte Carlo electron trajectory simulator) that can generate synthetic standard spectra from first-principles physics to yield absolute intensities (pqac-00000008). The simulation models electron scattering, X-ray generation, self-absorption, secondary fluorescence, and the detector response function.\\n\\n**Published accuracy assessments:**\\n\\nWhen Newbury and Ritchie (2015) used DTSA-II simulated standards to analyze NIST microanalysis glass K2496 at 10 keV, the resulting concentrations were very close to the as-synthesized values, with RDEV values of approximately \\u22121.0% to +1.7% for the constituent elements and precision metrics of ~0.08\\u20131.8% relative (pqac-00000006). This demonstrates that simulated standards can provide accurate quantification for moderate-to-high-energy X-ray lines in well-controlled measurements.\\n\\nHowever, for bulk K411 at 20 keV, a direct comparison of measured and simulated spectra (without scaling) showed discrepancies of +1.2% for Fe K\\u03b1 up to +19% for Mg K (pqac-00000008). The systematically larger error at low photon energies (Mg K at 1.254 keV) reflects the difficulty of accurately modeling the detector response\\u2014particularly ICC, dead layer absorption, and window transmission effects\\u2014in the sub-2 keV energy range.\\n\\n**Where simulated standards are acceptable:** Simulated standards are most useful when a flat, bulk reference of the desired composition is unavailable\\u2014for example, when analyzing irregularly shaped particles or microstructural features. DTSA-II can simulate a bulk reference spectrum from an estimated composition, with a first normalized analysis serving as that estimate (pqac-00000008, pqac-00000012). For higher-energy lines (>2 keV) and well-characterized detector parameters, simulated standards can approach the accuracy of measured standards.\\n\\n**Where simulated standards specifically fail:** The simulation's accuracy critically depends on the fidelity of the detector response model. Key failure modes include:\\n- **Low-energy peak tailing and ICC:** The incomplete charge collection process, which creates low-energy tails on peaks, is detector-specific and difficult to parameterize accurately from first principles. Giunto et al. (2025) note that detector artifacts \\\"particularly below 2 keV\\\" complicate background fitting and quantification (pqac-00000037).\\n- **Contamination layers and surface effects:** Real specimens accumulate carbon contamination and may have oxidation layers; these are not included in the simulation but strongly affect low-energy X-ray intensities (pqac-00000034).\\n- **Absorption edge structure:** The continuum under characteristic peaks contains absorption edge structures that are broadened by the detector function; at higher beam energies, the peak fitting residuals show non-physical zero-intensity regions, indicating modeling limitations (pqac-00000034).\\n\\n**For your specific case:** A simulated Al standard would not accurately reproduce the ICC tail that extends from Al K\\u03b1 into the Mg K\\u03b1 region on your specific Octane Plus detector. This tail is the dominant suspected source of your Mg over-estimation, and it is highly detector-specific. A measured Al standard acquired on your own detector is essential to characterize this tail empirically.\\n\\n## 4. Where to Obtain Physical Standards for Al, Si, and Mg\\n\\nThe following table provides a comprehensive listing of standards suppliers and CRMs relevant to your Al-Si-Mg system:\\n\\n<artifact id=\\\"artifact-01\\\"/>\\n\\n**Standards used in the Newbury & Ritchie 2024 study at 5 keV:** At E\\u2080 = 5 keV, their Table 1 explicitly documents the use of **MgO** as the standard for Mg, **Al\\u2082O\\u2083** for Al, and **SiO\\u2082** (or pure Si) for Si (pqac-00000040, pqac-00000041, pqac-00000043). Their materials sources included NIST SRMs (SRM 470 K411/K412, SRM 479, SRM 481, SRM 482, SRM 1871\\u20131875 series), minerals from SPI Supplies (West Chester, PA), stoichiometric compounds from Geller MicroAnalytical Laboratory (Topsfield, MA), and reagent compounds from Alfa Aesar (pqac-00000031, pqac-00000042).\\n\\n**On pure Mg metal as a standard:** Newbury and Ritchie consistently use MgO rather than pure Mg metal for their Mg standard (pqac-00000005, pqac-00000040, pqac-00000041, pqac-00000043). The general principle stated is that when pure elements are \\\"incompatible with vacuum or suffer electron-beam damage,\\\" stoichiometric compounds are substituted (pqac-00000003, pqac-00000005). Pure Mg metal oxidizes rapidly, forming a surface MgO layer that grows under the electron beam and in ambient air; this creates a composite specimen that violates the homogeneity assumption of the k-ratio protocol. The EPMA community conventionally uses MgO (periclase), MgAl\\u2082O\\u2084 (spinel), Mg\\u2082SiO\\u2084 (forsterite), or CaMg(CO\\u2083)\\u2082 (dolomite) as Mg standards, with MgO being the simplest and most widely used.\\n\\n**Specific additional suppliers (not directly verified in the retrieved literature but well-established in the EPMA community):**\\n- **Astimex Standards Ltd** (Toronto, Canada): Supplies mounted pure-element and compound standard blocks commonly used in EPMA laboratories.\\n- **Micro-Analysis Consultants (MAC)** (St. Ives, UK): Supplies mineral and synthetic microanalysis standards.\\n- **Ted Pella, Inc.**: Distributes microanalysis standards and specimen preparation supplies.\\n- **P&H Developments**: Supplies EPMA standard materials.\\n- **Smithsonian microbeam standards collection**: Curated mineral standards used by the Smithsonian Institution's microbeam facility and distributed to the community.\\n\\n*Note: Specific catalogue identifiers for Astimex, MAC, Ted Pella, and P&H Developments were not verified in the retrieved literature and should be confirmed with the vendors' current catalogues.*\\n\\n## 5. Public Repositories of EDS/EPMA Spectra\\n\\n**NIST DTSA-II internal standards database:** The DTSA-II software distribution (freely available from NIST at https://www.nist.gov/services-resources/software/nist-dtsa-ii) includes a built-in standards/k-ratio database. This database contains reference data for standard spectra and compositions used in the k-ratio quantification engine. However, these are primarily used as the software's internal reference framework for matrix corrections rather than as a downloadable library of measured spectra transferable to other instruments (pqac-00000012, pqac-00000014).\\n\\n**EMSA/MAS format (ISO 22029):** The standard data exchange format for microbeam analysis spectra is the EMSA/MAS .msa ASCII format, now codified as ISO 22029 (pqac-00000036). This format is supported by DTSA-II and most vendor software for import/export of EDS spectra.\\n\\n**Key limitation on transferability of archived spectra:** Even when spectra are available in .msa format from repositories or community resources, they are generally usable only as **reference/identification spectra** (for qualitative comparison and peak identification) rather than as quantification standards on a different instrument. This is because the spectra encode the detector-specific response function (resolution, tailing, efficiency) of the instrument on which they were acquired (pqac-00000009, pqac-00000010, pqac-00000012). Newbury and Ritchie's \\\"remote standards\\\" approach can partially address this limitation by applying corrections for spectrometer efficiency differences, but the raw analytical total loses validity and normalization is required (pqac-00000012).\\n\\n**Other resources:**\\n- **de-ma.ch web database** (Allaz, 2024, Microsc. Microanal. 30:489\\u2013500): A web database for electron and X-ray microanalysis to assist lab managers and users. The detailed contents were not fully verified in the retrieved literature.\\n- **NEXL** (Ritchie, 2022, Microsc. Microanal. 28:478\\u2013495): Ritchie's reproducible spectrum and hyperspectrum data analysis framework using a defined data format.\\n- **University of Oregon CAMCOR**: Maintains standard block documentation that can serve as a community reference but is not a downloadable spectral library.\\n- **Zenodo/Figshare deposits**: Individual researchers occasionally deposit EDS datasets; these should be evaluated case-by-case for usability as quantification standards.\\n\\n**Practical conclusion:** No large, publicly downloadable library of measured EDS standard spectra exists that would be directly usable as quantification standards on an arbitrary instrument. The most reliable path remains acquiring your own standards on your own detector.\\n\\n## 6. The Specific Low-kV Case: 5 kV Mg K\\u03b1 in an Al-Rich Matrix\\n\\n**The analytical challenge:** At 5 kV, Mg K\\u03b1 (1.254 keV) and Al K\\u03b1 (1.487 keV) are separated by only ~233 eV. With a typical SDD FWHM of ~55\\u201365 eV at these energies, the peaks are nominally resolved, but the Al K\\u03b1 peak\\u2014which is enormously intense in an 84+ wt% Al matrix\\u2014generates a low-energy tail due to incomplete charge collection that extends beneath the much smaller Mg K\\u03b1 peak. Your measured Mg concentration (0.9\\u20131.6 wt% vs. specification 0.20\\u20130.45 wt%) represents a 2\\u20134\\u00d7 overestimate that is entirely consistent with inadequate characterization of this Al K\\u03b1 low-energy tail artifact in a standardless quantification framework.\\n\\n**Accuracy demonstrated at 5 keV with the k-ratio protocol:** Newbury and Ritchie (2024) systematically tested accuracy at E\\u2080 = 5 keV using NIST DTSA-II with the standards-based k-ratio protocol, making 263 concentration measurements for 39 elements in 113 materials. More than 98% of their results fell within \\u00b15% RDEV, and 82% fell within \\u00b12% RDEV (pqac-00000028, pqac-00000029). This demonstrates that high-accuracy quantification at 5 keV is achievable with proper standards and protocol. Their analytical platform was a JEOL 8500f with a Bruker Quad SDD array (pqac-00000030, pqac-00000031).\\n\\n**Standards selection for Al, Si, Mg at 5 keV:** In the 5 keV study, MgO was used as the Mg standard, Al\\u2082O\\u2083 as the Al standard, and SiO\\u2082 as the Si standard (pqac-00000040, pqac-00000041). These compound standards avoid the surface oxidation problem of pure Mg metal and provide reliable, reproducible compositions.\\n\\n**Practical recommendations for your measurement:**\\n\\n1. **Acquire a measured Al standard spectrum on your own detector.** This is the single most important step to characterize the detector-specific Al K\\u03b1 low-energy tail under Mg K\\u03b1. The Al standard spectrum (pure Al metal or Al\\u2082O\\u2083) serves as both a quantification standard and a peak-shape reference for the MLLS fitting in DTSA-II (pqac-00000016, pqac-00000017, pqac-00000023). In DTSA-II, this is accomplished by setting up a \\\"Standard Bundle\\\" that combines the standard spectrum with peak-shape references (pqac-00000016).\\n\\n2. **Consider acquiring a \\\"blank\\\" spectrum from pure Al** (or an Al-Si binary alloy with no Mg) specifically to characterize and subtract the Al K\\u03b1 tail contribution under the Mg K\\u03b1 region. This provides an empirical characterization of the ICC tailing on your specific Octane Plus detector. The peak fitting residual spectrum after fitting Al should show whether any counts remain in the Mg K\\u03b1 region (pqac-00000017, pqac-00000023).\\n\\n3. **Collect high-count spectra.** For trace-level Mg (0.2\\u20130.45 wt% is in the minor/trace boundary), long acquisition times are needed to improve counting statistics and detection limits. Detection limits scale as C_DL = [3 \\u00d7 N_B^(1/2) / (N_S \\u2212 N_B)] \\u00d7 C_S, and practical LODs can reach ~200\\u2013500 ppm with sufficient counts (pqac-00000018). Total spectrum counts of 3\\u201310 million (0.1\\u20135 keV range) were typical in the Newbury & Ritchie 5 keV study (pqac-00000030, pqac-00000031).\\n\\n4. **Use conservative dead time (~10%).** At 5 kV in an Al-rich matrix, the Al K\\u03b1 peak will be extremely intense. Coincidence peaks (Al+Al at ~2.97 keV, Al+Si, etc.) become significant above ~10\\u201315% dead time and can distort the continuum shape in the fitting region. Choose beam current to keep dead time below 10% on the most highly excited standard (pqac-00000007, pqac-00000046).\\n\\n5. **Surface preparation is critical.** At 5 kV, the electron range is very short (~200\\u2013300 nm in Al), so surface roughness, oxidation, and carbon contamination have a proportionally larger effect. Surface roughness should be <50 nm rms for measurements of photon energies below 1 keV, and the same preparation/coating protocol must be applied to both standards and unknowns (pqac-00000002, pqac-00000007, pqac-00000022). Carbon coatings should be ~8\\u201310 nm and matched between standard and unknown; mismatched coating thickness introduces significant error at low beam energies (pqac-00000004).\\n\\n6. **Inspect the peak fitting residual spectrum.** After fitting Al and Si peaks, inspect the residual spectrum in the Mg K\\u03b1 region to verify whether a genuine Mg peak remains above the fitted background, and whether the residual shows any systematic structure indicating inadequate tail modeling (pqac-00000017, pqac-00000023).\\n\\n7. **The raw analytical total is diagnostic.** When using the k-ratio protocol (not normalized), the raw analytical total should fall near 1.00 (typically 0.98\\u20131.02 at conventional beam energies). At 5 keV, a broader range of 0.8\\u20131.2 is observed even for carefully vetted materials (pqac-00000029, pqac-00000034). A total significantly deviating from unity signals potential problems (missing elements, surface layers, or fitting artifacts).\\n\\n8. **Verify with a known Mg-bearing reference material.** Analyze NIST SRM 470 K412 glass (which contains Mg, Al, Si, Ca, Fe, and O) at 5 keV to validate your Mg measurement against the certified composition before analyzing the AlSi10Mg alloy. This serves as an independent accuracy check for the specific Al-Mg overlap situation on your instrument.\\n\\n**Root cause of your Mg overestimate:** In standardless quantification, the vendor's built-in peak model may not accurately represent the ICC tail of Al K\\u03b1 on your specific Octane Plus detector, leading to systematic misattribution of Al K\\u03b1 tail counts to the Mg K\\u03b1 channel. Switching to standards-based k-ratio quantification with DTSA-II, using a measured Al standard from your own detector as both standard and peak-shape reference, should dramatically reduce this systematic error by empirically capturing the actual detector response (pqac-00000012, pqac-00000014).\\n\"}",
+                    "name": "answer"
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+      "created_at": "2026-08-21T21:04:16.080140Z"
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+        "created_at": "2026-08-21T21:05:19.477322",
+        "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
+        "request": {},
+        "response": {
+          "answer": {
+            "id": "20cf0cb5-2cd4-49db-8dee-c2cf8e021bfc",
+            "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
+            "answer": "# Standards-Based k-Ratio Quantification for Low-kV SEM-EDS of AlSi10Mg: A Comprehensive Technical Guide\n\n## 1. What Is an EDS Standard Spectrum, Informationally?\n\nAn EDS standard spectrum is far more than an array of channel counts. For it to be usable in standards-based k-ratio quantification, a standard spectrum must be accompanied by a comprehensive set of metadata that documents the exact conditions under which it was acquired, so that the fundamental ratio k = I_unknown / I_standard is meaningful. The k-ratio protocol requires that unknown and standard be measured \"under identical conditions of beam energy, known dose, and detector efficiency\" (newbury2015performingelementalmicroanalysis pages 1-2). Specifically, the following metadata must be recorded and archived with each standard spectrum:\n\n**Instrumental parameters:** beam energy (accelerating voltage), probe current (measured with a Faraday cup and digital picoammeter for rigorous work), live time and real time (to calculate effective dose and dead time), and the EDS detector's process time/time constant (which must remain fixed\u2014adaptive process time is explicitly discouraged for standards-based work) (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 14-15). The dead time should be kept below approximately 10% to minimize coincidence artifacts, which grow significantly above ~15% dead time (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 6-8).\n\n**Geometric parameters:** detector elevation (take-off) angle, detector azimuthal angle, specimen tilt (preferably zero), detector-to-specimen distance (which sets the solid angle), and the detector active area (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4).\n\n**Detector characterization:** window type and thickness (polymer/Moxtek AP3/AP5 vs. Be vs. windowless), support grid geometry and open area fraction (typically 76\u201380%), detector dead layer thickness, energy resolution (FWHM at Mn K\u03b1, typically 122\u2013150 eV for modern SDDs), and the energy calibration (zero offset and gain, typically 5 eV/channel) (tsuji2010xrayspectrometry. pages 9-10, goldstein2018energydispersivexray pages 14-15, goldstein2018energydispersivexray pages 15-16, goldstein2018energydispersivexray pages 18-20).\n\n**Standard material parameters:** the identity and known composition of the standard (whether certified by an independent method), its microscopic homogeneity (confirmed by EPMA), and its certification traceability (e.g., NIST SRM certificate) (newbury2019electronexcitedxraymicroanalysis pages 2-3). When pure elements are incompatible with vacuum or suffer oxidation/beam damage, stoichiometric compounds are substituted\u2014e.g., MgO for Mg, KCl for K and Cl, FeS\u2082 for S, GaP for Ga and P, CaF\u2082 for Ca and F (newbury2015performingelementalmicroanalysis pages 1-2).\n\n**Sample condition parameters:** surface preparation state (highly polished, not chemically etched; surface roughness <50 nm rms for measurements of photons below 1 keV), coating material and thickness (typically ~8\u201310 nm carbon), and contamination/oxidation/tarnish state (newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 9-11, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4).\n\n**Administrative parameters:** date and time of acquisition, operator, and instrument identifier (newbury2015performingelementalmicroanalysis pages 11-13).\n\n**The EMSA/MAS .msa format (ISO 22029)** is the standardized spectrum data file format for microbeam analysis, originally defined by Fiori, Swyt, and others and adopted as ISO 22029 \"Microbeam Analysis \u2013 EMSA/MAS Standard File Format for Spectral-Data Exchange\" (dumit2025challengesandfuture pages 9-10). Its required keywords include `#FORMAT`, `#VERSION`, `#TITLE`, `#DATE`, `#TIME`, `#OWNER`, `#NPOINTS`, `#NCOLUMNS`, `#XUNITS`, `#YUNITS`, `#DATATYPE`, `#XPERCHAN`, `#OFFSET`, `#SIGNALTYPE`, and `#SPECTRUM`. Optional but analytically critical keywords include `#BEAMKV`, `#PROBECUR`, `#LIVETIME`, `#REALTIME`, `#ELEVANGLE`, `#AZIMANGLE`, and `#XTILTSTGE`/`#YTILTSTGE`. Notably, the classic EMSA/MAS keyword set does not include dedicated fields for detector window type, dead layer thickness, incomplete charge collection parameters, or FWHM at Mn K\u03b1\u2014these must be recorded in comment fields or external documentation. Scott, Wight, and Thorne (2002, Microsc. Microanal. 8:646\u2013647) proposed extending the format to XML-based \"EMSA/MAS 2.0,\" but the original ASCII format remains dominant.\n\nThe following table summarizes the complete metadata requirements:\n\n| Metadata Parameter | Description/Purpose | EMSA/MAS Keyword (where applicable) |\n|---|---|---|\n| Beam energy / accelerating voltage | Required because k-ratios are valid only when unknown and standard are measured under the same excitation conditions; changes ionization cross-sections, overvoltage, depth of generation, and matrix corrections. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 1-2, goldstein2018quantitativeanalysisthe pages 1-4) | `#BEAMKV` |\n| Probe current | Needed to document electron dose and to verify reproducibility/linearity of X-ray intensity; rigorous k-ratio work should measure current with a Faraday cup/picoammeter. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 18-20, goldstein2018quantitativeanalysisthe pages 6-8) | `#PROBECUR` |\n| Live time | Dose in EDS is probe current \u00d7 live time; live time, not real time, determines effective dose because dead time removes useful counts. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 16-18, goldstein2018energydispersivexray pages 18-20) | `#LIVETIME` |\n| Real time / dead time | Important to assess pulse pile-up/coincidence and detector operating regime; Newbury & Ritchie recommend conservative operation around ~10% dead time for standards-based work, especially when weak peaks sit near coincidence/tail artifacts. (newbury2015performingelementalmicroanalysis pages 20-21, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 18-20, goldstein2018quantitativeanalysisthe pages 6-8) | `#REALTIME`, `#DEADTIME` |\n| Detector elevation / take-off angle | Required geometric parameter for absorption correction; should match between unknown and standard and be verified physically if necessary. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, goldstein2018energydispersivexray pages 14-15) | often `#ELEVANGLE` or vendor-specific |\n| Detector azimuth angle | Needed because detector orientation changes X-ray path length and effective efficiency; should be fixed and recorded for reusable standards. (newbury2015performingelementalmicroanalysis pages 11-13) | often vendor-specific / not always standardized |\n| Specimen tilt | Changes take-off geometry and absorption; Goldstein/Newbury specify tilt should be controlled, preferably zero for bulk standards unless intentionally used. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4) | often `#XTILTSTGE`, `#YTILTSTGE` or vendor-specific |\n| Detector-to-specimen distance / working distance | Sets solid angle and count rate; must be reproducible between standard and unknown. Off-axis position also changes apparent low-energy efficiency because of window-grid/trap shadowing. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, goldstein2018energydispersivexray pages 15-16) | often `#WORKING`, `#DISTANCE` or vendor-specific |\n| Detector active area / solid angle | Needed to interpret count rate and portability of archived spectra; different detector geometries change throughput and sensitivity. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 9-11) | usually not in classic MSA core keywords; vendor-specific |\n| Detector window type and thickness | Critical below ~2 keV because polymer/SiN vs Be windows transmit low-energy X-rays very differently; affects Mg K, Al K, O K, etc. (tsuji2010xrayspectrometry. pages 9-10, ritchie2018exploringthelimits pages 1-4, tong2026measurementuncertaintiesof pages 8-11, goldstein2018energydispersivexray pages 15-16) | usually vendor-specific / not a required classic MSA keyword |\n| Window support grid / electron trap details | Off-axis shadowing and low-energy attenuation can change intensity and background, especially for light elements. (goldstein2018energydispersivexray pages 15-16) | vendor-specific |\n| Detector dead layer / front contact / Si absorption characteristics | Needed when comparing detectors or simulating spectra because fluorescence in dead layer, escape peaks, and efficiency roll-off alter low-energy response. (tsuji2010xrayspectrometry. pages 9-10, goldstein2018energydispersivexray pages 1-2) | vendor-specific |\n| Detector response function / incomplete charge collection behavior | Essential for fitting trace peaks under tails; low-energy tailing and peak-shape differences are detector-specific and limit transferability of standard spectra. (tsuji2010xrayspectrometry. pages 9-10, newbury2011isscanningelectron pages 13-16, giunto2025harnessingautomatedsemeds pages 4-6) | not represented in classic MSA keyword set |\n| Energy calibration zero offset | Required so standard and unknown spectra align channel-for-channel for integrated-peak k-ratios and peak fitting. (goldstein2018quantitativeanalysisthe pages 1-4, goldstein2018energydispersivexray pages 18-20) | `#OFFSET` |\n| Energy calibration gain / channel width | Required to define energy-per-channel; Goldstein recommends fixed channel width (e.g., 5 eV/channel) and consistent calibration. (goldstein2018quantitativeanalysisthe pages 1-4, goldstein2018energydispersivexray pages 18-20) | `#XPERCHAN`, sometimes paired with `#OFFSET` |\n| Number of channels / energy range | Needed to reconstruct spectrum and assure same fitting range; spectra should span low-energy region through the Duane\u2013Hunt limit. (goldstein2018quantitativeanalysisthe pages 1-4, goldstein2018energydispersivexray pages 18-20) | `#NPOINTS`, `#XUNITS` |\n| Energy resolution / FWHM at Mn K\u03b1 | Peak overlap sensitivity depends on detector resolution; should be documented because different FWHM values change deconvolution and low-energy tail contributions. (goldstein2018energydispersivexray pages 14-15, ritchie2018exploringthelimits pages 1-4, goldstein2018energydispersivexray pages 1-2) | often `#MNFWHM` or vendor-specific |\n| Process time / shaping time / time constant | Must be fixed; adaptive process time is specifically discouraged for standards-based quantification because it changes peak shape and resolution. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 14-15) | often `#TIMECNST` or vendor-specific |\n| Count total / integrated counts | High-count spectra are needed for robust MLLS fitting and trace-level overlap correction; archive the total counts or dose associated with the standard. (newbury2015performingelementalmicroanalysis pages 20-21, newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 17-20) | `#DATATYPE` with counts array; total counts often derived or vendor-specific |\n| Standard identity | The material used as the standard must be named explicitly so composition, homogeneity, and suitability can be checked. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2, newbury2019electronexcitedxraymicroanalysis pages 5-6, newbury2024testingtheaccuracy pages 1-3) | `#SAMPLE` |\n| Standard composition | Required because k-ratio denominator must correspond to a known concentration in the standard. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2, newbury2019electronexcitedxraymicroanalysis pages 5-6, newbury2024testingtheaccuracy pages 1-3) | no single core keyword; usually comment/header text |\n| Certification / traceability | For rigorous work, the standard composition should be certified or independently established and microscopically homogeneous. (newbury2015performingelementalmicroanalysis pages 2-4, newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2024testingtheaccuracy pages 1-3) | usually comment/header text |\n| Date/time of acquisition | Needed for traceability, detector stability checks, and QA of archived reusable standards. (newbury2015performingelementalmicroanalysis pages 11-13) | `#DATE`, `#TIME` |\n| Operator / instrument identifier | Supports QA and cross-checking of archived standards; important when spectra are reused. (newbury2015performingelementalmicroanalysis pages 11-13) | `#OWNER`, `#TITLE`, vendor-specific instrument fields |\n| Specimen surface preparation state | Surface roughness/topography directly affects low-energy X-rays; for photons below ~1 keV surfaces should be extremely flat, and standards/unknowns should be prepared similarly. (newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4) | usually comment/header text |\n| Coating material and thickness | Carbon or metal coatings absorb low-energy X-rays; mismatch between standard and unknown coatings can cause significant error at low kV. (newbury2015performingelementalmicroanalysis pages 9-11, newbury2015performingelementalmicroanalysis pages 11-13, newbury2024testingtheaccuracy pages 22-24) | usually comment/header text |\n| Contamination / oxidation / tarnish state | Surface films create composite specimens and strongly bias low-energy analysis; should be documented, especially for reactive standards like Mg-bearing materials. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2024testingtheaccuracy pages 22-24) | usually comment/header text |\n| Vacuum / chamber conditions | Useful for assessing contamination growth and detector performance stability during acquisition. (newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2024testingtheaccuracy pages 22-24) | vendor-specific |\n| Peak-family / line selection used for quantification | EDS often quantifies whole line families rather than a single line; the selected family must be known to interpret k-ratios and matrix corrections. (newbury2015performingelementalmicroanalysis pages 1-2, ritchie2018exploringthelimits pages 4-5) | usually analysis metadata, not core MSA |\n| Background/fit model or peak-shape reference linkage | Particularly valuable for trace-overlap cases, because usability of a stored standard also depends on the associated peak-shape references and fitting strategy. (ritchie2018exploringthelimits pages 4-5, newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9) | not in classic MSA core; DTSA-II/project metadata |\n| QA status / same-conditions verification | Archived standards are reusable only if a QA protocol confirms the unknown was measured under the same beam energy, dose, and EDS parameters. (newbury2015performingelementalmicroanalysis pages 11-13) | not a classic MSA keyword; external QA record |\n\n\n*Table: This table summarizes the metadata that must accompany an EDS standard spectrum for rigorous standards-based k-ratio quantification. It combines the practical requirements emphasized by Goldstein/Newbury/Ritchie with the fields typically represented in the EMSA/MAS .msa format and notes where classic MSA keywords are incomplete for modern detector-response details.*\n\n## 2. Are Standard Spectra Transferable Between Instruments?\n\n**The short answer is: generally no, not without significant correction, especially for low-energy lines below ~2 keV.**\n\nThe fundamental problem is that the k-ratio protocol requires that unknown and standard spectra be acquired under identical conditions. The stability of modern SDD-EDS detectors permits reuse of previously measured, stored standard spectra on the *same* instrument, provided a quality-assurance protocol confirms that the unknown was measured under the same documented conditions (beam energy, dose, and EDS parameters) (newbury2015performingelementalmicroanalysis pages 11-13). SDDs show nearly constant resolution and calibration across a wide range of input count rates, which enables practical spectrum archiving on a given instrument (newbury2015performingelementalmicroanalysis pages 9-11).\n\nHowever, cross-instrument transfer faces several detector-specific barriers:\n\n**Resolution differences:** Different SDDs have different FWHM values (typically 122\u2013150 eV at Mn K\u03b1), which change peak shapes and the extent of tails under adjacent peaks\u2014directly relevant to the Al K\u03b1 tail under Mg K\u03b1 in your case (ritchie2018exploringthelimits pages 1-4, goldstein2018energydispersivexray pages 1-2, goldstein2018energydispersivexray pages 14-15).\n\n**Window transmission:** The choice of window material (polymer/SiN vs. Be vs. windowless) dramatically affects transmission below ~2 keV. Moxtek AP3 and AP5 windows have different thicknesses (380 \u00b5m vs. 265 \u00b5m ribs), rib widths, and acceptance angles, creating different low-energy efficiencies (goldstein2018energydispersivexray pages 15-16). Be windows absorb essentially all X-rays below ~1 keV, making spectra taken with Be-window detectors incomparable to those from polymer-window detectors for light-element lines (tong2026measurementuncertaintiesof pages 8-11).\n\n**Silicon dead layer and incomplete charge collection (ICC):** Scholze and Procop modeled the EDS spectral response accounting for statistical and electronic noise, ICC (which causes peak tailing on the low-energy side), escape effects, and fluorescence from the front contact/dead layer (tsuji2010xrayspectrometry. pages 9-10). These processes are detector-specific and alter both peak shapes and the continuum particularly at low energies. The ICC tailing is the precise artifact creating your Al K\u03b1 tail under Mg K\u03b1.\n\n**Published \"standards transfer\" methodologies:** Newbury and Ritchie describe a \"remote standards standardless\" approach in which a library of standard measurements made on another instrument supplies standard intensities, with calculated corrections applied for beam energy and spectrometer efficiency differences. However, they note that no dose calibration is attempted in this approach, so the raw analytical total has no validity and normalization is required\u2014thereby removing important diagnostic indicators of geometric or other deviations (newbury2011isscanningelectron pages 13-16). Newbury and Ritchie (2019) also reference a \"golden detector\" calibration-transfer technique (from Alvisi et al., 2006), in which a detector calibrated at a synchrotron beamline is used with a carefully chosen reference material to transfer the calibration to other instruments\u2014an approach they note is inherently more accurate than purely first-principles standardless methods (newbury2019electronexcitedxraymicroanalysis pages 16-18).\n\n**Quantitative accuracy penalty:** When comparing measured and DTSA-II simulated spectra for bulk K411 at 20 keV (a surrogate for cross-instrument transfer using a modeled detector response), Newbury and Ritchie found discrepancies ranging from +1.2% for Fe K\u03b1 to +19% for Mg K, with the low-energy region showing systematically larger deviations (newbury2011isscanningelectron pages 13-16). This +19% discrepancy for Mg K specifically underscores the severity of the problem for your Mg K\u03b1 / Al K\u03b1 overlap situation.\n\n**Practical recommendation:** For your specific case (trace Mg K\u03b1 at 1.254 keV under the tail of the dominant Al K\u03b1 at 1.487 keV), standard spectra should be acquired on your own EDAX Octane Plus SDD on your Apreo SEM under the same conditions as your unknowns. Cross-instrument transfer of standards is not recommended for this challenging low-energy overlap problem.\n\n## 3. Simulated / Synthetic Standards\n\nNIST DTSA-II includes built-in spectrum simulation tools (based on NISTMonte, a Monte Carlo electron trajectory simulator) that can generate synthetic standard spectra from first-principles physics to yield absolute intensities (newbury2011isscanningelectron pages 13-16). The simulation models electron scattering, X-ray generation, self-absorption, secondary fluorescence, and the detector response function.\n\n**Published accuracy assessments:**\n\nWhen Newbury and Ritchie (2015) used DTSA-II simulated standards to analyze NIST microanalysis glass K2496 at 10 keV, the resulting concentrations were very close to the as-synthesized values, with RDEV values of approximately \u22121.0% to +1.7% for the constituent elements and precision metrics of ~0.08\u20131.8% relative (newbury2015performingelementalmicroanalysis pages 20-21). This demonstrates that simulated standards can provide accurate quantification for moderate-to-high-energy X-ray lines in well-controlled measurements.\n\nHowever, for bulk K411 at 20 keV, a direct comparison of measured and simulated spectra (without scaling) showed discrepancies of +1.2% for Fe K\u03b1 up to +19% for Mg K (newbury2011isscanningelectron pages 13-16). The systematically larger error at low photon energies (Mg K at 1.254 keV) reflects the difficulty of accurately modeling the detector response\u2014particularly ICC, dead layer absorption, and window transmission effects\u2014in the sub-2 keV energy range.\n\n**Where simulated standards are acceptable:** Simulated standards are most useful when a flat, bulk reference of the desired composition is unavailable\u2014for example, when analyzing irregularly shaped particles or microstructural features. DTSA-II can simulate a bulk reference spectrum from an estimated composition, with a first normalized analysis serving as that estimate (newbury2011isscanningelectron pages 13-16). For higher-energy lines (>2 keV) and well-characterized detector parameters, simulated standards can approach the accuracy of measured standards.\n\n**Where simulated standards specifically fail:** The simulation's accuracy critically depends on the fidelity of the detector response model. Key failure modes include:\n- **Low-energy peak tailing and ICC:** The incomplete charge collection process, which creates low-energy tails on peaks, is detector-specific and difficult to parameterize accurately from first principles. Giunto et al. (2025) note that detector artifacts \"particularly below 2 keV\" complicate background fitting and quantification (giunto2025harnessingautomatedsemeds pages 4-6).\n- **Contamination layers and surface effects:** Real specimens accumulate carbon contamination and may have oxidation layers; these are not included in the simulation but strongly affect low-energy X-ray intensities (newbury2024testingtheaccuracy pages 22-24).\n- **Absorption edge structure:** The continuum under characteristic peaks contains absorption edge structures that are broadened by the detector function; at higher beam energies, the peak fitting residuals show non-physical zero-intensity regions, indicating modeling limitations (newbury2024testingtheaccuracy pages 22-24).\n\n**For your specific case:** A simulated Al standard would not accurately reproduce the ICC tail that extends from Al K\u03b1 into the Mg K\u03b1 region on your specific Octane Plus detector. This tail is the dominant suspected source of your Mg over-estimation, and it is highly detector-specific. A measured Al standard acquired on your own detector is essential to characterize this tail empirically.\n\n## 4. Where to Obtain Physical Standards for Al, Si, and Mg\n\nThe following table provides a comprehensive listing of standards suppliers and CRMs relevant to your Al-Si-Mg system:\n\n| Supplier/Source | Product/CRM | Catalogue/SRM Number | Elements/Composition | Notes |\n|---|---|---|---|---|\n| NIST | Glass for microanalysis, K411 | SRM 470 K411 | O-Mg-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; useful as a multi-element glass containing Mg and Si. (newbury2024testingtheaccuracy pages 1-3) |\n| NIST | Glass for microanalysis, K412 | SRM 470 K412 | O-Mg-Al-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; directly relevant to Al-Mg-Si calibration and overlap studies. (newbury2024testingtheaccuracy pages 1-3) |\n| NIST | Gold-silver alloy set | SRM 481 | Au-Ag alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study as a certified alloy series suitable for microanalysis challenge specimens and standards work. (newbury2024testingtheaccuracy pages 1-3) |\n| NIST | Gold-copper alloy set | SRM 482 | Au-Cu alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study; Newbury & Ritchie also discuss spectra of SRM 482 at multiple beam energies. (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 22-24) |\n| NIST | Stainless steel CRM | SRM 479 | Fe-Cr-Ni stainless steel | Explicitly listed in the 5 kV study among NIST microanalysis challenge materials. (newbury2024testingtheaccuracy pages 1-3) |\n| NIST | Transformer steel CRM | SRM 483 | Fe-3Si steel | Mentioned by Newbury & Ritchie 2019 as an EPMA/EDS reference material in quantitative work. (newbury2019electronexcitedxraymicroanalysis pages 5-6) |\n| NIST | Thin-film microanalysis SRM | SRM 2063a | Thin film; composition not verified here | Relevant NIST microanalysis SRM class, but exact composition/details were not verified in the retrieved sources; include only after checking the current NIST certificate. |\n| NIST | K-glass / oxide glass series | SRM 1871, 1872, 1873, 1875 | SRM 1871 K456: O-Si-Pb; SRM 1872 K453: O-Ge-Pb; SRM 1873 K458: O-Si-Zn-Ba; SRM 1875 K496: O-Mg-Al-P | Explicitly listed in the 5 kV study as microanalysis-qualified SRMs. SRM 1875 is especially relevant because it contains Mg and Al. (newbury2024testingtheaccuracy pages 1-3) |\n| Geller MicroAnalytical Laboratory (Topsfield, MA, USA) | Stoichiometric binary compounds prepared for microanalysis | Vendor product line; specific catalogue IDs not verified here | MgO, Al2O3, SiO2, TiN, TiO2, Cr2N, etc. | Explicitly named by Newbury & Ritchie 2024 as a source of stoichiometric compounds with surfaces prepared for microanalysis. Recommended route for MgO, Al2O3, SiO2 standards. (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 14-16) |\n| SPI Supplies (West Chester, PA, USA) | Mineral standards / well-characterized minerals | Vendor product line; specific catalogue IDs not verified here | Minerals such as calcite, dolomite, fluorapatite, wollastonite, zircon; user-requested examples periclase/forsterite/spinel should be checked in current catalog | Explicitly named by Newbury & Ritchie 2024 as a source of minerals of known composition and micro-homogeneity used in the challenge set. (newbury2024testingtheaccuracy pages 1-3) |\n| Astimex Standards Ltd (Toronto, Canada) | Mounted pure-element and compound microanalysis standards | Vendor product line; specific catalogue IDs not verified here | Pure Al, Si, alloys, oxides, silicates, custom mounts | Common EPMA/SEM-EDS supplier, but specific products were not verified in the retrieved literature; check current catalog for Al, Si, Mg-bearing mounts before purchase. |\n| Ted Pella, Inc. | Microanalysis standards and mounts | Vendor product line; specific catalogue IDs not verified here | Pure elements, compounds, calibration mounts | Widely used supplier, but no product-specific verification in retrieved sources; confirm current catalog details. |\n| Micro-Analysis Consultants (MAC), St Ives, UK | Mineral and synthetic EPMA standards | Vendor product line; specific catalogue IDs not verified here | Silicates, oxides, sulfides, synthetic compounds | Common EPMA standards source, but exact catalog entries were not verified in retrieved sources. |\n| P&H Developments | Electron microprobe standards | Vendor product line; specific catalogue IDs not verified here | Mineral and synthetic standards | Named by user request; no product-specific verification found in retrieved sources, so verify directly with supplier. |\n| Alfa Aesar (now Thermo Fisher chemicals) | Reagent compounds | Reagent-grade products; specific catalogue IDs not verified here | BaTiO3, PbS, MoS2 and other compounds | Explicitly named by Newbury & Ritchie 2024 as source of reagent compounds used as challenge specimens; reagent grade is not automatically a microanalysis standard, so homogeneity/prep must be checked. (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 14-16) |\n| Smithsonian microbeam standards collection | Mineral reference materials | Collection-level resource; no single catalogue number | Mineral standards, including Mg-bearing silicates/carbonates depending on collection | Valuable institutional standards resource, but not documented in the retrieved contexts; verify access and material list directly with Smithsonian microbeam facility. |\n| Recommended Mg standard chemistry | MgO (periclase chemistry) | Not a single catalog number | Mg and O | Newbury & Ritchie\u2019s 5 kV study repeatedly used MgO as the Mg standard; their standards table maps Mg to MgO at 5 kV. This is the best-supported Mg standard in the retrieved sources. (newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18) |\n| Recommended Al standard chemistry | Al2O3 | Not a single catalog number | Al and O | In the 5 kV study, Al was standardized with Al2O3 in the standards table; practical if oxide standards are already in the block. (newbury2024testingtheaccuracy pages 14-16) |\n| Recommended Si standard chemistry | SiO2 or pure Si | Not a single catalog number | Si and O, or Si | The 5 kV study shows SiO2 used as a Si standard in multiple entries; Newbury & Ritchie also note that pure Si can be used among pure-element standards. (newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18) |\n| Caution on pure Mg metal | Pure Mg metal | Not recommended as first-choice standard for routine low-kV SEM-EDS | Mg metal, rapidly oxidizing surface | Not directly evaluated in the retrieved papers, but the literature retrieved strongly supports substitution with MgO; this is consistent with the practical oxidation/contamination problem for Mg metal and the repeated use of stoichiometric compounds when pure elements are unstable. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2, newbury2024testingtheaccuracy pages 16-18) |\n\n\n*Table: This table summarizes physical standards sources and certified reference materials relevant to Al, Si, and Mg SEM-EDS/EPMA work, emphasizing items explicitly documented in the Newbury & Ritchie 2024 5 kV study. It distinguishes directly verified standards from commonly used suppliers whose current catalogue details should still be checked before procurement.*\n\n**Standards used in the Newbury & Ritchie 2024 study at 5 keV:** At E\u2080 = 5 keV, their Table 1 explicitly documents the use of **MgO** as the standard for Mg, **Al\u2082O\u2083** for Al, and **SiO\u2082** (or pure Si) for Si (newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18). Their materials sources included NIST SRMs (SRM 470 K411/K412, SRM 479, SRM 481, SRM 482, SRM 1871\u20131875 series), minerals from SPI Supplies (West Chester, PA), stoichiometric compounds from Geller MicroAnalytical Laboratory (Topsfield, MA), and reagent compounds from Alfa Aesar (newbury2024testingtheaccuracy pages 1-3).\n\n**On pure Mg metal as a standard:** Newbury and Ritchie consistently use MgO rather than pure Mg metal for their Mg standard (newbury2015performingelementalmicroanalysis pages 1-2, newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18). The general principle stated is that when pure elements are \"incompatible with vacuum or suffer electron-beam damage,\" stoichiometric compounds are substituted (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2). Pure Mg metal oxidizes rapidly, forming a surface MgO layer that grows under the electron beam and in ambient air; this creates a composite specimen that violates the homogeneity assumption of the k-ratio protocol. The EPMA community conventionally uses MgO (periclase), MgAl\u2082O\u2084 (spinel), Mg\u2082SiO\u2084 (forsterite), or CaMg(CO\u2083)\u2082 (dolomite) as Mg standards, with MgO being the simplest and most widely used.\n\n**Specific additional suppliers (not directly verified in the retrieved literature but well-established in the EPMA community):**\n- **Astimex Standards Ltd** (Toronto, Canada): Supplies mounted pure-element and compound standard blocks commonly used in EPMA laboratories.\n- **Micro-Analysis Consultants (MAC)** (St. Ives, UK): Supplies mineral and synthetic microanalysis standards.\n- **Ted Pella, Inc.**: Distributes microanalysis standards and specimen preparation supplies.\n- **P&H Developments**: Supplies EPMA standard materials.\n- **Smithsonian microbeam standards collection**: Curated mineral standards used by the Smithsonian Institution's microbeam facility and distributed to the community.\n\n*Note: Specific catalogue identifiers for Astimex, MAC, Ted Pella, and P&H Developments were not verified in the retrieved literature and should be confirmed with the vendors' current catalogues.*\n\n## 5. Public Repositories of EDS/EPMA Spectra\n\n**NIST DTSA-II internal standards database:** The DTSA-II software distribution (freely available from NIST at https://www.nist.gov/services-resources/software/nist-dtsa-ii) includes a built-in standards/k-ratio database. This database contains reference data for standard spectra and compositions used in the k-ratio quantification engine. However, these are primarily used as the software's internal reference framework for matrix corrections rather than as a downloadable library of measured spectra transferable to other instruments (newbury2011isscanningelectron pages 13-16, newbury2019electronexcitedxraymicroanalysis pages 16-18).\n\n**EMSA/MAS format (ISO 22029):** The standard data exchange format for microbeam analysis spectra is the EMSA/MAS .msa ASCII format, now codified as ISO 22029 (dumit2025challengesandfuture pages 9-10). This format is supported by DTSA-II and most vendor software for import/export of EDS spectra.\n\n**Key limitation on transferability of archived spectra:** Even when spectra are available in .msa format from repositories or community resources, they are generally usable only as **reference/identification spectra** (for qualitative comparison and peak identification) rather than as quantification standards on a different instrument. This is because the spectra encode the detector-specific response function (resolution, tailing, efficiency) of the instrument on which they were acquired (tsuji2010xrayspectrometry. pages 9-10, ritchie2018exploringthelimits pages 1-4, newbury2011isscanningelectron pages 13-16). Newbury and Ritchie's \"remote standards\" approach can partially address this limitation by applying corrections for spectrometer efficiency differences, but the raw analytical total loses validity and normalization is required (newbury2011isscanningelectron pages 13-16).\n\n**Other resources:**\n- **de-ma.ch web database** (Allaz, 2024, Microsc. Microanal. 30:489\u2013500): A web database for electron and X-ray microanalysis to assist lab managers and users. The detailed contents were not fully verified in the retrieved literature.\n- **NEXL** (Ritchie, 2022, Microsc. Microanal. 28:478\u2013495): Ritchie's reproducible spectrum and hyperspectrum data analysis framework using a defined data format.\n- **University of Oregon CAMCOR**: Maintains standard block documentation that can serve as a community reference but is not a downloadable spectral library.\n- **Zenodo/Figshare deposits**: Individual researchers occasionally deposit EDS datasets; these should be evaluated case-by-case for usability as quantification standards.\n\n**Practical conclusion:** No large, publicly downloadable library of measured EDS standard spectra exists that would be directly usable as quantification standards on an arbitrary instrument. The most reliable path remains acquiring your own standards on your own detector.\n\n## 6. The Specific Low-kV Case: 5 kV Mg K\u03b1 in an Al-Rich Matrix\n\n**The analytical challenge:** At 5 kV, Mg K\u03b1 (1.254 keV) and Al K\u03b1 (1.487 keV) are separated by only ~233 eV. With a typical SDD FWHM of ~55\u201365 eV at these energies, the peaks are nominally resolved, but the Al K\u03b1 peak\u2014which is enormously intense in an 84+ wt% Al matrix\u2014generates a low-energy tail due to incomplete charge collection that extends beneath the much smaller Mg K\u03b1 peak. Your measured Mg concentration (0.9\u20131.6 wt% vs. specification 0.20\u20130.45 wt%) represents a 2\u20134\u00d7 overestimate that is entirely consistent with inadequate characterization of this Al K\u03b1 low-energy tail artifact in a standardless quantification framework.\n\n**Accuracy demonstrated at 5 keV with the k-ratio protocol:** Newbury and Ritchie (2024) systematically tested accuracy at E\u2080 = 5 keV using NIST DTSA-II with the standards-based k-ratio protocol, making 263 concentration measurements for 39 elements in 113 materials. More than 98% of their results fell within \u00b15% RDEV, and 82% fell within \u00b12% RDEV (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 18-22). This demonstrates that high-accuracy quantification at 5 keV is achievable with proper standards and protocol. Their analytical platform was a JEOL 8500f with a Bruker Quad SDD array (newbury2024testingtheaccuracy pages 4-6, newbury2024testingtheaccuracy pages 1-3).\n\n**Standards selection for Al, Si, Mg at 5 keV:** In the 5 keV study, MgO was used as the Mg standard, Al\u2082O\u2083 as the Al standard, and SiO\u2082 as the Si standard (newbury2024testingtheaccuracy pages 14-16). These compound standards avoid the surface oxidation problem of pure Mg metal and provide reliable, reproducible compositions.\n\n**Practical recommendations for your measurement:**\n\n1. **Acquire a measured Al standard spectrum on your own detector.** This is the single most important step to characterize the detector-specific Al K\u03b1 low-energy tail under Mg K\u03b1. The Al standard spectrum (pure Al metal or Al\u2082O\u2083) serves as both a quantification standard and a peak-shape reference for the MLLS fitting in DTSA-II (ritchie2018exploringthelimits pages 4-5, newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9). In DTSA-II, this is accomplished by setting up a \"Standard Bundle\" that combines the standard spectrum with peak-shape references (ritchie2018exploringthelimits pages 4-5).\n\n2. **Consider acquiring a \"blank\" spectrum from pure Al** (or an Al-Si binary alloy with no Mg) specifically to characterize and subtract the Al K\u03b1 tail contribution under the Mg K\u03b1 region. This provides an empirical characterization of the ICC tailing on your specific Octane Plus detector. The peak fitting residual spectrum after fitting Al should show whether any counts remain in the Mg K\u03b1 region (newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9).\n\n3. **Collect high-count spectra.** For trace-level Mg (0.2\u20130.45 wt% is in the minor/trace boundary), long acquisition times are needed to improve counting statistics and detection limits. Detection limits scale as C_DL = [3 \u00d7 N_B^(1/2) / (N_S \u2212 N_B)] \u00d7 C_S, and practical LODs can reach ~200\u2013500 ppm with sufficient counts (newbury2019electronexcitedxraymicroanalysis pages 13-15). Total spectrum counts of 3\u201310 million (0.1\u20135 keV range) were typical in the Newbury & Ritchie 5 keV study (newbury2024testingtheaccuracy pages 4-6, newbury2024testingtheaccuracy pages 1-3).\n\n4. **Use conservative dead time (~10%).** At 5 kV in an Al-rich matrix, the Al K\u03b1 peak will be extremely intense. Coincidence peaks (Al+Al at ~2.97 keV, Al+Si, etc.) become significant above ~10\u201315% dead time and can distort the continuum shape in the fitting region. Choose beam current to keep dead time below 10% on the most highly excited standard (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 6-8).\n\n5. **Surface preparation is critical.** At 5 kV, the electron range is very short (~200\u2013300 nm in Al), so surface roughness, oxidation, and carbon contamination have a proportionally larger effect. Surface roughness should be <50 nm rms for measurements of photon energies below 1 keV, and the same preparation/coating protocol must be applied to both standards and unknowns (newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4). Carbon coatings should be ~8\u201310 nm and matched between standard and unknown; mismatched coating thickness introduces significant error at low beam energies (newbury2015performingelementalmicroanalysis pages 9-11).\n\n6. **Inspect the peak fitting residual spectrum.** After fitting Al and Si peaks, inspect the residual spectrum in the Mg K\u03b1 region to verify whether a genuine Mg peak remains above the fitted background, and whether the residual shows any systematic structure indicating inadequate tail modeling (newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9).\n\n7. **The raw analytical total is diagnostic.** When using the k-ratio protocol (not normalized), the raw analytical total should fall near 1.00 (typically 0.98\u20131.02 at conventional beam energies). At 5 keV, a broader range of 0.8\u20131.2 is observed even for carefully vetted materials (newbury2024testingtheaccuracy pages 18-22, newbury2024testingtheaccuracy pages 22-24). A total significantly deviating from unity signals potential problems (missing elements, surface layers, or fitting artifacts).\n\n8. **Verify with a known Mg-bearing reference material.** Analyze NIST SRM 470 K412 glass (which contains Mg, Al, Si, Ca, Fe, and O) at 5 keV to validate your Mg measurement against the certified composition before analyzing the AlSi10Mg alloy. This serves as an independent accuracy check for the specific Al-Mg overlap situation on your instrument.\n\n**Root cause of your Mg overestimate:** In standardless quantification, the vendor's built-in peak model may not accurately represent the ICC tail of Al K\u03b1 on your specific Octane Plus detector, leading to systematic misattribution of Al K\u03b1 tail counts to the Mg K\u03b1 channel. Switching to standards-based k-ratio quantification with DTSA-II, using a measured Al standard from your own detector as both standard and peak-shape reference, should dramatically reduce this systematic error by empirically capturing the actual detector response (newbury2011isscanningelectron pages 13-16, newbury2019electronexcitedxraymicroanalysis pages 16-18).\n",
+            "raw_answer": "# Standards-Based k-Ratio Quantification for Low-kV SEM-EDS of AlSi10Mg: A Comprehensive Technical Guide\n\n## 1. What Is an EDS Standard Spectrum, Informationally?\n\nAn EDS standard spectrum is far more than an array of channel counts. For it to be usable in standards-based k-ratio quantification, a standard spectrum must be accompanied by a comprehensive set of metadata that documents the exact conditions under which it was acquired, so that the fundamental ratio k = I_unknown / I_standard is meaningful. The k-ratio protocol requires that unknown and standard be measured \"under identical conditions of beam energy, known dose, and detector efficiency\" (pqac-00000005). Specifically, the following metadata must be recorded and archived with each standard spectrum:\n\n**Instrumental parameters:** beam energy (accelerating voltage), probe current (measured with a Faraday cup and digital picoammeter for rigorous work), live time and real time (to calculate effective dose and dead time), and the EDS detector's process time/time constant (which must remain fixed\u2014adaptive process time is explicitly discouraged for standards-based work) (pqac-00000000, pqac-00000026). The dead time should be kept below approximately 10% to minimize coincidence artifacts, which grow significantly above ~15% dead time (pqac-00000007, pqac-00000046).\n\n**Geometric parameters:** detector elevation (take-off) angle, detector azimuthal angle, specimen tilt (preferably zero), detector-to-specimen distance (which sets the solid angle), and the detector active area (pqac-00000000, pqac-00000002, pqac-00000013).\n\n**Detector characterization:** window type and thickness (polymer/Moxtek AP3/AP5 vs. Be vs. windowless), support grid geometry and open area fraction (typically 76\u201380%), detector dead layer thickness, energy resolution (FWHM at Mn K\u03b1, typically 122\u2013150 eV for modern SDDs), and the energy calibration (zero offset and gain, typically 5 eV/channel) (pqac-00000009, pqac-00000026, pqac-00000027, pqac-00000035).\n\n**Standard material parameters:** the identity and known composition of the standard (whether certified by an independent method), its microscopic homogeneity (confirmed by EPMA), and its certification traceability (e.g., NIST SRM certificate) (pqac-00000003). When pure elements are incompatible with vacuum or suffer oxidation/beam damage, stoichiometric compounds are substituted\u2014e.g., MgO for Mg, KCl for K and Cl, FeS\u2082 for S, GaP for Ga and P, CaF\u2082 for Ca and F (pqac-00000005).\n\n**Sample condition parameters:** surface preparation state (highly polished, not chemically etched; surface roughness <50 nm rms for measurements of photons below 1 keV), coating material and thickness (typically ~8\u201310 nm carbon), and contamination/oxidation/tarnish state (pqac-00000002, pqac-00000004, pqac-00000007, pqac-00000022).\n\n**Administrative parameters:** date and time of acquisition, operator, and instrument identifier (pqac-00000000, pqac-00000013).\n\n**The EMSA/MAS .msa format (ISO 22029)** is the standardized spectrum data file format for microbeam analysis, originally defined by Fiori, Swyt, and others and adopted as ISO 22029 \"Microbeam Analysis \u2013 EMSA/MAS Standard File Format for Spectral-Data Exchange\" (pqac-00000036). Its required keywords include `#FORMAT`, `#VERSION`, `#TITLE`, `#DATE`, `#TIME`, `#OWNER`, `#NPOINTS`, `#NCOLUMNS`, `#XUNITS`, `#YUNITS`, `#DATATYPE`, `#XPERCHAN`, `#OFFSET`, `#SIGNALTYPE`, and `#SPECTRUM`. Optional but analytically critical keywords include `#BEAMKV`, `#PROBECUR`, `#LIVETIME`, `#REALTIME`, `#ELEVANGLE`, `#AZIMANGLE`, and `#XTILTSTGE`/`#YTILTSTGE`. Notably, the classic EMSA/MAS keyword set does not include dedicated fields for detector window type, dead layer thickness, incomplete charge collection parameters, or FWHM at Mn K\u03b1\u2014these must be recorded in comment fields or external documentation. Scott, Wight, and Thorne (2002, Microsc. Microanal. 8:646\u2013647) proposed extending the format to XML-based \"EMSA/MAS 2.0,\" but the original ASCII format remains dominant.\n\nThe following table summarizes the complete metadata requirements:\n\n| Metadata Parameter | Description/Purpose | EMSA/MAS Keyword (where applicable) |\n|---|---|---|\n| Beam energy / accelerating voltage | Required because k-ratios are valid only when unknown and standard are measured under the same excitation conditions; changes ionization cross-sections, overvoltage, depth of generation, and matrix corrections. (pqac-00000000, pqac-00000002, pqac-00000005, pqac-00000022) | `#BEAMKV` |\n| Probe current | Needed to document electron dose and to verify reproducibility/linearity of X-ray intensity; rigorous k-ratio work should measure current with a Faraday cup/picoammeter. (pqac-00000000, pqac-00000013, pqac-00000035, pqac-00000046) | `#PROBECUR` |\n| Live time | Dose in EDS is probe current \u00d7 live time; live time, not real time, determines effective dose because dead time removes useful counts. (pqac-00000000, pqac-00000013, pqac-00000025, pqac-00000035) | `#LIVETIME` |\n| Real time / dead time | Important to assess pulse pile-up/coincidence and detector operating regime; Newbury & Ritchie recommend conservative operation around ~10% dead time for standards-based work, especially when weak peaks sit near coincidence/tail artifacts. (pqac-00000006, pqac-00000013, pqac-00000035, pqac-00000046) | `#REALTIME`, `#DEADTIME` |\n| Detector elevation / take-off angle | Required geometric parameter for absorption correction; should match between unknown and standard and be verified physically if necessary. (pqac-00000000, pqac-00000002, pqac-00000013, pqac-00000026) | often `#ELEVANGLE` or vendor-specific |\n| Detector azimuth angle | Needed because detector orientation changes X-ray path length and effective efficiency; should be fixed and recorded for reusable standards. (pqac-00000000, pqac-00000013) | often vendor-specific / not always standardized |\n| Specimen tilt | Changes take-off geometry and absorption; Goldstein/Newbury specify tilt should be controlled, preferably zero for bulk standards unless intentionally used. (pqac-00000000, pqac-00000013, pqac-00000022) | often `#XTILTSTGE`, `#YTILTSTGE` or vendor-specific |\n| Detector-to-specimen distance / working distance | Sets solid angle and count rate; must be reproducible between standard and unknown. Off-axis position also changes apparent low-energy efficiency because of window-grid/trap shadowing. (pqac-00000000, pqac-00000002, pqac-00000027) | often `#WORKING`, `#DISTANCE` or vendor-specific |\n| Detector active area / solid angle | Needed to interpret count rate and portability of archived spectra; different detector geometries change throughput and sensitivity. (pqac-00000000, pqac-00000002, pqac-00000015) | usually not in classic MSA core keywords; vendor-specific |\n| Detector window type and thickness | Critical below ~2 keV because polymer/SiN vs Be windows transmit low-energy X-rays very differently; affects Mg K, Al K, O K, etc. (pqac-00000009, pqac-00000010, pqac-00000019, pqac-00000027) | usually vendor-specific / not a required classic MSA keyword |\n| Window support grid / electron trap details | Off-axis shadowing and low-energy attenuation can change intensity and background, especially for light elements. (pqac-00000027) | vendor-specific |\n| Detector dead layer / front contact / Si absorption characteristics | Needed when comparing detectors or simulating spectra because fluorescence in dead layer, escape peaks, and efficiency roll-off alter low-energy response. (pqac-00000009, pqac-00000011) | vendor-specific |\n| Detector response function / incomplete charge collection behavior | Essential for fitting trace peaks under tails; low-energy tailing and peak-shape differences are detector-specific and limit transferability of standard spectra. (pqac-00000009, pqac-00000012, pqac-00000037) | not represented in classic MSA keyword set |\n| Energy calibration zero offset | Required so standard and unknown spectra align channel-for-channel for integrated-peak k-ratios and peak fitting. (pqac-00000022, pqac-00000035) | `#OFFSET` |\n| Energy calibration gain / channel width | Required to define energy-per-channel; Goldstein recommends fixed channel width (e.g., 5 eV/channel) and consistent calibration. (pqac-00000022, pqac-00000035) | `#XPERCHAN`, sometimes paired with `#OFFSET` |\n| Number of channels / energy range | Needed to reconstruct spectrum and assure same fitting range; spectra should span low-energy region through the Duane\u2013Hunt limit. (pqac-00000022, pqac-00000035) | `#NPOINTS`, `#XUNITS` |\n| Energy resolution / FWHM at Mn K\u03b1 | Peak overlap sensitivity depends on detector resolution; should be documented because different FWHM values change deconvolution and low-energy tail contributions. (pqac-00000026, pqac-00000010, pqac-00000011) | often `#MNFWHM` or vendor-specific |\n| Process time / shaping time / time constant | Must be fixed; adaptive process time is specifically discouraged for standards-based quantification because it changes peak shape and resolution. (pqac-00000000, pqac-00000013, pqac-00000026) | often `#TIMECNST` or vendor-specific |\n| Count total / integrated counts | High-count spectra are needed for robust MLLS fitting and trace-level overlap correction; archive the total counts or dose associated with the standard. (pqac-00000006, pqac-00000007, pqac-00000017) | `#DATATYPE` with counts array; total counts often derived or vendor-specific |\n| Standard identity | The material used as the standard must be named explicitly so composition, homogeneity, and suitability can be checked. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | `#SAMPLE` |\n| Standard composition | Required because k-ratio denominator must correspond to a known concentration in the standard. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | no single core keyword; usually comment/header text |\n| Certification / traceability | For rigorous work, the standard composition should be certified or independently established and microscopically homogeneous. (pqac-00000002, pqac-00000003, pqac-00000042) | usually comment/header text |\n| Date/time of acquisition | Needed for traceability, detector stability checks, and QA of archived reusable standards. (pqac-00000000, pqac-00000013) | `#DATE`, `#TIME` |\n| Operator / instrument identifier | Supports QA and cross-checking of archived standards; important when spectra are reused. (pqac-00000013) | `#OWNER`, `#TITLE`, vendor-specific instrument fields |\n| Specimen surface preparation state | Surface roughness/topography directly affects low-energy X-rays; for photons below ~1 keV surfaces should be extremely flat, and standards/unknowns should be prepared similarly. (pqac-00000002, pqac-00000007, pqac-00000022) | usually comment/header text |\n| Coating material and thickness | Carbon or metal coatings absorb low-energy X-rays; mismatch between standard and unknown coatings can cause significant error at low kV. (pqac-00000004, pqac-00000007, pqac-00000034) | usually comment/header text |\n| Contamination / oxidation / tarnish state | Surface films create composite specimens and strongly bias low-energy analysis; should be documented, especially for reactive standards like Mg-bearing materials. (pqac-00000003, pqac-00000018, pqac-00000034) | usually comment/header text |\n| Vacuum / chamber conditions | Useful for assessing contamination growth and detector performance stability during acquisition. (pqac-00000018, pqac-00000034) | vendor-specific |\n| Peak-family / line selection used for quantification | EDS often quantifies whole line families rather than a single line; the selected family must be known to interpret k-ratios and matrix corrections. (pqac-00000005, pqac-00000016, pqac-00000024) | usually analysis metadata, not core MSA |\n| Background/fit model or peak-shape reference linkage | Particularly valuable for trace-overlap cases, because usability of a stored standard also depends on the associated peak-shape references and fitting strategy. (pqac-00000016, pqac-00000017, pqac-00000023) | not in classic MSA core; DTSA-II/project metadata |\n| QA status / same-conditions verification | Archived standards are reusable only if a QA protocol confirms the unknown was measured under the same beam energy, dose, and EDS parameters. (pqac-00000000, pqac-00000013) | not a classic MSA keyword; external QA record |\n\n\n*Table: This table summarizes the metadata that must accompany an EDS standard spectrum for rigorous standards-based k-ratio quantification. It combines the practical requirements emphasized by Goldstein/Newbury/Ritchie with the fields typically represented in the EMSA/MAS .msa format and notes where classic MSA keywords are incomplete for modern detector-response details.*\n\n## 2. Are Standard Spectra Transferable Between Instruments?\n\n**The short answer is: generally no, not without significant correction, especially for low-energy lines below ~2 keV.**\n\nThe fundamental problem is that the k-ratio protocol requires that unknown and standard spectra be acquired under identical conditions. The stability of modern SDD-EDS detectors permits reuse of previously measured, stored standard spectra on the *same* instrument, provided a quality-assurance protocol confirms that the unknown was measured under the same documented conditions (beam energy, dose, and EDS parameters) (pqac-00000000, pqac-00000013). SDDs show nearly constant resolution and calibration across a wide range of input count rates, which enables practical spectrum archiving on a given instrument (pqac-00000015).\n\nHowever, cross-instrument transfer faces several detector-specific barriers:\n\n**Resolution differences:** Different SDDs have different FWHM values (typically 122\u2013150 eV at Mn K\u03b1), which change peak shapes and the extent of tails under adjacent peaks\u2014directly relevant to the Al K\u03b1 tail under Mg K\u03b1 in your case (pqac-00000010, pqac-00000011, pqac-00000026).\n\n**Window transmission:** The choice of window material (polymer/SiN vs. Be vs. windowless) dramatically affects transmission below ~2 keV. Moxtek AP3 and AP5 windows have different thicknesses (380 \u00b5m vs. 265 \u00b5m ribs), rib widths, and acceptance angles, creating different low-energy efficiencies (pqac-00000027). Be windows absorb essentially all X-rays below ~1 keV, making spectra taken with Be-window detectors incomparable to those from polymer-window detectors for light-element lines (pqac-00000019).\n\n**Silicon dead layer and incomplete charge collection (ICC):** Scholze and Procop modeled the EDS spectral response accounting for statistical and electronic noise, ICC (which causes peak tailing on the low-energy side), escape effects, and fluorescence from the front contact/dead layer (pqac-00000009). These processes are detector-specific and alter both peak shapes and the continuum particularly at low energies. The ICC tailing is the precise artifact creating your Al K\u03b1 tail under Mg K\u03b1.\n\n**Published \"standards transfer\" methodologies:** Newbury and Ritchie describe a \"remote standards standardless\" approach in which a library of standard measurements made on another instrument supplies standard intensities, with calculated corrections applied for beam energy and spectrometer efficiency differences. However, they note that no dose calibration is attempted in this approach, so the raw analytical total has no validity and normalization is required\u2014thereby removing important diagnostic indicators of geometric or other deviations (pqac-00000012). Newbury and Ritchie (2019) also reference a \"golden detector\" calibration-transfer technique (from Alvisi et al., 2006), in which a detector calibrated at a synchrotron beamline is used with a carefully chosen reference material to transfer the calibration to other instruments\u2014an approach they note is inherently more accurate than purely first-principles standardless methods (pqac-00000014, pqac-00000021).\n\n**Quantitative accuracy penalty:** When comparing measured and DTSA-II simulated spectra for bulk K411 at 20 keV (a surrogate for cross-instrument transfer using a modeled detector response), Newbury and Ritchie found discrepancies ranging from +1.2% for Fe K\u03b1 to +19% for Mg K, with the low-energy region showing systematically larger deviations (pqac-00000008, pqac-00000012). This +19% discrepancy for Mg K specifically underscores the severity of the problem for your Mg K\u03b1 / Al K\u03b1 overlap situation.\n\n**Practical recommendation:** For your specific case (trace Mg K\u03b1 at 1.254 keV under the tail of the dominant Al K\u03b1 at 1.487 keV), standard spectra should be acquired on your own EDAX Octane Plus SDD on your Apreo SEM under the same conditions as your unknowns. Cross-instrument transfer of standards is not recommended for this challenging low-energy overlap problem.\n\n## 3. Simulated / Synthetic Standards\n\nNIST DTSA-II includes built-in spectrum simulation tools (based on NISTMonte, a Monte Carlo electron trajectory simulator) that can generate synthetic standard spectra from first-principles physics to yield absolute intensities (pqac-00000008). The simulation models electron scattering, X-ray generation, self-absorption, secondary fluorescence, and the detector response function.\n\n**Published accuracy assessments:**\n\nWhen Newbury and Ritchie (2015) used DTSA-II simulated standards to analyze NIST microanalysis glass K2496 at 10 keV, the resulting concentrations were very close to the as-synthesized values, with RDEV values of approximately \u22121.0% to +1.7% for the constituent elements and precision metrics of ~0.08\u20131.8% relative (pqac-00000006). This demonstrates that simulated standards can provide accurate quantification for moderate-to-high-energy X-ray lines in well-controlled measurements.\n\nHowever, for bulk K411 at 20 keV, a direct comparison of measured and simulated spectra (without scaling) showed discrepancies of +1.2% for Fe K\u03b1 up to +19% for Mg K (pqac-00000008). The systematically larger error at low photon energies (Mg K at 1.254 keV) reflects the difficulty of accurately modeling the detector response\u2014particularly ICC, dead layer absorption, and window transmission effects\u2014in the sub-2 keV energy range.\n\n**Where simulated standards are acceptable:** Simulated standards are most useful when a flat, bulk reference of the desired composition is unavailable\u2014for example, when analyzing irregularly shaped particles or microstructural features. DTSA-II can simulate a bulk reference spectrum from an estimated composition, with a first normalized analysis serving as that estimate (pqac-00000008, pqac-00000012). For higher-energy lines (>2 keV) and well-characterized detector parameters, simulated standards can approach the accuracy of measured standards.\n\n**Where simulated standards specifically fail:** The simulation's accuracy critically depends on the fidelity of the detector response model. Key failure modes include:\n- **Low-energy peak tailing and ICC:** The incomplete charge collection process, which creates low-energy tails on peaks, is detector-specific and difficult to parameterize accurately from first principles. Giunto et al. (2025) note that detector artifacts \"particularly below 2 keV\" complicate background fitting and quantification (pqac-00000037).\n- **Contamination layers and surface effects:** Real specimens accumulate carbon contamination and may have oxidation layers; these are not included in the simulation but strongly affect low-energy X-ray intensities (pqac-00000034).\n- **Absorption edge structure:** The continuum under characteristic peaks contains absorption edge structures that are broadened by the detector function; at higher beam energies, the peak fitting residuals show non-physical zero-intensity regions, indicating modeling limitations (pqac-00000034).\n\n**For your specific case:** A simulated Al standard would not accurately reproduce the ICC tail that extends from Al K\u03b1 into the Mg K\u03b1 region on your specific Octane Plus detector. This tail is the dominant suspected source of your Mg over-estimation, and it is highly detector-specific. A measured Al standard acquired on your own detector is essential to characterize this tail empirically.\n\n## 4. Where to Obtain Physical Standards for Al, Si, and Mg\n\nThe following table provides a comprehensive listing of standards suppliers and CRMs relevant to your Al-Si-Mg system:\n\n| Supplier/Source | Product/CRM | Catalogue/SRM Number | Elements/Composition | Notes |\n|---|---|---|---|---|\n| NIST | Glass for microanalysis, K411 | SRM 470 K411 | O-Mg-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; useful as a multi-element glass containing Mg and Si. (pqac-00000031, pqac-00000042) |\n| NIST | Glass for microanalysis, K412 | SRM 470 K412 | O-Mg-Al-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; directly relevant to Al-Mg-Si calibration and overlap studies. (pqac-00000031, pqac-00000042) |\n| NIST | Gold-silver alloy set | SRM 481 | Au-Ag alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study as a certified alloy series suitable for microanalysis challenge specimens and standards work. (pqac-00000031, pqac-00000042) |\n| NIST | Gold-copper alloy set | SRM 482 | Au-Cu alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study; Newbury & Ritchie also discuss spectra of SRM 482 at multiple beam energies. (pqac-00000031, pqac-00000034, pqac-00000042) |\n| NIST | Stainless steel CRM | SRM 479 | Fe-Cr-Ni stainless steel | Explicitly listed in the 5 kV study among NIST microanalysis challenge materials. (pqac-00000031, pqac-00000042) |\n| NIST | Transformer steel CRM | SRM 483 | Fe-3Si steel | Mentioned by Newbury & Ritchie 2019 as an EPMA/EDS reference material in quantitative work. (pqac-00000039) |\n| NIST | Thin-film microanalysis SRM | SRM 2063a | Thin film; composition not verified here | Relevant NIST microanalysis SRM class, but exact composition/details were not verified in the retrieved sources; include only after checking the current NIST certificate. |\n| NIST | K-glass / oxide glass series | SRM 1871, 1872, 1873, 1875 | SRM 1871 K456: O-Si-Pb; SRM 1872 K453: O-Ge-Pb; SRM 1873 K458: O-Si-Zn-Ba; SRM 1875 K496: O-Mg-Al-P | Explicitly listed in the 5 kV study as microanalysis-qualified SRMs. SRM 1875 is especially relevant because it contains Mg and Al. (pqac-00000031, pqac-00000042) |\n| Geller MicroAnalytical Laboratory (Topsfield, MA, USA) | Stoichiometric binary compounds prepared for microanalysis | Vendor product line; specific catalogue IDs not verified here | MgO, Al2O3, SiO2, TiN, TiO2, Cr2N, etc. | Explicitly named by Newbury & Ritchie 2024 as a source of stoichiometric compounds with surfaces prepared for microanalysis. Recommended route for MgO, Al2O3, SiO2 standards. (pqac-00000031, pqac-00000040) |\n| SPI Supplies (West Chester, PA, USA) | Mineral standards / well-characterized minerals | Vendor product line; specific catalogue IDs not verified here | Minerals such as calcite, dolomite, fluorapatite, wollastonite, zircon; user-requested examples periclase/forsterite/spinel should be checked in current catalog | Explicitly named by Newbury & Ritchie 2024 as a source of minerals of known composition and micro-homogeneity used in the challenge set. (pqac-00000031, pqac-00000042) |\n| Astimex Standards Ltd (Toronto, Canada) | Mounted pure-element and compound microanalysis standards | Vendor product line; specific catalogue IDs not verified here | Pure Al, Si, alloys, oxides, silicates, custom mounts | Common EPMA/SEM-EDS supplier, but specific products were not verified in the retrieved literature; check current catalog for Al, Si, Mg-bearing mounts before purchase. |\n| Ted Pella, Inc. | Microanalysis standards and mounts | Vendor product line; specific catalogue IDs not verified here | Pure elements, compounds, calibration mounts | Widely used supplier, but no product-specific verification in retrieved sources; confirm current catalog details. |\n| Micro-Analysis Consultants (MAC), St Ives, UK | Mineral and synthetic EPMA standards | Vendor product line; specific catalogue IDs not verified here | Silicates, oxides, sulfides, synthetic compounds | Common EPMA standards source, but exact catalog entries were not verified in retrieved sources. |\n| P&H Developments | Electron microprobe standards | Vendor product line; specific catalogue IDs not verified here | Mineral and synthetic standards | Named by user request; no product-specific verification found in retrieved sources, so verify directly with supplier. |\n| Alfa Aesar (now Thermo Fisher chemicals) | Reagent compounds | Reagent-grade products; specific catalogue IDs not verified here | BaTiO3, PbS, MoS2 and other compounds | Explicitly named by Newbury & Ritchie 2024 as source of reagent compounds used as challenge specimens; reagent grade is not automatically a microanalysis standard, so homogeneity/prep must be checked. (pqac-00000031, pqac-00000040) |\n| Smithsonian microbeam standards collection | Mineral reference materials | Collection-level resource; no single catalogue number | Mineral standards, including Mg-bearing silicates/carbonates depending on collection | Valuable institutional standards resource, but not documented in the retrieved contexts; verify access and material list directly with Smithsonian microbeam facility. |\n| Recommended Mg standard chemistry | MgO (periclase chemistry) | Not a single catalog number | Mg and O | Newbury & Ritchie\u2019s 5 kV study repeatedly used MgO as the Mg standard; their standards table maps Mg to MgO at 5 kV. This is the best-supported Mg standard in the retrieved sources. (pqac-00000040, pqac-00000041, pqac-00000043) |\n| Recommended Al standard chemistry | Al2O3 | Not a single catalog number | Al and O | In the 5 kV study, Al was standardized with Al2O3 in the standards table; practical if oxide standards are already in the block. (pqac-00000040, pqac-00000041) |\n| Recommended Si standard chemistry | SiO2 or pure Si | Not a single catalog number | Si and O, or Si | The 5 kV study shows SiO2 used as a Si standard in multiple entries; Newbury & Ritchie also note that pure Si can be used among pure-element standards. (pqac-00000040, pqac-00000041, pqac-00000043) |\n| Caution on pure Mg metal | Pure Mg metal | Not recommended as first-choice standard for routine low-kV SEM-EDS | Mg metal, rapidly oxidizing surface | Not directly evaluated in the retrieved papers, but the literature retrieved strongly supports substitution with MgO; this is consistent with the practical oxidation/contamination problem for Mg metal and the repeated use of stoichiometric compounds when pure elements are unstable. (pqac-00000003, pqac-00000005, pqac-00000043) |\n\n\n*Table: This table summarizes physical standards sources and certified reference materials relevant to Al, Si, and Mg SEM-EDS/EPMA work, emphasizing items explicitly documented in the Newbury & Ritchie 2024 5 kV study. It distinguishes directly verified standards from commonly used suppliers whose current catalogue details should still be checked before procurement.*\n\n**Standards used in the Newbury & Ritchie 2024 study at 5 keV:** At E\u2080 = 5 keV, their Table 1 explicitly documents the use of **MgO** as the standard for Mg, **Al\u2082O\u2083** for Al, and **SiO\u2082** (or pure Si) for Si (pqac-00000040, pqac-00000041, pqac-00000043). Their materials sources included NIST SRMs (SRM 470 K411/K412, SRM 479, SRM 481, SRM 482, SRM 1871\u20131875 series), minerals from SPI Supplies (West Chester, PA), stoichiometric compounds from Geller MicroAnalytical Laboratory (Topsfield, MA), and reagent compounds from Alfa Aesar (pqac-00000031, pqac-00000042).\n\n**On pure Mg metal as a standard:** Newbury and Ritchie consistently use MgO rather than pure Mg metal for their Mg standard (pqac-00000005, pqac-00000040, pqac-00000041, pqac-00000043). The general principle stated is that when pure elements are \"incompatible with vacuum or suffer electron-beam damage,\" stoichiometric compounds are substituted (pqac-00000003, pqac-00000005). Pure Mg metal oxidizes rapidly, forming a surface MgO layer that grows under the electron beam and in ambient air; this creates a composite specimen that violates the homogeneity assumption of the k-ratio protocol. The EPMA community conventionally uses MgO (periclase), MgAl\u2082O\u2084 (spinel), Mg\u2082SiO\u2084 (forsterite), or CaMg(CO\u2083)\u2082 (dolomite) as Mg standards, with MgO being the simplest and most widely used.\n\n**Specific additional suppliers (not directly verified in the retrieved literature but well-established in the EPMA community):**\n- **Astimex Standards Ltd** (Toronto, Canada): Supplies mounted pure-element and compound standard blocks commonly used in EPMA laboratories.\n- **Micro-Analysis Consultants (MAC)** (St. Ives, UK): Supplies mineral and synthetic microanalysis standards.\n- **Ted Pella, Inc.**: Distributes microanalysis standards and specimen preparation supplies.\n- **P&H Developments**: Supplies EPMA standard materials.\n- **Smithsonian microbeam standards collection**: Curated mineral standards used by the Smithsonian Institution's microbeam facility and distributed to the community.\n\n*Note: Specific catalogue identifiers for Astimex, MAC, Ted Pella, and P&H Developments were not verified in the retrieved literature and should be confirmed with the vendors' current catalogues.*\n\n## 5. Public Repositories of EDS/EPMA Spectra\n\n**NIST DTSA-II internal standards database:** The DTSA-II software distribution (freely available from NIST at https://www.nist.gov/services-resources/software/nist-dtsa-ii) includes a built-in standards/k-ratio database. This database contains reference data for standard spectra and compositions used in the k-ratio quantification engine. However, these are primarily used as the software's internal reference framework for matrix corrections rather than as a downloadable library of measured spectra transferable to other instruments (pqac-00000012, pqac-00000014).\n\n**EMSA/MAS format (ISO 22029):** The standard data exchange format for microbeam analysis spectra is the EMSA/MAS .msa ASCII format, now codified as ISO 22029 (pqac-00000036). This format is supported by DTSA-II and most vendor software for import/export of EDS spectra.\n\n**Key limitation on transferability of archived spectra:** Even when spectra are available in .msa format from repositories or community resources, they are generally usable only as **reference/identification spectra** (for qualitative comparison and peak identification) rather than as quantification standards on a different instrument. This is because the spectra encode the detector-specific response function (resolution, tailing, efficiency) of the instrument on which they were acquired (pqac-00000009, pqac-00000010, pqac-00000012). Newbury and Ritchie's \"remote standards\" approach can partially address this limitation by applying corrections for spectrometer efficiency differences, but the raw analytical total loses validity and normalization is required (pqac-00000012).\n\n**Other resources:**\n- **de-ma.ch web database** (Allaz, 2024, Microsc. Microanal. 30:489\u2013500): A web database for electron and X-ray microanalysis to assist lab managers and users. The detailed contents were not fully verified in the retrieved literature.\n- **NEXL** (Ritchie, 2022, Microsc. Microanal. 28:478\u2013495): Ritchie's reproducible spectrum and hyperspectrum data analysis framework using a defined data format.\n- **University of Oregon CAMCOR**: Maintains standard block documentation that can serve as a community reference but is not a downloadable spectral library.\n- **Zenodo/Figshare deposits**: Individual researchers occasionally deposit EDS datasets; these should be evaluated case-by-case for usability as quantification standards.\n\n**Practical conclusion:** No large, publicly downloadable library of measured EDS standard spectra exists that would be directly usable as quantification standards on an arbitrary instrument. The most reliable path remains acquiring your own standards on your own detector.\n\n## 6. The Specific Low-kV Case: 5 kV Mg K\u03b1 in an Al-Rich Matrix\n\n**The analytical challenge:** At 5 kV, Mg K\u03b1 (1.254 keV) and Al K\u03b1 (1.487 keV) are separated by only ~233 eV. With a typical SDD FWHM of ~55\u201365 eV at these energies, the peaks are nominally resolved, but the Al K\u03b1 peak\u2014which is enormously intense in an 84+ wt% Al matrix\u2014generates a low-energy tail due to incomplete charge collection that extends beneath the much smaller Mg K\u03b1 peak. Your measured Mg concentration (0.9\u20131.6 wt% vs. specification 0.20\u20130.45 wt%) represents a 2\u20134\u00d7 overestimate that is entirely consistent with inadequate characterization of this Al K\u03b1 low-energy tail artifact in a standardless quantification framework.\n\n**Accuracy demonstrated at 5 keV with the k-ratio protocol:** Newbury and Ritchie (2024) systematically tested accuracy at E\u2080 = 5 keV using NIST DTSA-II with the standards-based k-ratio protocol, making 263 concentration measurements for 39 elements in 113 materials. More than 98% of their results fell within \u00b15% RDEV, and 82% fell within \u00b12% RDEV (pqac-00000028, pqac-00000029). This demonstrates that high-accuracy quantification at 5 keV is achievable with proper standards and protocol. Their analytical platform was a JEOL 8500f with a Bruker Quad SDD array (pqac-00000030, pqac-00000031).\n\n**Standards selection for Al, Si, Mg at 5 keV:** In the 5 keV study, MgO was used as the Mg standard, Al\u2082O\u2083 as the Al standard, and SiO\u2082 as the Si standard (pqac-00000040, pqac-00000041). These compound standards avoid the surface oxidation problem of pure Mg metal and provide reliable, reproducible compositions.\n\n**Practical recommendations for your measurement:**\n\n1. **Acquire a measured Al standard spectrum on your own detector.** This is the single most important step to characterize the detector-specific Al K\u03b1 low-energy tail under Mg K\u03b1. The Al standard spectrum (pure Al metal or Al\u2082O\u2083) serves as both a quantification standard and a peak-shape reference for the MLLS fitting in DTSA-II (pqac-00000016, pqac-00000017, pqac-00000023). In DTSA-II, this is accomplished by setting up a \"Standard Bundle\" that combines the standard spectrum with peak-shape references (pqac-00000016).\n\n2. **Consider acquiring a \"blank\" spectrum from pure Al** (or an Al-Si binary alloy with no Mg) specifically to characterize and subtract the Al K\u03b1 tail contribution under the Mg K\u03b1 region. This provides an empirical characterization of the ICC tailing on your specific Octane Plus detector. The peak fitting residual spectrum after fitting Al should show whether any counts remain in the Mg K\u03b1 region (pqac-00000017, pqac-00000023).\n\n3. **Collect high-count spectra.** For trace-level Mg (0.2\u20130.45 wt% is in the minor/trace boundary), long acquisition times are needed to improve counting statistics and detection limits. Detection limits scale as C_DL = [3 \u00d7 N_B^(1/2) / (N_S \u2212 N_B)] \u00d7 C_S, and practical LODs can reach ~200\u2013500 ppm with sufficient counts (pqac-00000018). Total spectrum counts of 3\u201310 million (0.1\u20135 keV range) were typical in the Newbury & Ritchie 5 keV study (pqac-00000030, pqac-00000031).\n\n4. **Use conservative dead time (~10%).** At 5 kV in an Al-rich matrix, the Al K\u03b1 peak will be extremely intense. Coincidence peaks (Al+Al at ~2.97 keV, Al+Si, etc.) become significant above ~10\u201315% dead time and can distort the continuum shape in the fitting region. Choose beam current to keep dead time below 10% on the most highly excited standard (pqac-00000007, pqac-00000046).\n\n5. **Surface preparation is critical.** At 5 kV, the electron range is very short (~200\u2013300 nm in Al), so surface roughness, oxidation, and carbon contamination have a proportionally larger effect. Surface roughness should be <50 nm rms for measurements of photon energies below 1 keV, and the same preparation/coating protocol must be applied to both standards and unknowns (pqac-00000002, pqac-00000007, pqac-00000022). Carbon coatings should be ~8\u201310 nm and matched between standard and unknown; mismatched coating thickness introduces significant error at low beam energies (pqac-00000004).\n\n6. **Inspect the peak fitting residual spectrum.** After fitting Al and Si peaks, inspect the residual spectrum in the Mg K\u03b1 region to verify whether a genuine Mg peak remains above the fitted background, and whether the residual shows any systematic structure indicating inadequate tail modeling (pqac-00000017, pqac-00000023).\n\n7. **The raw analytical total is diagnostic.** When using the k-ratio protocol (not normalized), the raw analytical total should fall near 1.00 (typically 0.98\u20131.02 at conventional beam energies). At 5 keV, a broader range of 0.8\u20131.2 is observed even for carefully vetted materials (pqac-00000029, pqac-00000034). A total significantly deviating from unity signals potential problems (missing elements, surface layers, or fitting artifacts).\n\n8. **Verify with a known Mg-bearing reference material.** Analyze NIST SRM 470 K412 glass (which contains Mg, Al, Si, Ca, Fe, and O) at 5 keV to validate your Mg measurement against the certified composition before analyzing the AlSi10Mg alloy. This serves as an independent accuracy check for the specific Al-Mg overlap situation on your instrument.\n\n**Root cause of your Mg overestimate:** In standardless quantification, the vendor's built-in peak model may not accurately represent the ICC tail of Al K\u03b1 on your specific Octane Plus detector, leading to systematic misattribution of Al K\u03b1 tail counts to the Mg K\u03b1 channel. Switching to standards-based k-ratio quantification with DTSA-II, using a measured Al standard from your own detector as both standard and peak-shape reference, should dramatically reduce this systematic error by empirically capturing the actual detector response (pqac-00000012, pqac-00000014).\n",
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+                "context": "The excerpt explains the k-ratio quantification principle: k = Iunknown/Istandard, where the characteristic X-ray peak intensity must be measured under identical conditions (\"measured under identical conditions of beam energy, known dose, and detector efficiency for both\") so detector efficiency and other instrumental factors cancel. It also states that standards need not closely match unknown composition and gives acceptable standard types: pure elements and stoichiometric compounds for elements that are gaseous in vacuum, highly reactive, beam-sensitive, or low melting (examples: MgO for O; KCl for K and Cl; FeS2 for S; GaP for Ga and P). The conversion from k-ratios to concentrations uses matrix correction factors Ci/Cstd = k i Z A F c, with Z, A, F, and c defined as corrections for electron scattering/energy loss, X-ray self-absorption, and secondary X-ray emission/continuum. The excerpt does not provide a detailed checklist of metadata fields that must accompany an EDS standard spectrum nor the explicit Goldstein et al. requirements; it provides only these operational and standard-selection points relevant to k-ratio measurement.",
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+                  "k \u00bc Iunknown=Istandard:",
+                  "measured under identical conditions of beam energy, known dose, and detector ef\ufb01ciency for both",
+                  "standards required do not have to closely match the composition of the unknown, which is an enormous advantage when dealing with complicated multi-element unknowns.",
+                  "Suitable standards for the k-ratio measurements include pure elements (e.g., Al, Si, Cr, Fe, Ni, etc.), while stoichiometric compounds can be used for those elements that are not in solid form in a vacuum (e.g., MgO for O), that are highly reactive (e.g., KCl for K and Cl), that deteriorate under electron bombardment (e.g., FeS2 for S), or that have a low melting temperature (e.g., GaP for Ga and P).",
+                  "Ci=Cstd \u00bc ki ZAFc;",
+                  "Z, A, F, and c are the \u2018\u2018matrix correction factors\u2019\u2019 that calculate the compositionally dependent interelement effects of electron scattering and energy loss (Z), X-ray self-absorption within the specimen (A), and secondary X-ray emission following self-absorption of the electron-excited characteristic (F) and continuum (c) X-rays."
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+                "context": "The excerpt documents what metadata and accompanying information the authors stored with standard spectra for standards-based k-ratio quantification. Standards used are identified (pure elements or stoichiometric compounds) and non-conductive standards were carbon-coated (~10 nm). Standard spectra were recorded at known beam energies (examples: E0 = 20 keV or 15 keV for Cu L and K families) and kept alongside sample spectra in material-specific folders. A DTSA-II EDS detector configuration file was saved for each detector and includes detector-specific parameters such as window material and thickness. The k-ratio is computed as ki = Ix,sample / Ix,standard with spectrum corrections (peak interferences and background) and measurement conditions must be carefully defined (e.g., monitoring beam current to ensure constant dose). The workflow also records that k-ratios are converted to concentrations using matrix correction factors (Z, A, and F' factors). The excerpt does not, however, reproduce or cite the specific list of requirements from Goldstein et al.",
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+                  "Standards for analysis consisted of a suite of pure elements, e.g., B, C, Si, Ti, Cr, Fe, Ni, Cu, Zn, Mo, etc., and for those pure elements that are incompatible with the instrument vacuum requirements or which are unstable under electron beam bombardment, stoichiometric compounds, e.g., MgO, \u00adFeS2, KCl, etc., were utilized.",
+                  "Non-conductive standards were coated with a thin (approximately 10 nm) carbon layer applied by thermal evaporation.",
+                  "a DTSA-II EDS detector configuration file which incorporates the specific parametersth for that detector, such as the window material and thickness.",
+                  "For spectrum calibration with the DTSA-II calibration tool, a folder contains Cu spectra measured at \u00adE0 = 20 keV or \u00adE0 = 15 keV, providing both the Cu L- and K- families, that were recorded over the course of the measurement campaign.",
+                  "A folder for each material contains the spectra that were analyzed along with the standard spectra that were utilized.",
+                  "ki = Ix,sample\u2215Ix,standard",
+                  "the characteristic X-ray intensity, IX, for each element, i, (corrected for any peak interferences and for the X-ray continuum background) is ratioed to the intensity measured on a standard containing that element, Ci,stan, under carefully defined measurement conditions (e.g., monitoring of the beam current throughout each measurement sequence of challenge materials and appropriate standards to ensure a constant dose was achieved):",
+                  "the suite of k-ratios is then converted into a suite of mass concentrations by calculating a series of matrix correction factors for each element that account for differences between the unknown and standard in (1) the electron backscattering and energy loss (the \u201c\u200aZ\u200a\u201d factor); (2) X-ray self-absorption (the \u201c\u200aA\u200a\u201d factor); and (3) the secondary characteristic X-ray production induced by self-absorption of the primary characteristic X-rays (the \u201c\u200aF\u200a\u2019 factor)."
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+                "context": "The excerpt lists the metadata and requirements that must accompany EDS standard spectra for rigorous k-ratio quantification. Standard spectra must be measured and archived with known, reproducible beam energy and electron dose (beam current \u00d7 detector live time), and with documented EDS operating conditions (time constant/resolution, detector-to-specimen distance and detector active area/solid angle, detector take-off and azimuthal angles, and specimen tilt\u2014preferably zero). A calibrated beam-current measurement (Faraday cup + digital picoammeter) is required for a fully rigorous protocol, and a conservative beam current that yields roughly 10% detector deadtime is recommended to minimize pulse coincidence. Sample and standard surface condition must be controlled: highly polished, not chemically etched, and for low-energy lines surface roughness should be <50 nm rms. Standards may be co-mounted or prepared on separate mounts; they must have accurately known composition and be homogeneous at the micrometer scale. Finally, archived standard spectra can be reused only if a quality-assurance check confirms the unknown was measured under the same documented conditions (beam energy, dose, and EDS parameters), and high-count, stable peak-shape spectra are needed for robust peak fitting (MLLS) in severe overlap situations.",
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+                  "Spectra from the unknowns and standards must be measured under known and reproducible conditions of beam energy, dose (electron current 9 detector live time), and EDS operating conditions (fixed time constant, which defines a fixed resolution; fixed detector-to-specimen distance which with the detector active area defines the detector solid angle; known detector take-off angle and azimuthal angle relative to the specimen tilt axis; and known specimen tilt, which is preferably zero tilt, i.e., the beam is perpendicular to the specimen surface).",
+                  "A beam current measuring system consisting of a Faraday cup and a digital picoammeter is a necessary component if a fully rigorous k-ratio protocol is to be established [2].",
+                  "it is highly recommended that a conservative operating strategy be used for SDD-EDS measurements, with the beam current chosen to provide a detector deadtime of approximately 10 %",
+                  "(1)   Sample  surface condition: The sample must be highly polished to remove topography that creates the geometric effects discussed in Figs. 3, 4, and 5.",
+                  "The resulting highly polished surfaces must not be chemically or electrochemically etched, which can alter the composition of the near-surface region that is actually interrogated in the electron-excited X-ray measurement.",
+                  "For  the  low-energy  characteristic  X-rays below 1 keV needed to measure the elements Be through F, recent Monte Carlo modeling studies indicate that surface scratches must be reduced below a roughness of 50 nm (rms) for a system such as FeO to eliminate differential geometric effects between low-energy",
+                  "(5)   Standards can be co-mounted during metallographic preparation of the unknowns, but a more typical strategy is to prepare a separate standard mount containing a suite of pure elements and stoichiometric compounds.",
+                  "Multi-element mixtures such as alloys glasses, or minerals can also serve as standards, but in addition to accurately knowing the composition, such materials must be confirmed to be homogeneous on a micrometer lateral scale before they can serve as suitable standards.",
+                  "The stability of the SDD-EDS enables the careful analyst to operate with previously measured and stored standard spectra, providing that a quality assurance protocol is in place to confirm that the current measurement conditions for the unknown are consistent with the conditions under which the archived standards were measured: beam energy, dose, and EDS parameters."
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+                "context": "The excerpt lists the experimental requirements and metadata that should accompany an EDS standard spectrum used for k-ratio (standards-based) quantification. Key metadata/requirements include: identity and composition of the standard (single pure-element standard for each element; chemically similar standards where possible), flat polished sample/standard surface and homogeneity through the interaction volume, SEM accelerating voltage (electron energy \u2265 1.8 \u00d7 the X\u2011ray peak energy for elements of interest), sample orientation (surface normal to beam and ~35\u00b0 to the EDX detector), energy-scale calibration details (e.g., per ISO 22309:2011 using Al and Cu standards), beam current and detector-geometry calibration (e.g., \u2018Quant Optimisation\u2019 in Aztec), and a stable electron beam current. Also important are factory-supplied matrix correction data from comparable elemental standards and acquiring standards under the same experimental session to cancel dependence on beam current, geometry and chamber contamination. The excerpt does not contain the text of Goldstein et al. or their explicit checklist, so requirements specifically attributed to Goldstein et al. are not present here.",
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+                  "One standard is required for every element to be quantified, which should be chemically similar to the sample.",
+                  "Flat, polished sample surface.",
+                  "Homogeneous through interaction volume",
+                  "Single pure element standard (e.g.   Co) for beam current and detector geometry calibration",
+                  "Elemental standards with similar chemical properties to sample",
+                  "SEM accelerating voltage \u2013 electron energy is at least 1.8 \u00d7 X-ray peak energy for all elements",
+                  "Sample surface positioned normal to the electron beam and 35\u00b0 to the EDX detector",
+                  "Energy-scale calibration according to ISO 22309:2011 and manufacturer instructions, e.g. using a Al and Cu standard",
+                  "Beam current and detector geometry calibration (\u2018Quant Optimisation\u2019) in Aztec software",
+                  "Stable electron beam current",
+                  "Factory-supplied matrix correction factor data from elemental standards with similar chemical properties to sample.",
+                  "This cancels out the dependence of k-ratios on beam current, SEM-EDX geometry, and SEM chamber contamination which affects EDX detector efficiency"
+                ],
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+                "context": "The provided excerpt does not give an explicit checklist of metadata that must accompany an EDS standard spectrum for k\u2011ratio quantification, but it does cite key requirements for standards (Goldstein et al., 1975) used in a standards\u2011based k\u2011ratio protocol with matrix corrections. Those requirements include: (1) the standard's overall (bulk) composition must be measured by independent methods; (2) microscopic homogeneity must be established (by EPMA in the cited work); and (3) when pure elements are incompatible with vacuum or suffer electron\u2011beam damage, stoichiometric compounds (e.g., CaF2, GaP, FeS2 for S) are used instead. The text defines the \u201ctrue value\u201d as the concentration known from independent analysis and uses the relative deviation (RDEV) from expected values as the figure of merit for EPMA results. While instrument/measurement metadata (beam energy, detector type, acquisition conditions) are discussed elsewhere in the paper (e.g., analytical beam energy choices), the excerpt itself does not enumerate a formal metadata package that must accompany an EDS standard spectrum for k\u2011ratio quantification.",
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+                    "formatted_citation": "Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal."
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+                  "standards-based  k-ratio protocol with matrix corrections",
+                  "overall (bulk) composition was measured   by independent methods",
+                  "microscopic homogeneity   was  established  by  electron  probe  microanalysis   (Goldstein et  al., 1975).",
+                  "standards suite consisting of pure elements and stoichiometric    compounds for those elements incompatible with a vacuum or   which suffered electron beam damage (e.g., CaF2, GaP, and FeS2   for S, which in pure element form deteriorates under electron    beam bombardment).",
+                  "The \u201ctrue value\u201d is the concentration of the element known     from the independent analysis"
+                ],
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+                "context": "The excerpt specifies the experimental metadata that must accompany EDS standards used for k\u2011ratio/matrix quantification: the specimen surface condition (highly polished; avoid chemical etching because it produces topography that alters X\u2011ray intensities), the beam energy, the known dose (beam current and detector live time), the beam incidence angle, the detector elevation or \"take\u2011off\" angle, and detector efficiency (e.g., constant detector\u2011to\u2011target distance to keep solid angle constant). It also emphasizes that standards should be archived and recalled as needed (stability of EDS), and that certified reference materials (e.g., NIST SRMs) and materials confirmed to be homogeneous on the micrometer scale are appropriate standards. The excerpt does not present a separate, explicit list attributed to Goldstein et al.; the listed metadata and standard requirements above are those provided in this text.",
+                "question": "What metadata must accompany an EDS standard spectrum for k-ratio quantification? What are the requirements listed in Goldstein et al. for standards in SEM-EDS quantification?",
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+                  "The condition of the specimen surface was recognized to be another critical requirement [4].",
+                  "To create contrast in optical metallography, chemical etching typically produces topography through orientation-depen- dent etch rates in different grains and phases, but even fine-scale topography can influence measured X-ray intensities, especially for low-energy photons.",
+                  "measuring the intensities for the unknown and appropriate standards under the same carefully controlled conditions of surface condition (highly polished), beam energy, known dose (beam current 9 detector live time), beam incidence angle, detector elevation angle (\u2018\u2018take-off angle\u2019\u2019), and detector efficiency (e.g., constant detector-to-target distance to yield constant detector solid angle).",
+                  "The enormous advantages of the EDS over WDS for analysis were quickly recognized: (1) all elements in the unknown were measured simultaneously minimizing the dose to the specimen; (2) the large solid angle of the EDS relative to WDS further improved efficiency of detection which lowered the necessary dose relative to WDS; and (3) the stability of the EDS meant that the spectra of standards could be archived and recalled as needed.",
+                  "Materials analyzed in this paper include NIST Standard Reference Materials, NIST microanalysis research materials (glasses), natural minerals, and stoichiometric compounds con\ufb01rmed to be homogeneous on a micrometer lateral scale."
+                ],
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+                "context": "The excerpt documents examples of k-ratio protocol use and gives several experimental/metadata items shown alongside EDS standard spectra. Example spectra and k-ratio analysis were collected at a specified beam energy (E0 = 20 keV) using SDD-EDS (a four-detector array) with measured deadtime varying from 2% to 77%. The text emphasizes detector-related metadata (detector type: SDD-EDS; operating temperature ~-20 \u00b0C) and demonstrates that peak shapes and calibration remain stable over large input count rate ranges, which is important for reliable k-ratio fitting. For non-conductive standards and unknowns, the excerpt states a specimen must be coated and grounded, recommending a carbon coating 8\u201310 nm thick, and warns that differences in coating thickness between unknown and standards can introduce significant error (especially at low beam energies). The excerpt refers to Table 5 for k-ratio protocol analysis but does not reproduce a complete checklist of metadata or the requirements from Goldstein et al.; those Goldstein-specific requirements are not present on these pages.",
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+                  "Table 5 presents the k-ratio protocol analysis of the same spectra of metal sul\ufb01des as those reported by standardless analysis in Table 3.",
+                  "beam energy of E0 = 20 keV",
+                  "SDD-EDS (four-detector array) spectra of manganese",
+                  "deadtime from 2 to 77 %",
+                  "SDD-EDS operates at approximately -20  C",
+                  "Despite operating at a substantially higher temperature, SDD-EDS achieves equal or better resolution performance.",
+                  "Non-conducting specimens must be coated with a  conducting material which in turn must be connected to a suitable ground to discharge the electron current injected by the beam into the specimen.",
+                  "a layer of carbon 8\u201310 nm thick applied by thermal evaporation will suf\ufb01ce for discharging the surface of insulators.",
+                  "differences in the coating thickness between the unknown and the standards can contribute a signi\ufb01cant error."
+                ],
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+                "context": "The excerpt states that NIST DTSA-II can be used to simulate a bulk reference EDS spectrum from an estimated composition using first-principles physics to yield absolute intensities. An example (bulk K411, E0 = 20 keV) compared measured and simulated spectra with no scaling; the summed characteristic peak plus background intensities differed by +1.2% (Fe K\u03b1) up to +19% (Mg K) in that case. The authors note that a simulated reference is useful when a flat, bulk reference of the same composition is unavailable, but requires an estimate of the composition (a first normalized analysis can serve as that estimate). The excerpt warns that anomalous absorption\u2014especially in the low-photon-energy region\u2014can cause large deviations from the ideal spectrum (notably for microscopic shards and irregular geometries), and that application of standard k-value/matrix corrections followed by normalization to such spectra can produce unacceptably large errors. The passage does not provide details on how DTSA-II implements detector-response effects such as incomplete charge collection, detector dead layer, or window transmission.",
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+                  "simulate the bulk reference spectrum from an estimate of the composition of the unknown using a software tool such as NIST DTSA-II which calculates the spectrum on a first principles basis to yield absolute intensities.[9]",
+                  "Figure 15 shows an example of measured and simulated spectra for bulk K411 at E0 = 20 keV. No scaling has been applied to the simulation, and the estimate of the sum of the characteristic peak and background intensities ranges from +1.2% relative at FeK\u03b1 to +19% relative at MgK.",
+                  "The obvious problem in using this tool for the analysis of unknowns is the lack of a reference spectrum from a flat, bulk target of the appropriate composition, since this composition is the objective of the analysis.",
+                  "The impact of anomalous absorption, particularly in the low energy region of the x-ray spectrum, can be observed directly in the EDS spectrum",
+                  "The large deviation from the ideal spectrum is readily apparent for these shards and should serve as a warning that applying conventional k-value/matrix corrections to such a spectrum followed by normalization is likely to lead to unacceptably large errors."
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+                "context": "The excerpt shows DTSA-II simulated-standard analysis of NIST microanalysis glass K2496 (Table 11) producing concentrations very close to the as-synthesized values (example: 0.3230 vs 0.3197, 0.2291 vs 0.2256, 0.0180 vs 0.0176, 0.4299 vs 0.4371) with small relative errors (e.g., -1.0, -1.5, -2.4, 1.7 %) and small precision metrics (r relative (%) ~0.08\u20131.8 %). The authors emphasize an SDD-EDS measurement strategy (10 keV beam, deadtime \u224810 %, dose \u224810^7 counts) that yields high-count spectra and low detection limits; they recommend conservative counting to keep deadtime \u227210 % to avoid coincidence artifacts. The excerpt illustrates spectral interference issues (BaL\u03b1 vs TiK\u03b1 \u0394=41 eV; BaL\u03b23 vs TiK\u03b2 \u0394=4 eV) and shows that residual fitting can reveal low-level peaks masked by overlaps. Thus DTSA-II simulated spectra can give accurate quantification in well-controlled, high-count SDD-EDS measurements and can represent minor constituents within a few percent. The excerpt does not describe in detail how DTSA-II models detector effects such as incomplete charge collection, dead layer, or window transmission, nor does it fully enumerate failure modes beyond noted peak overlaps and deadtime/coincidence artifacts.",
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+                  "Table 11 DTSA-II analysis of NIST microanalysis glass K2496:    quantification of a minor constituent with interference from a major    constituent",
+                  "Concentration   0.3230     0.2291      0.0180       0.4299",
+                  "Concentration   0.3197     0.2256      0.0176       0.4371",
+                  "Relative error   -1.0    -1.5       -2.4           1.7",
+                  "r relative (%)   0.08        0.13         1.8          0.13",
+                  "SDD-EDS provides improved measurement sensitivity for photon energies below 1 keV compared to Si(Li)-EDS,",
+                  "The analytical strategy that was employed included selection of a beam energy of 10 keV to provide access to the K-shell X-rays of the transition elements and the L-shell X-rays of higher atomic elements; a beam current to restrict the deadtime to approximately 10 % to minimize coincidence peaks; and a dose to provide spectra with approximately 10^7 integrated counts.",
+                  "a conservative count rate that yields a deadtime of approximately 10 % or less is recommended to minimize coincidence artifacts",
+                  "BaL\u03b1 and TiK\u03b1: \u0394 = 41 eV",
+                  "BaL\u03b23 and TiK\u03b2: \u0394 = 4 eV",
+                  "fitting only for Si and Ba (red), revealing the low-level TiKa and TiKb peaks in the residual spectrum (blue)",
+                  "SDD-EDS can provide high-count spectra, e.g., integrated spectrum counts[50 million, in practical counting times, e.g., 500 s,"
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-70d0644e",
+                "context": "The excerpt notes that DTSA-II was used alongside the k-ratio protocol to show relative errors and raw analytical totals at multiple locations on a pyrite fragment, and that while accurate results can be obtained in some locations, most locations showed severe deviations from correct stoichiometry. The authors emphasize that the k-ratio protocol and matrix corrections provide an important warning flag in the raw analytical total, whereas standardless analysis (which would include simulated standards) can hide that clue. Achieving EPMA/WDS-level accuracy with SEM/SDD-EDS requires careful measurement practice and specimen/standard preparation (polished to <50 nm rms relief). Reported routine accuracies for SEM/SDD-EDS in this work are \u00b15% relative for major constituents (mass fraction >0.1), \u00b110% for minor constituents (0.01\u20130.1), and \u00b125% for trace constituents (0.001\u20130.01); limits of detection as low as 0.0005 mass fraction are attainable. The excerpt implies simulated or standardless approaches (e.g., DTSA-II used in a standardless mode) can fail or give misleading results when specimen topography, geometry, or other deviations from the ideal flat polished case introduce large geometric or collection effects that hide as apparently normalized compositions.",
+                "question": "What is the accuracy of NIST DTSA-II simulated standard spectra vs measured standards for EDS quantification? How does DTSA-II model detector response including incomplete charge collection, dead layer, window transmission? When do simulated standards fail?",
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+                      "Dale E. Newbury",
+                      "Nicholas W. M. Ritchie"
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+                    "title": "Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)",
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+                  },
+                  "chunk_id": "98357799-b721-48af-94c1-f0c9851ebc41"
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+                  "the relative errors (after normalization to 100 %) and the raw analytical total obtained with the k-ratio protocol and DTSA-II are shown at various locations.",
+                  "While accurate analytical results can be obtained at certain locations in the image, at most locations in the images, the deviations from the correct stoichiometry are severe.",
+                  "While the k-ratio protocol and matrix correction provide an important warning \ufb02ag in the raw analytical total, the standardless analysis procedure would hide this vital clue.",
+                  "However, to achieve SEM/SDD-EDS results at the level of EPMA/WDS, the analyst must be prepared to perform the careful measurement science of the k-ratio protocol, including careful attention to the surface preparation of unknowns and standards, which must be polished to eliminate relief above 50 nm rms.",
+                  "Accuracy within \u00b15 % relative can be routinely achieved for major constituents (mass concentration C [ 0.1), even the low atomic number elements, \u00b110 % relative for minor constituents (0.01 B C B 0.1), and \u00b125 % relative for trace constituents from 0.001 to 0.01 mass fraction.",
+                  "Limits of detection as low as 0.0005 mass fraction can be achieved for most elements, even when severe peak interference occurs."
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000007",
+                "context": "The excerpt shows that NIST DTSA-II, when used to process high-count, stable spectra and applied within a rigorous k-ratio protocol, can produce k-ratio determinations comparable to WDS and yield results within the EPMA/WDS error envelope (see Table 5 for sulfides at E0 = 20 keV). Achieving this performance requires strict measurement reproducibility: known beam energy, dose (electron current \u00d7 detector live time), fixed EDS parameters, and careful beam-current measurement (Faraday cup + picoammeter). A conservative operating strategy\u2014selecting beam current to give ~10% detector deadtime\u2014minimizes pulse coincidence, which becomes problematic above ~15% deadtime. High-count spectra with stable peak shape enable MLLS fitting to extract characteristic intensities even in severe peak overlap. The excerpt also notes practical failure modes for simulated/archived standards: standards must be homogeneous at the micrometer scale; sample surfaces must be highly polished (low topography, scratches < ~50 nm rms for low-energy X-rays); and at low beam energies (E0 \u2264 ~5 keV) differences in coating thickness between unknown and standards can introduce significant errors. The excerpt does not describe how DTSA-II models detector physics such as incomplete charge collection, detector dead layers, or window transmission.",
+                "question": "What is the accuracy of NIST DTSA-II simulated standard spectra vs measured standards for EDS quantification? How does DTSA-II model detector response including incomplete charge collection, dead layer, window transmission? When do simulated standards fail?",
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+                    "authors": [
+                      "Dale E. Newbury",
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+                    "title": "Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)",
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+                  },
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+                  "The results in Table 5 are accurate and fall well within the envelope of relative errors established by EPMA/WDS.",
+                  "Using the NIST DTSA-II EDS software engine to process spectra, it has been demonstrated that SDD-EDS can match WDS for determination of the k-ratio in severe overlap cases",
+                  "combination of high-count spectra with stable peak shape and position provides statistically robust peak references needed for MLLS fitting of spectral peaks to accurately extract the characteristic X-ray intensities",
+                  "Spectra from the unknowns and standards must be measured under known and reproducible conditions of beam energy, dose (electron current 9 detector live time), and EDS operating conditions",
+                  "A beam current measuring system consisting of a Faraday cup and a digital picoammeter is a necessary component if a fully rigorous k-ratio protocol is to be established",
+                  "it is highly recommended that a conservative operating strategy be used for SDD-EDS measurements, with the beam current chosen to provide a detector deadtime of approximately 10 % to minimize pulse coincidence (sum peaks)",
+                  "coincidence becomes progressively more significant above 15 % deadtime",
+                  "for low beam energy analysis, E0 B 5 keV, differences in the coating thickness between the unknown and the standards can contribute a significant error",
+                  "final polishing with the finest media then available was necessary to reduce the uncertainty contributed by the remaining specimen topography",
+                  "such materials must be confirmed to be homogeneous on a micrometer lateral scale before they can serve as suitable standards"
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000012",
+                "context": "The excerpt describes using a \"remote-standards standardless\" approach in which a library of standard measurements made on another instrument supplies standard intensities; calculated corrections are applied for beam energy and spectrometer efficiency differences between instruments. However, no dose calibration is attempted, so the raw analytical total from such transferred standards has no validity and normalization is required\u2014thereby removing indicators of geometric or other deviations. The authors emphasize that the low-photon-energy region is particularly sensitive to anomalous absorption and spectrum-shape deviations; a measured-vs-simulated example for bulk K411 at 20 keV showed discrepancies ranging from +1.2% (FeK\u03b1) to +19% (MgK), illustrating larger uncertainties at low energies. Because a flat-bulk reference of the exact composition is often unavailable, the authors recommend simulating a bulk reference spectrum (e.g., with NIST DTSA-II) and using x-ray spectrum imaging (XSI) to locate favorable regions on rough specimens for analysis. The excerpt discusses spectrometer efficiency corrections but does not explicitly detail the separate effects of detector resolution, window, dead layer, or incomplete charge collection on k-ratios below 2 keV.",
+                "question": "Can EDS standard spectra be transferred between different instruments/detectors? What are the effects of detector-to-detector variation in resolution, window, dead layer, incomplete charge collection on k-ratios for light elements below 2 keV?",
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+                  },
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+                  "The \"remote-standards standardless\" analysis procedure derives a suite of standard intensities as needed from a library of standard measurements made on another instrument.",
+                  "Calculated corrections based upon the measurement physics are made for differences in beam energy and spectrometer efficiency between the local instrument and the remote library instrument, but there is no dose calibration attempted so the raw analytical total has no validity.",
+                  "Normalization must be applied to place the calculated concentrations on a sensible basis, thus losing any indication of the influence of other factors possibly affecting the analytical total.",
+                  "The impact of anomalous absorption, particularly in the low energy region of the x-ray spectrum, can be observed directly in the EDS spectrum",
+                  "Figure 15 shows an example of measured and simulated spectra for bulk K411 at E0 = 20 keV. No scaling has been applied to the simulation, and the estimate of the sum of the characteristic peak and background intensities ranges from +1.2% relative at FeK\u03b1 to +19% relative at MgK.",
+                  "The obvious problem in using this tool for the analysis of unknowns is the lack of a reference spectrum from a flat, bulk target of the appropriate composition, since this composition is the objective of the analysis.",
+                  "A possible solution is to simulate the bulk reference spectrum from an estimate of the composition of the unknown using a software tool such as NIST DTSA-II which calculates the spectrum on a first principles basis to yield absolute intensities.[9]",
+                  "The high throughput of SDD-EDS makes it advantageous to collect x-ray microanalysis data of geometrically complex targets in the x-ray spectrum imaging (XSI) mode, in which at each pixel of an x-y scan a complete SDD-EDS spectrum is recorded.[8]"
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000010",
+                "context": "Relevant points from the excerpt for assessing transferability of EDS standard spectra and detector-to-detector effects on k-ratios (especially <2 keV): 1) EDS quantitation depends on integrating intensity over the same channel ranges on unknowns and standards: \"In the case of EDS, the intensity should be integrated over the same range of channels on the unknown and the standard.\" This implies standards and unknowns must be measured under consistent channel/binning and spectral-resolution conditions. 2) Detector physical differences matter: improvements and changes in \"dead layers trimmed,\" \"leakage currents\" and window materials affect low-energy X-ray transmission (\"These new window technologies permitted lower energy X-rays to reach the detector.\" and \"Some even, Li-K X-rays\"). 3) Resolution and peak shape affect peak integration and peak-to-background: \"Detector resolutions have improved.\"; \"The peak-to-background ratio on an EDS is determined by the ranges of channels used to estimate the continuum and peak intensity.\"; and the central FWHM holds \u224876% of peak intensity. 4) Limits of detection and k-ratios are constrained by the continuum vs signal: \"Ultimately, limits of detection are constrained by the magnitude of the background (continuum) level relative to the signal (characteristic) level.\" 5) By implication, differences in resolution, window transmission, dead layer and electronic performance between detectors will change observed peak shapes, background and low-energy sensitivity and thus will affect k-ratios for light elements below ~2 keV unless corrected or measured under matched conditions.",
+                "question": "Can EDS standard spectra be transferred between different instruments/detectors? What are the effects of detector-to-detector variation in resolution, window, dead layer, incomplete charge collection on k-ratios for light elements below 2 keV?",
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+                    "formatted_citation": "N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations."
+                  },
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+                "score": 7,
+                "snippets": [
+                  "In the case of EDS, the intensity should be integrated over the same range of channels on the unknown and the standard.",
+                  "Detector resolutions have improved.",
+                  "As leakage currents were reduced, dead layers trimmed, and analogue electronics and digitizers were improved, resolutions fell from hundreds of eV to approximately 135 eV at Mn-K\u03b1",
+                  "These new window technologies permitted lower energy X-rays to reach the detector.",
+                  "Some even, Li-K X-rays",
+                  "The peak-to-background ratio on an EDS is determined by the ranges of channels used to estimate the continuum and peak intensity.",
+                  "The central FWHM corresponds to approximately 76 % of the total peak intensity.",
+                  "Ultimately, limits of detection are constrained by the magnitude of the background (continuum) level relative to the signal (characteristic) level.",
+                  "The peak-to-background ratio on a WDS is determined by the convolution of the natural width of the characteristic X-ray line and the dispersive power of the spectrometer."
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000009",
+                "context": "The excerpt emphasizes that detailed, instrument-specific detector characterization is critical for FP-based XRF/EDS quantification. Key detector properties that must be known include absolute efficiency, energy resolution, and the precise shape of the detector response function. Scholze and Procop modelled EDS spectral response accounting for detector statistical and electronic noise, incomplete charge collection (which causes peak tailing), escape effects, and fluorescence from the front contact or dead layer\u2014all processes that alter peak shapes and continuum, particularly at low energies. An FP method that explicitly includes the energy-broadening response was used to predict peak-area ratios (KR fluorescence vs. scattered peaks), and the detector response curve was adjusted by matching theory to experiment. New SDDs with thin windows and improved electronics change throughput and low-energy sensitivity, and geometry/solid-angle differences further affect detected intensities. Taken together, these points indicate that uncorrected transfer of EDS standard spectra between different instruments/detectors is problematic unless detector-to-detector differences (resolution, window/dead layer absorption, incomplete charge collection, escape, response shape, and geometry) are modeled or empirically calibrated.",
+                "question": "Can EDS standard spectra be transferred between different instruments/detectors? What are the effects of detector-to-detector variation in resolution, window, dead layer, incomplete charge collection on k-ratios for light elements below 2 keV?",
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+                    "authors": [
+                      "Kouichi Tsuji",
+                      "Kazuhiko Nakano",
+                      "Yoshio Takahashi",
+                      "Kouichi Hayashi",
+                      "Chul-Un Ro"
+                    ],
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+                    "journal": "Analytical chemistry",
+                    "publisher": "American Chemical Society (ACS)",
+                    "url": "https://doi.org/10.1021/ac101069d",
+                    "title": "X-ray Spectrometry.",
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+                  },
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+                "snippets": [
+                  "For FP-based quanti\ufb01cation, detailed knowledge of the characteristics of the detector, including ef\ufb01ciency, energy resolution, and the precise shape of the response function, is essential.",
+                  "Scholze and Procop (68) presented an analytical description of the physical processes determining the spectral response of an EDS with a silicon detector (Si(Li) or SDD).",
+                  "The model considered the detector statistical noise, the electronic noise, the incomplete charge collection that gives rise to the peak tailing, the escape effect, the \ufb02uorescence of the front contact or the dead layer,",
+                  "An FP approach that explicitly incorporates the energy-broadening response of the detector has been reported (71).",
+                  "The ratio between the KR \ufb02uorescence peak area and the sum of coherently and incoherently scattered peak areas was used as an indicator of trace element concentration.",
+                  "The energy-broadening response curve of the Si(Li) detector was estimated by matching the theoretical and experimental values of this ratio.",
+                  "new-generation EDS with SDD, equipped with thin windows and integrated digital processing electronics, are claimed to approach the WDS throughput."
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000016",
+                "context": "The excerpt explains that in EDS the signals from multiple X-ray lines are integrated into a single measured peak and that each contributing line has slightly different matrix correction factors. For EDS this leads to a weighted matrix correction [ZAF]EDS computed from the individual transition weights (Wi) and their single-transition [ZAF]i values. Using complex or matrix-matched standards can reduce sensitivity to poorly known parameters because the ratio [ZAF]unk/[ZAF]std approaches unity. To handle peak interferences, DTSA-II uses additional spectra called peak-shape references \u201cwhich can be calibrated relative to the standard and fit to the unknown,\u201d and a \u201cStandard Bundle that sums standards and integrates the necessary peak-shape references.\u201d The text also notes that REE have complex L-line structures (tens of lines over a range of energies), which complicates WDS background placement but provides structure beneficial for EDS. Multiple acquisitions and summed standards are recommended to improve quality and reveal metrology issues. The authors\u2019 measurements used a multi-detector SDD setup (four independent 30 mm2 PulseTor SDDs), indicating multi-detector configurations are in practice.",
+                "question": "Can EDS standard spectra be transferred between different instruments/detectors? What are the effects of detector-to-detector variation in resolution, window, dead layer, incomplete charge collection on k-ratios for light elements below 2 keV?",
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+                    "authors": [
+                      "N W M Ritchie",
+                      "D E Newbury",
+                      "H Lowers",
+                      "M Mengason"
+                    ],
+                    "publication_date": "2018-08-01T00:00:00Z",
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+                    "title": "Exploring the limits of EDS microanalysis: rare earth element analyses",
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+                  },
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+                "snippets": [
+                  "For EDS measurements the signal from multiple lines sum into a single peak that  is measured simultaneously.",
+                  "Each of these lines will have slightly di\ufb00erent correction factors.",
+                  "The appropriate matrix correction for EDS is\n\n                                                                                   i Wi [ZAF]i\n                          [ZAF]EDS =                                               (2)\n                                                                                         i Wi\nwhere sum over i is over all the X-ray transitions in the integrated interval, Wi represents the nominal relative weight of the ith transition in a pure element and the [ZAF]i are the traditional single transition matrix correction factors.",
+                  "Complex standards can be chosen to minimise the dependence of the matrix correction on poorly known quantities.",
+                  "A standard similar in composition to the unknown  is likely to have a similar matrix correction so the ratio [ZAF]unk/[ZAF]std is close to unity",
+                  "The strategy used to resolve these interferences in National Institute of Standards and Technology DSTA-II (a pseudo-acronym) [DTSA-II can be downloaded for free https://goo.gl/MI1Ku] are additional spectra called peak-shape references (or simply references), which can be calibrated relative to the standard and \ufb01t to the unknown.",
+                  "National Institute of Standards and Technology DSTA-II (a pseudo-acronym) provides a mechanism called the Standard Bundle that sums standards and integrates the necessary peak-shape references.",
+                  "Multiple acquisitions from the unknown permit homogeneity testing and can bring to light sample preparation and other metrology problems.",
+                  "REE have very complex L-line structures with tens of characteristic lines spread over a range of energies.",
+                  "The data was collected on a TESCAN MIRA3 equipped with four independent 30 mm2 PulseTor SDDs"
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000013",
+                "context": "The excerpt states that SDD-EDS stability allows use of previously measured, stored standard spectra, provided a quality-assurance protocol confirms the unknown is measured under the same conditions as the archived standards (beam energy, dose, and EDS parameters). It emphasizes that spectra for unknowns and standards must be acquired under known, reproducible conditions including beam energy, electron dose/dead time, fixed time constant (resolution), detector-to-specimen distance (solid angle), detector take-off/azimuthal angles, and specimen tilt. A Faraday cup/digital picoammeter for beam current measurement is recommended for a rigorous k-ratio protocol. The authors recommend operating to yield ~10% detector deadtime to minimize pulse-coincidence (sum) peaks, noting coincidence grows significantly above ~15% deadtime; coincidence can still affect low-Z element peaks at high count rates. High-count spectra with stable peak shape and position improve MLLS peak fitting and thus k-ratio determination. The excerpt does not provide quantitative data on how detector-to-detector variations (resolution, window, dead layer, incomplete charge collection) specifically affect k-ratios for light elements below ~2 keV, so no direct numeric effects are given here.",
+                "question": "Can EDS standard spectra be transferred between different instruments/detectors? What are the effects of detector-to-detector variation in resolution, window, dead layer, incomplete charge collection on k-ratios for light elements below 2 keV?",
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+                      "Dale E. Newbury",
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+                    "title": "Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)",
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+                  },
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+                  "The stability of the SDD-EDS enables the careful analyst to operate with previously measured and stored standard spectra, providing that a quality assurance protocol is in place to confirm that the current measurement conditions for the unknown are consistent with the conditions under which the archived standards were measured: beam energy, dose, and EDS parameters.",
+                  "Spectra from the unknowns and standards must be measured under known and reproducible conditions of beam energy, dose (electron current 9 detector live time), and EDS operating conditions (fixed time constant, which defines a fixed  resolution;  fixed detector-to-specimen distance which with the detector active area defines the detector solid angle; known detector take-off angle and azimuthal angle relative to the specimen tilt axis; and known specimen tilt, which is preferably zero tilt, i.e., the beam is perpendicular to the specimen surface).",
+                  "A beam current measuring system consisting of a Faraday cup and a digital picoammeter is a necessary component if a fully rigorous k-ratio protocol is to be established [2].",
+                  "It is highly recommended that a conservative operating strategy be used for SDD-EDS measurements, with the beam current chosen to provide a detector deadtime of approximately 10 % to minimize pulse coincidence (sum peaks).",
+                  "Coincidence becomes progressively more signi\ufb01cant above 15 % deadtime.",
+                  "combination of high-count spectra with stable peak shape and position provides statistically robust peak references needed for MLLS fitting of spectral peaks to accurately extract the characteristic X-ray intensities",
+                  "Note that for a pure element of low atomic number, e.g., Al or Si, it is likely that a coincidence peak will still be seen for the primary peak even with this conservative counting strategy, but when such elements appear in the unknown at lower concentration, coincidence is generally reduced to a negligible level."
+                ],
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+              },
+              {
+                "id": "pqac-00000014",
+                "context": "The excerpt discusses using a \u2018\u2018remote standards\u2019\u2019 approach and calibration transfer to address limitations of purely first\u2011principles (standardless) EDS quantification. It states that the remote standards method, tied to measurements of real materials, is inherently more accurate than first\u2011principles approaches. A practical calibration\u2011transfer technique mentioned is using a \u2018\u2018golden detector\u2019\u2019 (calibrated at a beamline) plus a carefully chosen reference material to transfer the calibration from that detector to other instruments (Alvisi et al., 2006). The text also notes that vendors often do not fully document their standardless implementations, leaving users uncertain about how numerical concentrations are derived. The paper includes low\u2011voltage (E0 = 5 keV) analyses and spectra (e.g., borides with B K\u2011L2,3 peak and YBa2Cu3O7 at 5 keV, and an EDS spectrum of BaCl2 at 5 keV), indicating attention to light\u2011element measurements at low energies. While the excerpt does not provide quantitative k\u2011ratio shifts caused by detector\u2011to\u2011detector differences (resolution, window, dead layer, incomplete charge collection), it implies such differences must be corrected via transferred calibration/standards to obtain accurate low\u2011energy (below ~2 keV) analyses.",
+                "question": "Can EDS standard spectra be transferred between different instruments/detectors? What are the effects of detector-to-detector variation in resolution, window, dead layer, incomplete charge collection on k-ratios for light elements below 2 keV?",
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+                  "the remote standards method  is tied to measurements of real materials, it is inherently more accurate and is a good compromise between first-principles standardless analysis and locally collected standards-based analysis.",
+                  "One method is to use a \u201cgolden detector\u201d calibrated at a beamline and a carefully chosen reference material to transfer the calibration from the golden detector to others (Alvisi et al., 2006).",
+                  "guessing how vendors implement their \u201cstandard-less quantifica- tion\u201d because they have typically not provided the customer with adequate documentation on what is actually being done to derive numerical concentrations.",
+                  "Fig. 9. (a) EDS spectrum of BaCl2 at E0 = 5 keV; note the extended Ba M-family.",
+                  "Table 20. Analysis of Binary Borides (All Analyses Performed with E0 = 5 keV; B K-L2,3 Peak, C K-L2,3 Peak, Ti and Cr L-Family, and La M-Family Peaks).",
+                  "Table 21. Analysis of YBa2Cu3O7 at E0 = 5 keV."
+                ],
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+                "context": "The excerpt describes the fundamental EDS detection physics and the principal measurement artifact relevant to low-energy X-rays. Photoelectric absorption in Si produces electron\u2013hole pairs (about 3.6 eV per pair), so the number of charge carriers (and statistical fluctuations) scales with photon energy. The EDS system builds a histogram of photon energies and has a usable energy range from about 0.05 keV to ~30 keV depending on detector design. The main artifact is peak broadening (the EDS resolution function): even sharply defined X-ray lines are broadened by statistical and detector contributions, and the measured FWHM is an energy-dependent function (a referenced equation is provided). The text contrasts older Si(Li) detectors with modern silicon drift detectors (SDD-EDS), implying detector design changes the detection characteristics. The table of contents also lists low-energy artifacts (Si-escape peak, Si absorption edge, internal fluorescence) that can affect spectra below a few keV. Together, these points indicate that detector-to-detector differences in resolution, efficiency and design will influence the measured peak shapes and low-energy response, which are the factors that would affect quantitative ratios for light elements.",
+                "question": "Can EDS standard spectra be transferred between different instruments/detectors? What are the effects of detector-to-detector variation in resolution, window, dead layer, incomplete charge collection on k-ratios for light elements below 2 keV?",
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+                      "Dale E. Newbury",
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+                      "Nicholas W. M. Ritchie",
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+                  },
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+                  "As illustrated in .\t Fig. 16.1, the physical basis of energy dispersive X-ray spectrometry (EDS) with a semiconductor detector begins with photoelectric absorption of an X-ray photon in the active volume of the semiconductor (Si).",
+                  "This charge generation process requires approximately 3.6 eV per electron hole pair, so that the number of charge carriers is proportional to the original photon energy, Ep:",
+                  "The typical photon energy range that can be measured by EDS starts at a threshold of 0.05 keV and extends to 30 keV or even higher, depending on the detector design.",
+                  "16.1.1   The Principal EDS Artifact: Peak Broadening (EDS Resolution Function) \u2013 210",
+                  "If the EDS detection and measurement process were perfect, all the measurements for a particular characteristic X-ray peak would be placed in a single energy bin with a very narrow width.",
+                  "The EDS peak width (FWHM) measured experimentally is a function of the photon energy, which can be estimated approximately as (Fiori and Newbury 1978)",
+                  "The original type of EDS was the lithium-drifted silicon [Si(Li)-EDS] detector (. \t Fig. 16.1a), with a uniform electrode on the front and rear surfaces (Fitzgerald et al. 1968).",
+                  "Over the last 10 years, the Si(Li)-EDS has been replaced by the silicon drift detector design (SDD-EDS), illustrated in .\t Fig. 16.1b (Gatti and Rehak 1984; Struder et al. 1998).",
+                  "For example, the natural energy width of Mn K-L3 is approximately 1.5 eV."
+                ],
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+                "id": "pqac-00000015",
+                "context": "The excerpt describes differences between silicon drift detectors (SDD-EDS) and older Si(Li)-EDS: SDDs operate around -20 \u00b0C (Peltier cooled) versus -190 \u00b0C for Si(Li), and their modified structure yields higher throughput and larger solid angle. Crucially, SDD-EDS shows nearly constant resolution (peak shape) and calibration (peak stability) across a wide range of input count rates, so peak shape and position used for fitting remain stable from major to trace peaks. This consistency allows assembling clusters of SDD detectors without significant degradation of the combined output. The figures and captions also illustrate spectral identification issues, e.g., misidentification of Pb M-family peaks in different materials and the close superposition of Mn K- and L-family peaks after scaling. While the text emphasizes improved stability and detector clustering for SDDs, it does not directly state how standard spectra transfer between different instruments or quantify detector-to-detector effects (window, dead layer, incomplete charge collection) on k-ratios for light elements below 2 keV.",
+                "question": "Can EDS standard spectra be transferred between different instruments/detectors? What are the effects of detector-to-detector variation in resolution, window, dead layer, incomplete charge collection on k-ratios for light elements below 2 keV?",
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+                  "SDD-EDS replaces Si(Li)-EDS",
+                  "SDD-EDS operates at approximately -20  C, which is achieved with Peltier electronic cooling, compared to the -190 C of the Si(Li)-EDS achieved with a liquid nitrogen cryostat.",
+                  "SDD-EDS resolution (peak shape) and calibration (peak stability) are nearly constant over the entire input count rate range, as shown for the Mn K-family in Fig. 9a and the Mn L-family in Fig. 9b.",
+                  "This means that the shape and position of the peak reference necessary for accurate MLLS fitting is constant regardless of variations in the peak count rate ranging from that of a major constituent to that of a trace constituent.",
+                  "The consistency of performance is such that clusters of SDD detectors can be assembled where the ganged output is not significantly degraded compared to the output of the individual detectors.",
+                  "Fig. 8 a Lead, beam energy 20 keV, showing correct identification of the Pb L-family and PbMa,b, but misidentification of PbMf as WM and PbM2N4 as CdL [16\u201318].",
+                  "b NIST glass K230 with Pb as a major constituent, beam energy 20 keV; the Pb M-family is misidentified as SK and TcL, while the Pb L-family is ignored [16\u201318]",
+                  "Note excellent superposition of the peaks after scaling to the MnLa peak integral."
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-a969a5f7",
+                "context": "The excerpt describes using high-count SDD-EDS spectra and MLLS peak fitting to produce robust peak references and accurate k-value based quantification. SDD detectors reach much higher throughput (OCR) than Si(Li), with required time constants and resulting resolution trade-offs explicitly noted (e.g., <130 eV needs \u2264500 ns; shortening to 220 ns degrades resolution to 145 eV while raising OCR). The authors collected ~5 million counts per 50 s spectrum (0.10\u201320 keV) at 20 keV beam energy, used DTSA-II for MLLS peak fitting, and measured peak references on pure element standards (Mg, Si, Fe) and CaCO3 (Ca) to avoid interferences. Intensities were used to form k-values and apply XPP matrix corrections. The paper emphasizes the importance of specimen/standard geometry for standards-based protocols (flat polished bulk targets at defined angles). The excerpt focuses on detector time-constant/resolution and high-count reference formation; it does not provide explicit data or discussion about detector window materials, dead layers, or incomplete charge collection effects nor specific k-ratio shifts for light elements below 2 keV.",
+                "question": "Can EDS standard spectra be transferred between different instruments/detectors? What are the effects of detector-to-detector variation in resolution, window, dead layer, incomplete charge collection on k-ratios for light elements below 2 keV?",
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+                  },
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+                  "To achieve resolution below 130 eV (MnK\u03b1) typically requires a time constant of 500 ns or less for SDD-EDS compared to ~30 \u03bcs for Si(Li)-EDS.",
+                  "By choosing a shorter time constant (220 ns) that degrades the resolution to 145 eV, the single SDD-EDS detector can reach a maximum OCR of 270 kHz and the cluster can exceed 1.25 MHz.",
+                  "Thus, for the most critical parameter of detector throughput, the OCR vs. ICR performance of SDD-EDS greatly exceeds that of Si(Li)-EDS, and this level of performance directly translates into significant improvements in quantitative analysis by enabling collection of statistically robust EDS spectra in a practical measurement interval of 100 seconds or less.",
+                  "By forming the peak reference from a high count spectrum, the channel-to-channel variation due to random counting statistics is minimized, creating a more robust reference.",
+                  "The Bruker QUAD SDD-EDS was operated with the intermediate speed time constant (440 ns), which provided a peak OCR of approximately 130 kHz per detector, or 520 kHz for the cluster, at a measured resolution of 127.5 eV (MnK\u03b1).",
+                  "Spectra of unknowns and standards were collected for 50 s giving a spectrum integral (0.10 keV \u2013 20 keV) of approximately 5 million counts.",
+                  "MLLS peak references were measured on pure elements for Mg, Si, and Fe and on CaCO3 for Ca to ensure that there were no peak interferences corrupting the peak references.",
+                  "Intensity measurements on samples and standards were used to form k-values, and concentrations were calculated from the suite of k-values with the XPP matrix correction procedure embedded in DTSA-II.",
+                  "One of the critical requirements to satisfy the standards-based k-value measurement protocol concerns the geometry of the specimen and standard(s), all of which must be in the form of a flat, polished bulk target placed at carefully defined angles to the incident beam and the x-ray spectrometer."
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000022",
+                "context": "The excerpt lays out practical requirements relevant to low-kV SEM/EDS quantification. It emphasizes that the k-ratio/matrix-correction method assumes a homogeneous bulk specimen (interaction volume ~0.5\u201310 \u03bcm; secondary fluorescence up to 10\u2013100 \u03bcm) and that specimen and standards must be measured under identical conditions (beam energy, electron dose, EDS parameters, target orientation, take-off angle). Surface preparation is critical: a highly polished, flat surface with roughness <100 nm rms (and <50 nm rms for measurements of photons <1 keV) is required; chemical polishing should be avoided and ion milling can alter near-surface composition. For spectral quality and peak fitting, consistent EDS parameters are essential; a 5 eV/channel energy width is recommended to adequately span peaks including those below 1 keV, and spectra should cover from ~100 eV up to the Duane\u2013Hunt limit. These points inform choices for low-energy (e.g., 5 keV) analyses, standard selection, peak-fitting resolution, and the need to control sample preparation and measurement geometry to minimize artifacts and allow meaningful k-ratio/matrix corrections.",
+                "question": "Low beam energy 5 keV EDS quantification of trace Mg in Al matrix, Al Ka peak tail under Mg Ka, detection limits, peak overlap correction, standard selection for low-kV analysis",
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+                    "url": "https://doi.org/10.1007/978-1-4939-6676-9_20",
+                    "title": "Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step",
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+                    "formatted_citation": "Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations."
+                  },
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+                  "Bulk specimens have dimensions that are sufficiently large to contain the full range of the direct electron-excited X-ray production (typically 0.5\u201310 \u03bcm) as well as the range of the secondary X-ray fluorescence induced by the propagation of the characteristic and continuum X-rays (typically 10\u2013100 \u03bcm).",
+                  "The k-ratio/matrix correction protocol for the analysis of bulk specimens has two basic underlying assumptions:",
+                  "1. The composition is homogeneous throughout the entire volume of the specimen in which primary characteristic X-rays are directly excited by the incident electron beam and in which secondary X-ray fluorescence is induced during the propagation of the primary characteristic and continuum X-rays.",
+                  "2. The X-ray intensities measured on the location of interest on the specimen and on the standard(s) differ only because the compositions are different.",
+                  "A highly polished, flat surface must be created following the appropriate metallographic preparation protocol for each particular material.",
+                  "The surface should be finished to a surface roughness below 100 nm root mean square (rms) ... When the analysis involves measuring low energy photons below 1 keV ... the surface finish should be better than 50 nm rms.",
+                  "\"Chemical polishing\" should be avoided since chemical reactions may induce shallow, near-surface compositional changes that affect the very shallow region that is excited and sampled by the electron beam.",
+                  "ion beam milling can be used to shape and finish the specimen, but it must be recognized that implantation of the primary ion and differential material removal caused by differences in the sputtering rates of the elements can modify the composition of a shallow surface layer.",
+                  "Consistency in the choice of the EDS parameters is critical for establishing a robust analytical measurement environment, and this is especially important when archived standard spectra are used.",
+                  "A choice of 5 eV for the channel energy width will provide a sufficient number of channels to adequately span all of the peaks of analytical interest, including the peaks that occur below 1 keV.",
+                  "It is also desirable for the measured spectrum to span the full range of the excited X-ray energy, from an effective threshold of approximately 100 eV to the Duane\u2013Hunt limit",
+                  "The basis of the k-ratio/matrix corrections protocol is measurement of the X-ray spectra of the specimen and standard(s) under identical conditions of beam energy, known electron dose ... EDS parameters ... target orientation (tilt angle, ideally 0\u00b0 tilt, i.e., beam perpendicular to the target surface), and EDS take-off angle (i.e., the detector elevation angle above the flat sample surface)."
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000017",
+                "context": "The excerpt emphasizes iterative, peak-fitting\u2013based analysis for detecting and quantifying trace elements in the presence of major-element interference. Peak fitting must include possible interfering peaks (example: TiKa/TiKb appearing in residuals when omitted); residual spectra should be inspected after stripping fitted peaks to reveal minor/trace constituents hidden beneath larger peaks. Residuals can also be used to estimate limits of detection, and detection limits may be lowered by accumulating more counts. Low-energy X-ray peaks are affected by chemical-shift and peak-shape \u2018\u2018chemical effects,\u2019\u2019 and EDS has significantly poorer spectral resolution than WDS, making interference correction more challenging for low-energy (low-Z) analyses. The text shows use of matrix-appropriate references and standards (e.g., \"Si and W as references and standards\" and \"using as standards elemental Mn and Ta, with sanbornite (BaSi2O5) for Si and Ba\") and examples where oxygen was set by stoichiometry. Together these points support strategies for low-kV EDS quantification: careful peak fitting including interfering major-element peaks, iterative re-analysis guided by residuals, increasing counts to improve detection limits, and using appropriate standards/matrix references.",
+                "question": "Low beam energy 5 keV EDS quantification of trace Mg in Al matrix, Al Ka peak tail under Mg Ka, detection limits, peak overlap correction, standard selection for low-kV analysis",
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+                    "authors": [
+                      "Dale E. Newbury",
+                      "Nicholas W. M. Ritchie"
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+                    "title": "Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)",
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+                  "This example illustrates that comprehensive analysis of an unknown must be performed iteratively.",
+                  "when peak \ufb01tting is performed without including a peak reference for Ti, the TiKa and TiKb peaks can be recognized in the residuals.",
+                  "After peak \ufb01tting and quantitative analysis for those elements are performed, careful examination of the residual spectrum with those peaks stripped off may reveal previously unrecognized minor and trace constituents hidden under the higher intensity peaks.",
+                  "The residual spectrum can also be used to estimate limits of detection for trace constituents of interest, and the analytical strategy can be modified if necessary to lower the limit of detection by accumulating more counts.",
+                  "the low-energy photon peaks are subject to the so-called \u2018\u2018chemical effects\u2019\u2019 manifested as shifts in the X-ray peak position and changes in peak shape that depend on chemical binding.",
+                  "the significantly poorer spectral resolution of EDS compared to WDS",
+                  "Si and W as references and standards",
+                  "using as standards elemental Mn and Ta, with sanbornite (BaSi2O5) for Si and Ba"
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000023",
+                "context": "The excerpt highlights peak overlap and misidentification risks relevant to attempting low-kV (e.g., 5 keV) EDS quantification of trace Mg in an Al matrix. Table 4 shows Mg K\u03b1 (1.253 keV) and Al K\u03b1 (1.487 keV) lie in nearby energy bands, a situation prone to peak interference. Automatic peak-identification can mislabel peaks (e.g., BrL\u03b1 misidentified as AlK\u03b1) and such errors occur more frequently for minor/trace constituents. The authors recommend careful analyst review of tentative assignments, using software tools to explore alternative identifications, sequential peak identification with peak fitting and residual inspection, and adjusting beam energy when appropriate \u2014 either decreasing to reduce self-absorption or increasing to excite additional shells for confirmation. They also emphasize the value of standards-based k-ratio/matrix corrections (vs. standardless analysis), since standardless normalization can obscure clues (raw analytical total) that reveal dubious analyses. Overall, the text supports using peak fitting/residual checks, careful standard selection and standards-based quantification, beam-energy optimization, and cautious interpretation when quantifying trace Mg in an Al matrix at low beam energies.",
+                "question": "Low beam energy 5 keV EDS quantification of trace Mg in Al matrix, Al Ka peak tail under Mg Ka, detection limits, peak overlap correction, standard selection for low-kV analysis",
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+                    "authors": [
+                      "Dale E. Newbury",
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+                  },
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+                "snippets": [
+                  "1.20\u20131.30        MgKa (1.253); AsLa (1.282); TbMa (1.246)",
+                  "1.45\u20131.55          AlKa (1.487); BrLa (1.480); YbMa (1.521)",
+                  "BrL\u03b1 misidentified as AlK\u03b1",
+                  "Elemental misidenti\ufb01cation typically occurs in a few percent of attempted peak identi\ufb01cations for major constituents, with the frequency of mistakes increasing signi\ufb01cantly for minor and trace constituents and especially in cases where peak interference occurs [16\u201318].",
+                  "Analysis with the standards-based k-ratio/matrix corrections protocol reveals the impact of geometric effects on X-ray microanalysis through the behavior of the raw analytical total [19].",
+                  "Because of the inevitable normalization that must occur in the standardless analysis procedure, the important clue that the raw analytical total provides that will identify such dubious analyses is lost.",
+                  "decreasing the beam energy to reduce the self-absorption that can occur for certain elements or increasing the beam energy to excite an additional X-ray shell to confirm the presence of an element.",
+                  "sequential peak identification\u2014peak fitting\u2014residual inspection methodology will",
+                  "the prudent analyst will inspect each tentative elemental assignment that is suggested by the automatic peak identi\ufb01cation software and con\ufb01rm or correct the identi\ufb01cation by carefully considering possible alternatives using software tools to explore the database of characteristic X-ray energies."
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000024",
+                "context": "Relevant points for low-kV EDS quantification (e.g., trace Mg in an Al matrix) from the excerpt: meticulous sample preparation and consistent measurement conditions are essential for accurate EDS results. Quantification uses the k-ratio method with matrix (ZAF) corrections that account for atomic number (Z), absorption (A) and secondary fluorescence (F); Z and A are typically computed from \u03c6(\u03c1z)-models. For EDS, multiple X-ray transitions are summed in an integrated peak and each transition has its own correction, so an overall weighted [ZAF]EDS must be applied. Standard selection matters: simple standards are easier but can increase dependence on poorly known parameters (e.g., mass absorption coefficients), while matrix-matched (complex) standards reduce matrix-correction dependence because [ZAF]unk/[ZAF]std approaches unity. Peak overlaps/interferences can be handled using peak-shape reference spectra (e.g., DTSA-II peak-shape references) and careful spectral fitting. Improving detection limits and precision is aided by collecting multiple spectra (N \u2248 5\u201310) of shorter live time, inter-comparing/rejecting outliers, and summing for better statistics. The excerpt also notes that complex line structure can be beneficial for EDS and gives an example dataset collected with SDD detectors (30 mm2) at 20 keV and 0.9 nA.",
+                "question": "Low beam energy 5 keV EDS quantification of trace Mg in Al matrix, Al Ka peak tail under Mg Ka, detection limits, peak overlap correction, standard selection for low-kV analysis",
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+                    "citation": "N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013.",
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+                    "authors": [
+                      "N W M Ritchie",
+                      "D E Newbury",
+                      "H Lowers",
+                      "M Mengason"
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+                  "All of WDS\u2019s requirements for meticulous sample preparation and maintaining consistent measurement conditions remain equally as critical for EDS.",
+                  "The most common approach to quanti\ufb01cation of EDS and WDS data is the k-ratio approach",
+                  "The matrix correction compensates for di\ufb00erences in the way that the electrons and X-rays interact with the sample.",
+                  "There are three predominant mechanisms. The \ufb01rst mechanism (\u2019atomic number\u2019 or Z) has to do with how the energetic electrons interact with the material in terms of backscatter losses and energy loss. The second mechanism (\u2019absorption\u2019 or A) has to do with how the X-rays, once generated, escape from the sample in the direction of the detector. The third mechanism (\u2019secondary \ufb02uorescence\u2019 or F) concerns how X-rays can generate addition X-rays through photoabsorption and subsequent X-ray emission.",
+                  "A \u03c6(\u03c1z)-curve is an expression that models the ionisation in an in\ufb01nitesimally thick layer at depth z relative to the ionisation in an in\ufb01nitesimally thick \ufb01lm at z = 0.",
+                  "where sum over i is over all the X-ray transitions in the integrated interval, Wi represents the nominal relative weight of the ith transition in a pure element and the [ZAF]i are the traditional single transition matrix correction factors.",
+                  "Simple standards are easier to work with but typically produce less accurate results because the matrix corrections are typically larger and dependent on poorly known quantities like [\u03bc/\u03c1], the mass absorption coe\ufb03cient.",
+                  "Complex standards can be chosen to minimise the dependence of the matrix correction on poorly known quantities.",
+                  "A standard similar in composition to the unknown  is likely to have a similar matrix correction so the ratio [ZAF]unk/[ZAF]std is close to unity",
+                  "The strategy used to resolve these interferences in National Institute of Standards and Technology DSTA-II (a pseudo-acronym) [DTSA-II can be downloaded for free https://goo.gl/MI1Ku] are additional spectra called peak-shape references (or simply references), which can be calibrated relative to the standard and \ufb01t to the unknown.",
+                  "it is usually bene\ufb01cial to collect multiple measurements from each material.",
+                  "It is a good strategy to collect N spectra (with N \u22485 to 10) for a live-time t/N from the standard rather than one for a live-time t.",
+                  "Multiple acquisitions from the unknown permit homogeneity testing and can bring to light sample preparation and other metrology problems.",
+                  "measurements of minerals containing minor and trace quantities (Cz < 10.0 % mass fraction) of REE are a challenge for both WDS and EDS.",
+                  "the complex line structure provides signi\ufb01cant spectral structure, which is bene\ufb01cial for EDS measurements.",
+                  "The data was collected on a TESCAN MIRA3 equipped with four independent 30 mm2 PulseTor SDDs",
+                  "The beam energy was 20 keV and the probe current was 0.9 nA."
+                ],
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+                "context": "The excerpt gives practical guidance relevant to low-voltage (5 keV) EDX on light elements: using low E0 reduces X-ray information depth (useful for surface/near-surface features) but also limits which lines are excited and increases the chance of unresolved low-energy overlaps. It emphasises that the SEM electron energy should be at least 1.8\u00d7 the X-ray peak energy to excite a line, and recommends appropriate detector windows (windowless, polymer, or Si3N4) for light-element detection. Pile-up can produce spurious peaks (example: C_K + O_K producing an apparent 0.8 keV peak), so careful pile-up correction and inspection for artefacts is required. For quantification, the report recommends energy-scale calibration, use of factory k-ratios and matrix correction factors derived from elemental standards of similar chemistry, and good sample preparation (flat, polished, normal to beam, 35\u00b0 to detector). It also warns that standardless normalised analysis is inappropriate when some elements do not produce quantifiable peaks. The excerpt does not provide numerical detection limits nor specific discussion of Al-K\u03b1 tailing under Mg-K\u03b1, but it highlights general limitations of low-kV analysis and the need for standards, calibration, and pile-up/overlap handling.",
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+                  "5 kV SEM accelerating voltage was chosen here to minimise the X-ray information depth, since the Pt particles are nano-sized (Figure 11a).",
+                  "At 5 kV, only C, O, N, and Si can be identified.",
+                  "The Ti-K peak (4.510 keV) is not excited, the Ti-L (0.452 keV) and O-K peak (0.523 keV) peaks are overlapped, and several minor peaks between 0.6 and 2 keV remain unidentified.",
+                  "Comparison of the raw (green) and pile-up corrected (grey) spectra shows that the small grey peak at 0.8 keV is an artefact from insufficient pile-up correction (C_K @ 0.277 + O_K @ 0.523 = 0.800 keV) and should not be assigned to an element.",
+                  "Windowless, polymer, or Si3N4 window EDX detector for light element detection (Z \u2264 11)",
+                  "SEM accelerating voltage \u2013 electron energy is at least 1.8 \u00d7 X-ray peak energy for all elements.",
+                  "Sample surface positioned normal to the electron beam and 35\u00b0 to the EDX detector",
+                  "Normalised standardless analysis is inappropriate for hydrogen-containing materials, because hydrogen contributes to the mass of the sample but does not scatter X-rays, or where not all elements present have quantifiable X-ray peaks in the acquired spectrum.",
+                  "Factory-supplied k-ratio and matrix correction factor data from elemental standards with similar chemical properties to sample."
+                ],
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+                "id": "pqac-e4c961e5",
+                "context": "The excerpt highlights practical issues and recommended approaches for low beam-energy (E0 \u22645 keV) EDS analysis that are directly relevant to attempting trace Mg quantification in an Al matrix. Modern SDD-EDS detectors can measure very low photon energies, enabling low-kV work, but quantitative low-energy analysis is substantially more challenging than conventional energies. Surface and environmentally altered near-surface layers become a larger fraction of the interaction volume at low E0 and can strongly bias results. Detector geometry differences (take-off angle) require correction factors that grow in importance at lower photon energies. The authors recommend exploiting the entire spectrum (peak-to-background methods and model-based continuum fitting) because P/B approaches are more robust to topography, transport physics, and mass-absorption coefficient uncertainties, and high SDD throughput yields adequate counts rapidly. They suggest using peak-to-background standardless analysis to seed selection of real standards and iterating measurement protocols, with a comprehensive uncertainty model guiding optimization. These points bear on detection limits, overlap corrections, and how to choose standards and measurement strategies for low-kV Mg-in-Al quantification.",
+                "question": "Low beam energy 5 keV EDS quantification of trace Mg in Al matrix, Al Ka peak tail under Mg Ka, detection limits, peak overlap correction, standard selection for low-kV analysis",
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+                  "A disadvantage occurs if the detector take-off angle (X-ray emergence angle) differs between the reference detector and the user\u2019s detector, requiring that a correction factor be calculated, which has an increasing influence at lower photon energies.",
+                  "Low beam energy (E0 \u22645 keV) X-ray microanalysis has been made practical by the outstanding electron beam performance, e.g., size, current, and stability, of SEMs in this energy range complemented by the excellent low-photon energy performance of SDD-EDS, which can now measure photons down to energies of 40 eV or less.",
+                  "However, quantitative low beam energy X-ray microanalysis is much more challenging compared with analysis in the conventional beam energy range (10 keV \u2264E0 \u226425 keV).",
+                  "Such surface layers form only a small percentage of the electron range under the conventional beam energy operation and do not significantly affect quantitative measurements. However, in the low beam energy regime, these shallow surface layers comprise a more significant fraction of the range and have a significant impact on quantitative analysis.",
+                  "6. Using the entire EDS spectrum: Peak-to-background (P/B) methods based upon exploiting properties of the continuum (bremsstrahlung) X-ray background become much more viable with the high-integrated count spectra made possible by the high throughput of the SDD-EDS.",
+                  "Peak-to-background methods do not require the measurement of probe dose to produce a useful analytical total and peak-to-background methods are much less susceptible to sample topography, providing that the measured continuum is from the analyzed volume and is not degraded by remote sources, e.g., backscattered electrons striking other portions of the specimen or the instrument chamber.",
+                  "Peak-to-background methods are much less sensitive to electron and X-ray transport physics and to uncertainties in mass absorption coefficients.",
+                  "The first measurement might use a peak-to-background standardless analysis algorithm to seed the algorithm which selects the first-pass set of optimized standards and measurement conditions."
+                ],
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+                "id": "pqac-00000020",
+                "context": "The excerpt discusses EDS detection limits, peak-to-background considerations, and metrology relevant to low-voltage EDS trace analysis. Limits of detection are fundamentally set by the continuum (background) relative to the characteristic signal; the same detection-limit formalism applies to EDS and WDS, but for EDS the measured intensities must be integrated over identical channel ranges on standard and unknown. Peak-to-background on EDS depends on the channel ranges used to estimate continuum and peak; optimal practice is to integrate the central FWHM (\u224876% of peak) and use equivalent ranges of continuum above and below. Modern SDDs have greatly improved throughput, resolution, and low-energy response (enabling detection down to Be-K and even Li-K), and for many measurements SDDs can match or exceed WDS in accuracy and precision. However, SDDs still generally have inferior peak-to-background ratios compared with WDS, limiting the lowest trace detection. Careful metrology and sample preparation (polish, conductive path, beam/sample geometry and working distance control) are emphasized, and standards should be measured and integrated over the same channel ranges as the unknown.",
+                "question": "Low beam energy 5 keV EDS quantification of trace Mg in Al matrix, Al Ka peak tail under Mg Ka, detection limits, peak overlap correction, standard selection for low-kV analysis",
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+                      "D E Newbury",
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+                  "Ultimately,  limits of  detection are constrained by the magnitude  of the background (continuum) level relative to the signal (characteristic) level.",
+                  "The same equation can be used for either EDS or WDS. In the case of EDS, the intensity should be integrated over the same range of channels on the unknown and the standard.",
+                  "The peak-to-background ratio on an EDS is determined by the ranges of channels used to estimate the continuum and peak intensity.",
+                  "Typically, integrating the peak over the central full-width half-max (FWHM) and an equivalent range of the continuum (above and below) produces close to optimal results. The central FWHM corresponds to approximately 76 % of the total peak intensity.",
+                  "The latest revolution, the silicon drift detector (SDD), has brought bountiful improvements in throughput, size, resolution, and stability",
+                  "In the early days, the Na-K line was the practical limit, but today EDS detectors routinely detect Be-K X-rays and, some even, Li-K X-rays [5].",
+                  "For many measurements, the SDD can match or exceed the accuracy and precision of a WDS measurement in a fraction of the instrument and operator time [10].",
+                  "Regardless, the SDD is unlikely to ever challenge the WDS at the lowest measurable trace levels [13] due to inferior peak-to-background ratios.",
+                  "Regardless of the technology, the key to good microanalysis measurements is careful metrology.",
+                  "Samples are often mounted in epoxy, and polished to a mirror-like surface finish.",
+                  "The orientation of the sample is maintained normal to the incidence electron beam, and the working distance is maintained precisely."
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+                "context": "Relevant points for low-voltage (\u22485 keV) EDS quantification of trace Mg in an Al matrix: the incident beam energy must exceed the shell excitation energy (ideally by \u22651.25\u00d7), and 5 keV is effectively the lowest E0 that still excites at least one characteristic X-ray family for most elements. At E0 \u22645 keV, more elements become inaccessible and low-energy analysis increases the influence of surface layers and carbon contamination, which can change X-ray absorption. Trace measurements (C < 0.01) commonly involve peaks close to the continuum background and subject to overlap from much more intense major-element peaks; when a trace peak is buried under a major peak, the measurement challenge is substantially increased. Limits of detection (CDL) can be estimated from counts using CDL = [3NB1/2/(NS \u2212 NB)]CS, and practical LODs on suitably long counts can reach ~0.0002\u20130.0005 mass fraction (200\u2013500 ppm) depending on element and matrix. Mutual interferences can often be addressed with careful peak fitting. These points imply that for Mg-in-Al at 5 keV one should expect significant Al\u2013Mg overlap issues, require rigorous peak fitting and standards appropriate for low-kV geometry and surface/contamination effects, and use long counts to approach ppm-level detection.",
+                "question": "Low beam energy 5 keV EDS quantification of trace Mg in Al matrix, Al Ka peak tail under Mg Ka, detection limits, peak overlap correction, standard selection for low-kV analysis",
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+                  "the beam energy must exceed the critical shell excitation energy, Ec, ideally by a factor of at least 1.25.",
+                  "A beam energy of 5 keV  is the lowest value at which at least one characteristic X-ray peak or family can be excited for  all elements of the Periodic Table, except for H and He which do not produce characteristic X-rays.",
+                  "As the beam energy is reduced below 5 keV, an increasing number of elements becomes inaccessible to EPMA due to the lack of a practically measurable characteristic X-ray peak",
+                  "Measurement of trace elements, arbitrarily defined in this paper as those present at a mass concentration C < 0.01, involves fitting peaks that are close to the X-ray continuum background and that may also be subject to overlap from the significantly more intense peaks of major and minor constituents.",
+                  "limits of detection in the range 0.0002\u20130.0005 mass concentration (200\u2013500 parts per million), depending  on  the   particular  element  and  the  matrix composition, can be reached with counting times below 500 s",
+                  "CDL = [3NB1/2/(NS \u2212NB)]CS,               (6)",
+                  "For peaks that do not suffer interference, CDL, the limit of detection (minimum mass fraction) can be estimated from the measured (or independently known) composition as",
+                  "There are many peak interference situations encountered in the analysis of SRM 610, but those that involve mutual interferences of trace constituents that produce peaks of similar intensity, e.g., the Ti K-family and the Ba L-family, can be solved with peak fitting.",
+                  "When the X-ray peak for a trace constituent is buried under the interfering peak of a major or minor constituent, the measurement challenge is substantially increased.",
+                  "Contamination from carbon deposition can increase the absorption of X-rays with energies near the carbon K-edge (0.284 keV) above that expected from the compositions of the unknown and standard."
+                ],
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+                "context": "The excerpt discusses quantitative EDS work performed at low beam energy (E0 = 5 keV) and highlights practical issues and methods relevant to low-kV analysis. Several tables and spectra are reported for analyses at 5 keV (e.g., borides, carbides, YBa2Cu3O7 and BaCl2 spectra), illustrating that low-energy spectra include extended low-energy families (for example, an \u201cextended Ba M-family\u201d), and that analyses used K-L2,3 or L-/M-family peaks depending on element and voltage. The text contrasts first-principles (standardless) analysis with a \u201cremote standards\u201d approach, stating that the remote standards method is tied to measurements of real materials and is inherently more accurate. It also notes a practical calibration transfer technique using a \u201cgolden detector\u201d calibrated at a beamline and a reference material. Finally, uncertainties were evaluated using NIST DTSA-II (reported as combined uncertainties), and tables give mean concentrations, RDEV, and replicate sigmas, conveying achievable precision at 5 keV. These points bear on detection limits, peak overlap and deconvolution, and standard selection for low-kV Mg-in-Al measurements.",
+                "question": "Low beam energy 5 keV EDS quantification of trace Mg in Al matrix, Al Ka peak tail under Mg Ka, detection limits, peak overlap correction, standard selection for low-kV analysis",
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+                      "Dale E. Newbury",
+                      "Nicholas W.M. Ritchie"
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+                  "All Analyses Performed with E0 = 5 keV; B K-L2,3 Peak, C K-L2,3 Peak, Ti and Cr L-Family, and La M-Family Peaks).",
+                  "note the extended Ba M-family.",
+                  "the remote standards method  is tied to measurements of real materials, it is inherently more accurate and is a good compro- mise between first-principles standardless analysis and locally col- lected standards-based analysis.",
+                  "one method is to use a \u201cgolden detector\u201d calibrated at a beamline and a carefully chosen reference material to trans- fer the calibration from the golden detector to others (Alvisi et al., 2006).",
+                  "Standardless analysis requires only",
+                  "Combined Uncertainties as Estimated from NIST DTSA-II."
+                ],
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+                "context": "Relevant points for low\u2011kV (5 keV) EDS quantification of trace Mg in an Al matrix: EDX detectors typically have energy resolution \u2265100 eV so peaks are broad; ambiguity only occurs for peaks within ~30 eV but broad tails and fitting can still cause interference between nearby lines. Quantitative analysis requires sufficient electron overvoltage (ISO 22309:2011 recommends \u22651.8) and primary energy must exceed the X-ray energy. Detector efficiency varies strongly with X-ray energy and detector/window configuration, so elemental standards are needed for full quantification to cancel detector response differences. All quantitative work requires subtraction of Bremsstrahlung background; background fitting methods differ between software and a poor fit signals high uncertainty. Matrix (ZAF) corrections are required to account for electron backscattering, X-ray absorption and secondary fluorescence. Low\u2011energy detection is also affected by detector windows (Be absorbs <1 keV); windowless detectors are preferable but not always available. Operators must check and correct detector artefacts (sum/escape peaks) and ensure standards and acquisition conditions are appropriate for low\u2011kV analysis.",
+                "question": "Low beam energy 5 keV EDS quantification of trace Mg in Al matrix, Al Ka peak tail under Mg Ka, detection limits, peak overlap correction, standard selection for low-kV analysis",
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+                  "When electrons of sufficient energy hit a sample, they generate X-rays of specific energies characteristic of the elements present.",
+                  "Since the energy resolution of EDX detectors are usually \u2265 100 eV, only a single broader peak is measured.",
+                  "Elemental assignment of X-ray peaks might be ambiguous if the peaks from multiple elements have similar energies (within 30 eV of each other).",
+                  "An electron overvoltage of at least 1.8 is specified for quantitative analysis in ISO 22309:2011.",
+                  "It is impossible to generate X-rays that have a higher energy than the primary electron energy.",
+                  "Problem (1) explains why elemental standards are needed for full quantitative analysis, so that differences in detector efficiency can be cancelled out.",
+                  "All quantitative analysis considers the characteristic X-ray peaks only, which means it is necessary to remove the intensity contribution of background X-rays generated by Brehmsstralung radiation.",
+                  "Background correction is important in quantification, but different EDX analysis software packages use different methods and this usually cannot be tuned by the user.",
+                  "A poor background fit (Figure 1b), which leads to inadequate peak area determination, is still a useful warning sign to the operator that that the quantitative results have high uncertainty.",
+                  "Beryllium windows absorb the majority of X-rays below 1 keV and therefore are not suitable for use with low-Z elements below Na (Na K = 1.04 keV).",
+                  "Windowless detectors would be preferable but are not currently available at NPL in 2024.",
+                  "These account for the effects of: - Electron backscattering (which increases with atomic number Z) ... - X-ray Absorption ... - Secondary X-ray Fluorescence"
+                ],
+                "used_images": false
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+                "id": "pqac-00000025",
+                "context": "The excerpt describes importing RAW spectra into ImageJ\u2011Fiji as a \u201cstack\u201d and using \u201cImage \u2192 Stack \u2192 Reslice\u201d and \u201cImage \u2192 Stack \u2192 Z\u2011project\u201d to \u201cidentify the range of channels\u201d for lines (e.g. Cu L\u2011family, Cu K\u2011L2,3), then converting with \u201cImage \u2192 Lookup Tables \u2192 Thermal\u201d and extracting traverses via \u201cAnalyze \u2192 Surface Plot\u201d and \u201cAnalyze \u2192 Plot Profile.\u201d It defines \u201cdead\u2011time,\u201d \u201clive\u2011time,\u201d and \u201creal\u2011time,\u201d noting \u201cthe effective probe dose equals the live\u2011time times the probe current.\u201d Count\u2011rate linearity Check 5 uses a Faraday cup, picoammeter, flat polished Cu, 15\u201325 keV beam, and \u201ccollect a 60 live\u2011time second spectrum,\u201d stepping probe current ~10\u201320\u00d7.",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "bibtex": "@article{goldstein2018energydispersivexray,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"209-234\",\n    doi = \"10.1007/978-1-4939-6676-9\\_16\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_16\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n",
+                    "authors": [
+                      "Joseph I. Goldstein",
+                      "Dale E. Newbury",
+                      "Joseph R. Michael",
+                      "Nicholas W. M. Ritchie",
+                      "John Henry J. Scott",
+                      "David C. Joy"
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+                "context": "- Windows are \"ultrathin layers of polymer or silicon nitride mounted on a grid\" whose grid bars (often 0.38 mm thick) can \"occlude the direct transmission of X\u2011rays\", producing position\u2011dependent efficiency (open area typically 75\u201380%).  \n- Detector grid examples (MOXTEK AP3/AP5): thickness 380/265 \u00b5m; rib width 59/45 \u00b5m; opening 190 \u00b5m; open area 76%/78%; acceptance angle 53\u00b0/72\u00b0.  \n- Recommended checks: set ~20% dead time, \"collect a 60 live\u2011time second spectrum\", map counts vs working distance to find optimum.  \n- For imaging: acquire \"moderate\u2011to\u2011high probe current for an hour or more at 256 \u00d7 256\u2011pixel\" and \"extract the raw intensities and not the normalized intensities.\"",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "authors": [
+                      "Joseph I. Goldstein",
+                      "Dale E. Newbury",
+                      "Joseph R. Michael",
+                      "Nicholas W. M. Ritchie",
+                      "John Henry J. Scott",
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+                    "url": "https://doi.org/10.1007/978-1-4939-6676-9_16",
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+                "context": "From Goldstein et al., Ch.16 (EDS): spectral \"process time\" trades throughput vs resolution\u2014longer process time \u2192 higher resolution but lower throughput; shorter \u2192 higher throughput but worse resolution. \"By spectral resolution we mean the width of a characteristic peak, usually taken to be the Mn K\u2011L2,3 (K\u03b1) peak.\" Modern SDDs can reach ~122\u2013128 eV; compromising to 130\u2013135 eV is recommended; even 140\u2013150 eV can give \"excellent quantitative results.\" \"Do not use an 'adaptive process time' for standards-based quantitative analysis.\" Most spectrum files are ASCII and \"the vendors write a line containing the elevation or nominal take\u2011off angle.\" Detector windows are ultrathin polymer or silicon\u2011nitride on a grid (open area 75\u201380%; grid bar \u22480.38 mm).",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                "id": "pqac-00000028",
+                "context": "The study evaluated the accuracy of low-beam-energy (E0 = 5 keV) electron-excited X-ray microanalysis using energy-dispersive spectrometry (EDS) with the NIST DTSA-II software and a standards-based k-ratio protocol. A total of 263 concentration measurements were made, covering 39 elements across 113 materials (including CRMs, stoichiometric compounds, minerals, and alloys). Accuracy was assessed using the relative deviation from expected value (RDEV) metric. Results show very high accuracy at 5 keV: more than 98% of the 263 measurements fell within \u00b15% RDEV, and 82% fell within -2% to 2% RDEV. DTSA-II also provides uncertainty budgets for reported concentrations, accounting for random and systematic contributions arising from X-ray counting statistics and matrix-correction factors, which underpins the reported confidence in these accuracy statistics.",
+                "question": "NIST DTSA-II accuracy at 5 keV low beam energy, RDEV results, number of measurements, how many percent fell within \u00b15% RDEV at 5 keV?",
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+                    "citation": "Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4.",
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+                    "authors": [
+                      "Dale E. Newbury",
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+                    "url": "https://doi.org/10.1007/s10853-024-10285-4",
+                    "title": "Testing the accuracy of low-beam-energy electron-excited X-ray microanalysis with energy-dispersive spectrometry",
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+                  "specifically at an incident beam energy of 5 keV, which is the lowest beam energy for which a useful characteristic X-ray peak can be excited for all elements of the periodic table, excepting H and He.",
+                  "Two-hundred sixty-three concentration measurements for 39 elements in 113 materials were determined following the k-ratio protocol and using the EDS analytical software NIST DTSA-II.",
+                  "The accuracy of the results, as characterized by the relative deviation from expected value (RDEV) metric, was such that more than 98% of the results were found to be captured within a range of \u00b15% RDEV, while 82% of the results fell in the range -2% to 2% RDEV."
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+                "context": "The excerpt defines the accuracy metric RDEV as RDEV = [(measured value \u2212 expected value)/expected value] \u00d7 100%. Table 1 summarizes DTSA\u2011II results at a beam energy E0 = 5 keV, comprising 263 concentration measurements for 39 elements in 113 materials. Figure 3a shows the RDEV histogram for atomic concentrations derived from that table. For this 5 keV dataset, more than 98% of the results are captured within \u00b15% RDEV, with 82% within \u22122% to 2% RDEV. A separate raw totals histogram (sum of constituent mass concentrations) spans 0.8\u20131.2, with 67% of analyses in the 0.95\u20131.05 range. The paper notes the RDEV distribution at 5 keV is similar to that observed using conventional higher beam energies (\u226510 keV) when higher\u2011energy characteristic X\u2011rays are selected, and that Table 1 lists measured raw and normalized concentrations plus atomic concentrations and the computed RDEV values for each reported analysis.",
+                "question": "NIST DTSA-II accuracy at 5 keV low beam energy, RDEV results, number of measurements, how many percent fell within \u00b15% RDEV at 5 keV?",
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+                    "authors": [
+                      "Dale E. Newbury",
+                      "Nicholas W. M. Ritchie"
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+                    "publication_date": "2024-10-14T00:00:00Z",
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+                    "journal": "Journal of Materials Science",
+                    "publisher": "Springer Science and Business Media LLC",
+                    "url": "https://doi.org/10.1007/s10853-024-10285-4",
+                    "title": "Testing the accuracy of low-beam-energy electron-excited X-ray microanalysis with energy-dispersive spectrometry",
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+                    "formatted_citation": "Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal."
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+                  "RDEV = [(measured value \u2212expected value)\u2215expected value)]x 100%",
+                  "Table 1 summarizes the analytical results for 263 con-centration measurements for 39 elements in 113 mate-rials measured at \u00adE0 = 5 keV.",
+                  "Figure 3a shows a histogram of the RDEV values at \u00adE0 = 5 keV for the atomic concentrations derived from Table 1.",
+                  "more than 98% of the results are found to be captured within a range of \u00b15% RDEV, and 82% of the results fall in the range \u2212\u20092% to 2% RDEV.",
+                  "The distribution ranges from 0.8 to 1.2, with 67% of the analyses falling in the range 0.95\u20131.05."
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+                "context": "Excerpt shows a Table 1 of 5 keV EDS quantifications (JEOL 8500F microscope, \"BrukerQuad\" SDD) using NIST SRMs (e.g. \"SRM482\", \"SRM481\", \"SRM479\") and alloy mixes (Au\u2013Cu, Ag\u2013Au). It reports atomic/mass concentrations (example: Atomicconc 0.9282 / 0.0718; Normalized mass conc 0.8067 / 0.1933), total raw sums \u22481.0066, and a \"DTSA_IIUnc_Budget\" column (examples: \"\u00b10.0117\", \"\u00b10.0026\", \"\u00b10.0175\", later entries \u00b10.0032\u2013\u00b10.0832). Photon/event counts per standard appear (e.g. \"6,705,457\", \"4,778,550\") and a \"0.1-5counts\" energy range is shown.",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "authors": [
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+                "id": "pqac-00000031",
+                "context": "Newbury & Ritchie (J Mater Sci 2024) tested standards-based k\u2011ratio EDS at E0 = 5 keV using NIST DTSA\u2011II: 263 concentration measurements for 39 elements in 113 materials. Key points: E0 = 5 keV is \u201cthe lowest beam energy for which an analytically useful characteristic X\u2011ray\u201d (all elements except H, He); electron range R \u2248 E0^1.66. DTSA\u2011II attaches an uncertainty budget including random statistics and systematic \u201cZ\u201d (scattering/energy\u2011loss) and \u201cA\u201d (self\u2011absorption) terms, giving >98% of results within \u00b15% RDEV and 82% within \u22122% to 2% RDEV.",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                "context": "Table 1 (J Mater Sci 2024, 59:19088\u201319111) reports many measured 5 keV EDS spectra collected on a JEOL8500f with a \"BrukerQuad\" detector (standards named e.g. CuO_5kV, Cr2O3_5keV, Fe3C_5kV, NiTi_5kV, \"MgO\", \"Al\", etc.). Spectra have multi-million total counts (examples shown 3.08\u00d710^6\u20138.18\u00d710^6). For each standard the table lists \"Knownmass\", \"Atomicconc\"/\"Atomicconcreference\", \"Normalizedconc\", \"Rawmassconc\" (e.g. MgO: Normalizedconc 0.2893, Rawmassconc 0.2865) and a \"DTSA_IIUnc_Budget\" (per-standard uncertainties range from \u00b10.0008 up to \u00b10.0988; MgO entry \u2248 \u00b10.0097). Reported raw-conc RDEV values span roughly \u22127% to +12%.",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "authors": [
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+                "context": "- Figures compare NiTi spectra at E0 = 15, 10 and 5 keV; the \u201cpeak fitting residual spectrum\u201d at E0 = 5 keV \u201cshows much reduced structure\u201d around absorption edges vs 10\u201315 keV.  \n- Lowering E0 reduces self\u2011absorption and the absorption correction (and RDEV), improving peak fits for low\u2011energy lines because the beam \u201cdoes not penetrate deep\u201d so generated continuum is less absorbed.  \n- Residual = unknown spectrum minus (standard characteristic intensity \u00d7 k\u2011ratio); it is \u201ca somewhat artificial construct\u201d whose quality depends on continuum modeling, differential absorption, and bonding\u2011induced energy shifts.  \n- Raw analytical totals normally lie 0.98\u20131.02; at 5 keV they ranged ~0.8\u20131.2 despite vetted samples.  \n- Advice: sequentially lower E0 from \u226510 keV down to \u22645 keV to reveal surface anomalies; electron channeling and surface layers (oxidation/coatings) can strongly bias low\u2011E analyses.",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                "context": "- Measure and record probe current with a Faraday cup + picoammeter; collect a \"60 live-time second spectrum\" from a standard (e.g. Cu).  \n- Vary probe current in ~10\u201320 steps up to \"approximately 2 times the optimal probe current\", collect 60 s at each step, integrate the characteristic peak (no background correction), and plot measured intensity divided by probe current vs probe current. The result \"should be a horizontal line.\" Example fit: f(x) = 35876.1202787172 x, R2 = 0.9999923818.  \n- Dead-time causes loss of counts; check for probe-current zero offset by blanking the beam.  \n- Energy calibration: use ~\"5-eV/channel\", calibrate with two points (zero strobe + a high line such as Mn K-L2,3 or Cu K-L2,3); \"resolution (peak shape) should be constant with input count rate.\" Modern detectors are largely linear, though mid-energy KLM markers may be misaligned \"by a channel or two.\"",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "citation": "Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16.",
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+                    "bibtex": "@article{goldstein2018energydispersivexray,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"209-234\",\n    doi = \"10.1007/978-1-4939-6676-9\\_16\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_16\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n",
+                    "authors": [
+                      "Joseph I. Goldstein",
+                      "Dale E. Newbury",
+                      "Joseph R. Michael",
+                      "Nicholas W. M. Ritchie",
+                      "John Henry J. Scott",
+                      "David C. Joy"
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+                    "formatted_citation": "Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations."
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+                "context": "Table (J Mater Sci 2024, 59:19088\u201319111) reports DTSA\u2011II quantification of ~100 measured standards at 5 keV on JEOL8500F with BrukerQuad/Bruker2019 detectors. It lists \"Knownmass\", \"Atomicconc\", \"Rawmassconc\", \"Normalizedconc\", per\u2011standard \"DTSA_IIUnc_Budget\" (examples: \"\u00b10.0023\", \"\u00b10.0043\", \"\u00b10.0177\", \u2026 up to \"\u00b10.0370\") and relative deviations (\"Raw-concRDEV\" values ranging ~-7.9% to +8.3%). Per\u2011spectrum total counts are very large (examples: 4,100,229; 7,363,940). MgO and other light\u2011element standards are explicitly included.",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "citation": "Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4.",
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+                    "authors": [
+                      "Dale E. Newbury",
+                      "Nicholas W. M. Ritchie"
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+                    "publication_date": "2024-10-14T00:00:00Z",
+                    "year": 2024,
+                    "volume": "59",
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+                    "pages": "19088-19111",
+                    "journal": "Journal of Materials Science",
+                    "publisher": "Springer Science and Business Media LLC",
+                    "url": "https://doi.org/10.1007/s10853-024-10285-4",
+                    "title": "Testing the accuracy of low-beam-energy electron-excited X-ray microanalysis with energy-dispersive spectrometry",
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+                "context": "AutoEMXSp automates SEM-EDS and achieves \"atomic fraction measurements with relative deviations typically below 5\u201310%.\" It acquires \"one hundred spectra of 50,000 counts each\" (20\u201345 min total). Quantification uses a peak-to-background (P/B) approach: Pi,p/Bi,p \u2243 Pi,b/Bi,b and I*i = Pi,b \u2243 Pi,p \u00b7 Bi,b/Bi,p. The excerpt flags low-energy issues: \"the background shape underneath the peaks, influenced by X\u2011ray absorption edges and detector artifacts\u2014particularly below 2 keV,\" and notes continuum models that neglect electron stopping power can cause substantial errors when standards and samples differ.",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "citation": "Andrea Giunto, Yuxing Fei, Pragnay Nevatia, Bernardus Rendy, Nathan Szymanski, and Gerbrand Ceder. Harnessing automated sem-eds and machine learning to unlock high-throughput compositional characterization of powder materials. Unknown journal, Oct 2025. URL: https://doi.org/10.21203/rs.3.rs-7837297/v1, doi:10.21203/rs.3.rs-7837297/v1.",
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+                      "Andrea Giunto",
+                      "Yuxing Fei",
+                      "Pragnay Nevatia",
+                      "Bernardus Rendy",
+                      "Nathan Szymanski",
+                      "Gerbrand Ceder"
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+                "context": "The excerpt emphasizes metadata/quality frameworks for nanomaterial data. It notes development of \"nanoCRED criteria\" and that the SciRAP tool was extended with \"38 criteria for reporting quality, 19 criteria for methodological quality, and 4 guidance items\" to \"support harmonized evaluation.\" It cites initiatives: Nanomaterial Data Curation Initiative (NDCI), MIRIBEL, MINChar, MIAN, NanoTox Metadata List, GUIDEnano, and a \"two-step method\" using ToxRTool (Card & Magnuson 2010). Comandella et al. assess completeness of physicochemical data via an (meta)data template. Explicit traceability and documented experimental metadata are prioritized.",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "bibtex": "@article{dumit2026challengesandfuture,\n    author = \"Dumit, Ver\u00f3nica I. and Furxhi, Irini and Nymark, Penny and Afantitis, Antreas and Ammar, Ammar and Amorim, Monica J. B. and Antunes, Dalila and Avramova, Svetlana and Battistelli, Chiara L. and Basei, Gianpietro and Bossa, Cecilia and Cimpan, Emil and Cimpan, Mihaela Roxana and Ciornii, Dmitri and Costa, Anna and Delpivo, Camilla and Dusinska, Maria and Fonseca, Ana Sofia and Friedrichs, Steffi and Hodoroaba, Vasile\u2010Dan and Hristozov, Danail and Isigonis, Panagiotis and Jeliazkova, Nina and Kochev, Nikolay and Kranjc, Eva and Maier, Dieter and Melagraki, Georgia and Papadiamantis, Anastasios G. and Puzyn, Tomasz and Rauscher, Hubert and Reilly, Katie and Jim\u00e9nez, Araceli S\u00e1nchez and Scott\u2010Fordsmand, Janeck J. and Shandilya, Neeraj and Shin, Hyun Kil and Tancheva, Gergana and van Rijn, Jeaphianne P. M. and Willighagen, Egon L. and Wyrzykowska, Ewelina and Bakker, Martine I. and Drobne, Damjana and Exner, Thomas E. and Himly, Martin and Lynch, Iseult\",\n    title = \"Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re\u2010Usability: A Position Paper From the Nanosafety Community\",\n    year = \"2026\",\n    journal = \"Advanced Sustainable Systems\",\n    volume = \"10\",\n    month = \"Dec\",\n    doi = \"10.1002/adsu.202500567\",\n    url = \"https://doi.org/10.1002/adsu.202500567\",\n    publisher = \"Wiley\",\n    issue = \"4\",\n    issn = \"2366-7486\"\n}\n",
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+                      "Irini Furxhi",
+                      "Penny Nymark",
+                      "Antreas Afantitis",
+                      "Ammar Ammar",
+                      "Monica J. B. Amorim",
+                      "Dalila Antunes",
+                      "Svetlana Avramova",
+                      "Chiara L. Battistelli",
+                      "Gianpietro Basei",
+                      "Cecilia Bossa",
+                      "Emil Cimpan",
+                      "Mihaela Roxana Cimpan",
+                      "Dmitri Ciornii",
+                      "Anna Costa",
+                      "Camilla Delpivo",
+                      "Maria Dusinska",
+                      "Ana Sofia Fonseca",
+                      "Steffi Friedrichs",
+                      "Vasile\u2010Dan Hodoroaba",
+                      "Danail Hristozov",
+                      "Panagiotis Isigonis",
+                      "Nina Jeliazkova",
+                      "Nikolay Kochev",
+                      "Eva Kranjc",
+                      "Dieter Maier",
+                      "Georgia Melagraki",
+                      "Anastasios G. Papadiamantis",
+                      "Tomasz Puzyn",
+                      "Hubert Rauscher",
+                      "Katie Reilly",
+                      "Araceli S\u00e1nchez Jim\u00e9nez",
+                      "Janeck J. Scott\u2010Fordsmand",
+                      "Neeraj Shandilya",
+                      "Hyun Kil Shin",
+                      "Gergana Tancheva",
+                      "Jeaphianne P. M. van Rijn",
+                      "Egon L. Willighagen",
+                      "Ewelina Wyrzykowska",
+                      "Martine I. Bakker",
+                      "Damjana Drobne",
+                      "Thomas E. Exner",
+                      "Martin Himly",
+                      "Iseult Lynch"
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+                    "publication_date": "2025-12-26T00:00:00Z",
+                    "year": 2026,
+                    "volume": "10",
+                    "issue": "4",
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+                    "journal": "Advanced Sustainable Systems",
+                    "publisher": "Wiley",
+                    "url": "https://doi.org/10.1002/adsu.202500567",
+                    "title": "Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re\u2010Usability: A Position Paper From the Nanosafety Community",
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+                    "formatted_citation": "Ver\u00f3nica I. Dumit, Irini Furxhi, Penny Nymark, Antreas Afantitis, Ammar Ammar, Monica J. B. Amorim, Dalila Antunes, Svetlana Avramova, Chiara L. Battistelli, Gianpietro Basei, Cecilia Bossa, Emil Cimpan, Mihaela Roxana Cimpan, Dmitri Ciornii, Anna Costa, Camilla Delpivo, Maria Dusinska, Ana Sofia Fonseca, Steffi Friedrichs, Vasile\u2010Dan Hodoroaba, Danail Hristozov, Panagiotis Isigonis, Nina Jeliazkova, Nikolay Kochev, Eva Kranjc, Dieter Maier, Georgia Melagraki, Anastasios G. Papadiamantis, Tomasz Puzyn, Hubert Rauscher, Katie Reilly, Araceli S\u00e1nchez Jim\u00e9nez, Janeck J. Scott\u2010Fordsmand, Neeraj Shandilya, Hyun Kil Shin, Gergana Tancheva, Jeaphianne P. M. van Rijn, Egon L. Willighagen, Ewelina Wyrzykowska, Martine I. Bakker, Damjana Drobne, Thomas E. Exner, Martin Himly, and Iseult Lynch. Challenges and future directions in assessing the quality and completeness of advanced materials safety data for re\u2010usability: a position paper from the nanosafety community. Advanced Sustainable Systems, Dec 2026. URL: https://doi.org/10.1002/adsu.202500567, doi:10.1002/adsu.202500567. This article has 2 citations and is from a peer-reviewed journal."
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+                "context": "- Benchmarks span \"38 elements, ranging from nitrogen (Z = 7) to bismuth (Z = 83)\". Standard P/B values came from \"bulk polished samples of the pure metallic form when available, or otherwise from simple binary or ternary compounds.\"\n- RDEV defined: \"RDEV = (ni \u2212 ni,nominal) / ni,nominal\".\n- Dataset: 8,226 RDEV values from 2,483 spectra. Per-spectrum RDEV: 61.3% (84.4%) <5% (10%); at cluster centroids: 75.8% (93.6%) <5% (10%).\n- Absolute errors: 71.2% / 90.3% / 95.8% within 1 / 2 / 3 at%. Many large RDEV >10% occur at low concentrations (<10 at%).\n- Uncertainty: 48.1% (91.2%) of ni have \u03c3i <1 at% (<2 at%); relative uncertainties <5% (10%) in 66.2% (95.6%).\n- Method: \"refined spectral fitting routines and standard-based EDS quantification\" (example: NIST K-412 composition listed: Fe 3.1 at%, Mg 10.6 at%, Ca 6.0 at%, Al 4.0 at%, Si 16.8 at%, O 59.4 at%).",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "authors": [
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+                      "Yuxing Fei",
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+                      "Bernardus Rendy",
+                      "Nathan Szymanski",
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+              {
+                "id": "pqac-ebc93c14",
+                "context": "The excerpt discusses the general choice and role of physical standards for EPMA/EDS quantification. It distinguishes simple standards (pure elements or simple compounds) from complex, matrix-matched standards. Simple standards are easier to use but typically yield larger matrix-correction uncertainties because they depend more on poorly known parameters such as mass absorption coefficients ([\u03bc/\u03c1]). Matrix-matched (complex) standards reduce dependence on those uncertain parameters because the ratio of matrix-correction factors for unknown and standard tends toward unity. The authors note that software/tools such as NIST DTSA-II support handling complex interferences by using calibrated peak-shape reference spectra and a Standard Bundle mechanism for summing standards. As an example, engineered REE glasses with a Si\u2013Al\u2013Ca glass matrix were used as well-characterized standards in the study. The excerpt does not list specific NIST SRM numbers (e.g., SRM 470, 481, 482, 2063a), nor does it enumerate Mg compound standards (MgO, periclase, forsterite, spinel) or comment on using pure Mg metal as an EPMA standard.",
+                "question": "What physical standards are used for Al, Si, Mg in EPMA and EDS analysis? Which NIST SRMs are relevant (SRM 470 K-glasses, SRM 481, 482, 2063a)? What compound standards are used for Mg (MgO, periclase, forsterite, spinel)? Is pure Mg metal usable as an EPMA standard?",
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+                    "citation": "N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013.",
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+                    "authors": [
+                      "N W M Ritchie",
+                      "D E Newbury",
+                      "H Lowers",
+                      "M Mengason"
+                    ],
+                    "publication_date": "2018-08-01T00:00:00Z",
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+                    "title": "Exploring the limits of EDS microanalysis: rare earth element analyses",
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+                    "formatted_citation": "N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations."
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+                  "materials used for standards may either be simple (pure elements or simple compounds) or complex (similar or \u201dmatrix-matched\u201d).",
+                  "Simple standards are easier to work with but typically produce less accurate results because the matrix corrections are typically larger and dependent on poorly known quantities like [\u03bc/\u03c1], the mass absorption coe\ufb03cient.",
+                  "Complex standards can be chosen to minimise the dependence of the matrix correction on poorly known quantities.",
+                  "The strategy used to resolve these interferences in National Institute of Standards and Technology DSTA-II (a pseudo-acronym) [DTSA-II can be downloaded for free https://goo.gl/MI1Ku] are additional spectra called peak-shape references (or simply references), which can be calibrated relative to the standard and \ufb01t to the unknown.",
+                  "These glasses have either 3 or 4 REE at approximately 3 % mass fraction to 4 % mass fraction. The remaining material being a Si-Al-Ca glass."
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-6b780b33",
+                "context": "The excerpt emphasizes using well-characterized physical standards for EPMA/SDD-EDS: typically a separate standard mount containing a suite of pure elements and stoichiometric compounds is prepared (co-mounting is possible but less common). Multi-element mixtures (alloys, glasses, minerals) can be used only if their composition is accurately known and they are homogeneous at the micrometer scale. NIST SRM 470 (K412 glass) is explicitly mentioned and is shown in spectra containing O, Mg, Al, Si, Ca, and Fe. For low-Z pure-element standards such as Al or Si, the text notes that coincidence peaks can still appear and that such elements are used as highly excited pure-element standards for setting conservative operating conditions. It recommends a conservative SDD-EDS operating strategy with beam current chosen to yield ~10% detector deadtime to minimize pulse coincidence, and stresses careful surface preparation (highly polished) to avoid topography errors. The excerpt does not mention NIST SRMs 481, 482, or 2063a, nor does it list specific Mg compound standards (MgO, periclase, forsterite, spinel) or directly state whether pure Mg metal is acceptable as an EPMA standard.",
+                "question": "What physical standards are used for Al, Si, Mg in EPMA and EDS analysis? Which NIST SRMs are relevant (SRM 470 K-glasses, SRM 481, 482, 2063a)? What compound standards are used for Mg (MgO, periclase, forsterite, spinel)? Is pure Mg metal usable as an EPMA standard?",
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+                      "Dale E. Newbury",
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+                    "formatted_citation": "Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal."
+                  },
+                  "chunk_id": "59de9ff3-24e5-4836-962e-ed908a0379b4"
+                },
+                "score": 4,
+                "snippets": [
+                  "NIST SRM 470 (K412 glass)",
+                  "the sample must be highly polished to remove topography",
+                  "Standards can be co-mounted during metallographic preparation of the unknowns, but a more typical strategy is to prepare a separate standard mount containing a suite of pure elements and stoichiometric compounds.",
+                  "Note that for a pure element of low atomic number, e.g., Al or Si, it is likely that a coincidence peak will still be seen for the primary peak even with this conservative counting strategy",
+                  "Multi-element mixtures such as alloys glasses, or minerals can also serve as standards, but in addition to accurately knowing the composition, such materials must be confirmed to be homogeneous on a micrometer lateral scale before they can serve as suitable standards.",
+                  "it is highly recommended that a conservative operating strategy be used for SDD-EDS measurements, with the beam current chosen to provide a detector deadtime of approximately 10 %"
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-b201eb75",
+                "context": "The excerpt provides limited but relevant procedural details for standards and calibration in SEM-EDS workflows. It states that energy-scale calibration should be performed \"using a Al and Cu standard sample\" and references ISO 22309:2011 for energy-scale calibration and manufacturer instructions. For detection of light elements (Z \u2264 11) the text recommends a windowless, polymer, or Si3N4-window EDX detector. The document warns that normalised standardless analysis is inappropriate for hydrogen-containing materials (since H contributes mass but produces no X-rays) or when not all elements present have quantifiable X-ray peaks. For semi-quantitative analysis, factory-supplied k-ratio and matrix correction factor data from elemental standards with similar chemical properties are recommended. The table also notes a recommendation that \"have atomic number > 11\" for elements intended for quantification, implying elements of Z>11 are preferred for reliable quantification (so Mg, Z=12, would fall above that threshold). The excerpt does not mention any specific NIST SRMs (e.g., SRM 470 K-glasses, SRM 481, SRM 482, SRM 2063a), does not list Mg compound standards (MgO, periclase, forsterite, spinel), and does not discuss using pure Mg metal as an EPMA standard.",
+                "question": "What physical standards are used for Al, Si, Mg in EPMA and EDS analysis? Which NIST SRMs are relevant (SRM 470 K-glasses, SRM 481, 482, 2063a)? What compound standards are used for Mg (MgO, periclase, forsterite, spinel)? Is pure Mg metal usable as an EPMA standard?",
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+                  },
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+                  "using a Al and Cu standard sample",
+                  "Energy-scale calibration according to ISO 22309:2011 and manufacturer instructions.",
+                  "Windowless, polymer, or Si3N4 window EDX detector for light element detection (Z \u2264 11)",
+                  "Normalised standardless analysis is inappropriate for hydrogen-containing materials,",
+                  "have atomic number > 11"
+                ],
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+              {
+                "id": "pqac-00000040",
+                "context": "Table 1 (pages 14\u201316) lists the analytical standards used in this study. For Mg-containing materials the table repeatedly lists MgO as the standard. For Si-bearing materials the standard shown is SiO2, and for Al the table shows Al2O3 as a standard. The table also cites NIST SRM identifiers used in the study: entries labelled SRM470_K411_O- and SRM470_K412_O- appear in the material/standard columns, and the text explicitly mentions EDS spectra of NIST SRM 482 (Au40-Cu60) recorded at multiple beam energies. Sample preparation notes indicate materials were mounted, polished and (for non-conductors) coated with an approximately 10 nm carbon layer. The excerpt does not mention SRM 481 or SRM 2063a, nor does it list compound Mg standards such as periclase, forsterite, or spinel, nor any use of pure Mg metal as an EPMA standard\u2014those details are not present in the provided pages.",
+                "question": "What physical standards are used for Al, Si, Mg in EPMA and EDS analysis? Which NIST SRMs are relevant (SRM 470 K-glasses, SRM 481, 482, 2063a)? What compound standards are used for Mg (MgO, periclase, forsterite, spinel)? Is pure Mg metal usable as an EPMA standard?",
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+                  "MgO",
+                  "SiO2",
+                  "Al2O3",
+                  "SRM470_K411_O-",
+                  "SRM470_K412_O-",
+                  "NIST SRM 482 (Au40-Cu60)"
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000039",
+                "context": "The excerpt shows EPMA/EDS analyses using both pure-element and oxide standards. For Al (in SRM 2062) the authors used pure element standards (Table 7: \"Pure Element Standards; Al K ...\"). Si is analyzed in different sample types; for glasses (SRM 470 K411 and K412) the analyses use oxide standards rather than pure elements (\"Oxide Standards Except for Fe\"). SRM 470 (K\u2011glass; K411 and K412) is explicitly used for glass analyses; SRM 2062 (Al\u2013Ti\u2013Nb\u2013W alloy) and SRM 483 (Fe\u20133Si transformer steel) are also included in these tables. Mg is treated as an oxide in the glass analyses: oxygen was either by assumed stoichiometry or \"O Directly Analyzed (MgO)\" (Tables 8b, 9b), indicating MgO was used as a compound standard/oxygen standard in these DTSA\u2011II analyses. The excerpt does not mention NIST SRM 481, 482, or 2063a, nor does it mention compound standards such as periclase, forsterite, or spinel, and it does not state whether pure Mg metal was used or recommended as an EPMA standard. Further sources should be consulted for recommendations on periclase/forsterite/spinel or the acceptability of pure Mg metal as a standard.",
+                "question": "What physical standards are used for Al, Si, Mg in EPMA and EDS analysis? Which NIST SRMs are relevant (SRM 470 K-glasses, SRM 481, 482, 2063a)? What compound standards are used for Mg (MgO, periclase, forsterite, spinel)? Is pure Mg metal usable as an EPMA standard?",
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+                    "title": "Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping",
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+                  "Table 7. Analysis of NIST SRM 2062 (Al\u2013Ti\u2013Nb\u2013W Alloy) (E0 = 20 keV; Pure Element Standards; Al K, Ti K, Nb L, W L; Values in Normalized Mass Concentration; Combined Uncertainties Estimated from NIST DTSA-II).",
+                  "Table 6. Analysis of NIST SRM 483 (Fe\u20133Si Transformer Steel Alloy) (E0 = 20 keV; Pure Element Standards; K-Shell X-rays; Values in Normalized Mass Concentration; Combined Uncertainties Estimated from NIST DTSA-II).",
+                  "Table 8a. Analysis of SRM 470 (K411 Glass) (E0 = 10 keV; Oxide Standards Except for Fe; O by Assumed Stoichiometry; K-Shell X-rays; Values in Mass Concentration; Combined Uncertainties Estimated from NIST DTSA-II.",
+                  "Table 8b. Analysis of SRM 470 (K411 Glass) [E0 = 10 keV; Oxide Standards Except for Fe; O Directly Analyzed (MgO); K-Shell; Values in Mass Concentration; Values in Mass Concentration; Combined Uncertainties Estimated from NIST DTSA-II].",
+                  "Table 9b. Analysis of SRM 470 (K412 Glass) [E0 = 10 keV; Oxide Standards Except for Fe; O by Assumed Stoichiometry or Directly Analyzed (MgO); K-Shell; Values in Normalized Mass Concentration; Combined Uncertainties Estimated from NIST DTSA-II].",
+                  "Oxide Standards Except for Fe",
+                  "Pure Element Standards"
+                ],
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+                "id": "pqac-3f95bc32",
+                "context": "The excerpt discusses how remote standards libraries for EDS/EPMA are built from measured X-ray peak intensities of pure elements and stoichiometric compounds at several beam energies using a characterized EDS. It notes use of a \"golden detector\" calibrated at a beamline and transfer to local detectors, and that interpolation/extrapolation plus X-ray generation equations are used when a needed standard or beam energy is missing. Standardless analysis only requires beam energy and spectrometer takeoff angle, and results must often be normalized to 100 wt% (particularly when oxygen is estimated by assumed stoichiometry). The paper provides example reference materials: Table 22 lists NIST Microanalysis Glass K523 (E0 = 20 keV) with Mg mass fraction 0.00097 (CDL 0.00019), and Table 23 summarizes analysis of NIST SRM 610 (trace elements in glass). The authors caution that early standardless testing showed large RDEVs (95% spanning \u00b125% relative) and that vendors typically do not provide customers with rigorous accuracy testing of their standardless procedures.",
+                "question": "What physical standards are used for Al, Si, Mg in EPMA and EDS analysis? Which NIST SRMs are relevant (SRM 470 K-glasses, SRM 481, 482, 2063a)? What compound standards are used for Mg (MgO, periclase, forsterite, spinel)? Is pure Mg metal usable as an EPMA standard?",
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+                  "The remote standards library is populated with characteristic       X-ray peak intensities from the pure element and stochiometric    compounds measured at several beam energies with a carefully    characterized EDS.",
+                  "One method is to use a \u201cgolden detector\u201d calibrated at a beamline and a carefully chosen reference material to transfer the calibration from the golden detector to others (Alvisi et al., 2006).",
+                  "If a given analysis requires a standard not in the library or at a beam energy not represented, then interpolation/extrapolation from existing measurements augmented by the equations  of X-ray generation and propagation can be    used to supply the missing value(s).",
+                  "Standardless analysis requires only that the analyst provides the beam energy and the X-ray spectrometer takeoff angle relative to the specimen surface.",
+                  "Standardless analysis results, including oxygen  if calculated by the method of assumed stoichiometry, must be normalized to unity mass fraction (100 wt%) to be placed on a sensible basis.",
+                  "Table 22. NIST Microanalysis Glass K523 (E0 = 20 keV; Integrated Counts 0.1 \u2013 20 keV = 26.6 million).",
+                  "Mg                             0.00097                        0.00019",
+                  "Table 23. Analysis of NIST SRM 610 (Trace Elements in Glass) (E0 = 20 keV; Integrated Counts 0.1\u201320 keV = 1.7 billion).",
+                  "Early testing of standardless analysis with known materials revealed a distribution of RDEVs such that 95% of the analytical results spanned an RDEV range of \u00b125% relative (Newbury et al., 1995).",
+                  "customers are not typically provided by the vendor with rigorous testing of the accuracy of the standardless analysis procedure"
+                ],
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+              {
+                "id": "pqac-5fdafae7",
+                "context": "The excerpt documents SEM/SDD-EDS analyses of NIST SRM 470 (K411 glass) using a standards-based k-ratio protocol processed with NIST DTSA-II. In these analyses the authors explicitly state that the standards used included the pure elements Mg, Si, and Fe, while Ca was taken from SRM 470 (glass K412) and oxygen was calculated by assumed stoichiometry of the cations. Analyses were performed at E0 = 20 keV on well-polished, carbon-coated specimens (0.1 \u03bcm alumina final polish; ~<10 nm carbon coat) following the k-ratio protocol. The paper also emphasizes strong geometric effects (surface roughness, scratches, fragments) on measured k-ratios and apparent concentrations. The excerpt does not mention Al standards, other NIST SRMs such as SRM 481, 482, or 2063a, nor compound Mg standards (MgO, periclase, forsterite, spinel), nor does it address EPMA-specific standard practice directly. It does, however, show that pure Mg metal was used here as an EDS standard.",
+                "question": "What physical standards are used for Al, Si, Mg in EPMA and EDS analysis? Which NIST SRMs are relevant (SRM 470 K-glasses, SRM 481, 482, 2063a)? What compound standards are used for Mg (MgO, periclase, forsterite, spinel)? Is pure Mg metal usable as an EPMA standard?",
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+                  },
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+                "context": "The provided excerpt documents multiple analyses carried out at an incident energy E0 = 5 keV. Table 20 explicitly states that the binary boride analyses were performed at E0 = 5 keV (with B K-L2,3, C K-L2,3, Ti/Cr L-family, La M-family peaks). Table 21 gives the standards used for the YBa2Cu3O7 analysis at 5 keV: oxygen and yttrium were referenced to Y2O3 (\"O (Y2O3 Standard and Reference)\" and \"Y (Y2O3 Standard and Reference)\"), copper to a generic \"Standard and Reference\" (Cu), and barium used BaF2 as the standard and BaCl2 as a reference (\"Ba (BaF2 Standard and BaCl2 Reference)\"). Figure 9 caption also shows BaCl2 spectra recorded at 5 keV. The excerpt also discusses the \"remote standards\" approach vs first-principles standardless analysis. However, the excerpt does not list any standards for Mg, Al, or Si; therefore the specific standards used for Mg, Al, and Si are not present in this text and cannot be determined from the provided pages.",
+                "question": "What are the standards used at 5 keV in the Newbury and Ritchie 2024 study? What standards did they use for Mg, Al, Si specifically?",
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+                  },
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+                  "Table 20. Analysis of Binary Borides (All Analyses Performed with E0 = 5 keV; B K-L2,3 Peak, C K-L2,3 Peak, Ti and Cr L-Family, and La M-Family Peaks).",
+                  "Table 21. Analysis of YBa2Cu3O7 at E0 = 5 keV. O (Y2O3 Standard and Reference); Cu (Standard and Reference); Y (Y2O3 Standard and Reference); Ba (BaF2 Standard and BaCl2 Reference), Values in Normalized Mass Concentration; Combined Uncertainties as Estimated from NIST DTSA-II.",
+                  "Fig. 9. (a) EDS spectrum of BaCl2 at E0 = 5 keV; note the extended Ba M-family.",
+                  "the remote standards method  is tied to measurements of real materials, it is inherently more accurate and is a good compromise between first-principles standardless analysis and locally collected standards-based analysis."
+                ],
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+                "id": "pqac-00000041",
+                "context": "Table 1 (continued) shows the standards used for the 5 keV analyses. In the block of columns labeled with materials ending in \u201c_5keV\u201d the Standard row lists GaP, MgO, MgO, SiO2, CaF2, K412, MgO, MgO, Al2O3, SiO2, CaF2, K411. The corresponding Ele-ment row maps those standards to elements: P, O, Mg, Si, Ca, Fe, O, Mg, Al, Si, Ca, Fe. Thus for the 5 keV measurements shown in this portion of the table (materials such as Mg-Al-P_5keV, Mg-Al-Si-Ca-Fe_5keV, Si-Pb_5keV), the standards assigned to Mg are MgO, to Al is Al2O3, and to Si is SiO2. The table therefore indicates repeated use of MgO for Mg standards and SiO2 and Al2O3 for Si and Al standards within the 5 keV dataset.",
+                "question": "What are the standards used at 5 keV in the Newbury and Ritchie 2024 study? What standards did they use for Mg, Al, Si specifically?",
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+                  "Standard         GaP   MgO     MgO       SiO2       CaF2       K412     MgO     MgO        Al2O3       SiO2       CaF2       K411",
+                  "Ele-ment  P O   Mg   Si   Ca   Fe  O   Mg   Al   Si   Ca   Fe",
+                  "Mg-Al-P_5keV",
+                  "Mg-Al-Si-Ca-Fe_5keV",
+                  "Si-Pb_5keV"
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+                "context": "The excerpt states that standards for analysis were a suite of pure elements (examples given include Si) and, where pure elements were incompatible or unstable under the vacuum/beam, stoichiometric compounds were used (example given: MgO). Non-conductive standards were coated with an ~10 nm carbon layer. The paper shows examples of spectra recorded at 5 keV (e.g., NIST SRM 482 (Au40-Cu60)), and it notes that some materials (example: AlN) were excluded because C and O became significant at reduced beam energies. The excerpt therefore indicates Mg was analyzed using a stoichiometric compound standard (MgO) and Si was included among the pure-element standards. The excerpt does not explicitly state which standard was used for Al.",
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+                  "Standards for analysis consisted of a suite of pure elements, e.g., B, C, Si, Ti, Cr, Fe, Ni, Cu, Zn, Mo, etc., and for those pure elements that are incompatible with the instrument vacuum requirements or which are unstable under electron beam bombardment, stoichiometric compounds, e.g., MgO, \u00adFeS2, KCl, etc., were utilized.",
+                  "Non-conductive standards were coated with a thin (approximately 10 nm) carbon layer applied by thermal evaporation.",
+                  "An example of a material deemed accept- able for this study is shown in Figure 2, where EDS spectra of NIST SRM 482 (Au40-Cu60) recorded at \u00adE0 = 20 keV, 10 keV, and 5 keV displayed with scaling to the Cu L family peak (yellow band) reveals only a small increase in the relative intensity of the C and O peaks as the beam energy is reduced.",
+                  "Figure 1\u2002 \u2009EDS spectra of AlN recorded at \u00adE0 = 15 keV, 10 keV and 5 keV. Scaling to the N K peak (yellow) shows the increasing inten- sity of the C and O peaks as the beam energy is reduced."
+                ],
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+                "context": "The study tested EDS microanalysis at an incident beam energy of 5 keV and implemented a standards-based, k-ratio measurement protocol using the NIST DTSA-II software. The authors analyzed a broad set of reference materials suitable for microanalysis, including NIST Standard Reference Materials (SRMs), certified reference materials (CRMs), reagent compounds, stoichiometric binary compounds, and well-characterized minerals. The NIST SRMs listed explicitly include SRM 470 K411 glass (composition O-Mg-Si-Ca-Fe) and SRM 470 K412 glass (composition O-Mg-Al-Si-Ca-Fe), along with other SRMs (e.g., SRM 479 stainless steel, SRM 481/482 metal alloys, SRM 1871\u20131875 series glasses). Reagent and stoichiometric compounds and mineral standards were also used as challenge specimens. From the excerpt, SRM 470 K411 and SRM 470 K412 are the explicit glass standards containing Mg, Si (K411) and Mg, Al, Si (K412), and these materials were included among the standards used in the 5 keV analyses.",
+                "question": "What are the standards used at 5 keV in the Newbury and Ritchie 2024 study? What standards did they use for Mg, Al, Si specifically?",
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+                    "citation": "Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4.",
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+                      "Dale E. Newbury",
+                      "Nicholas W. M. Ritchie"
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+                    "publication_date": "2024-10-14T00:00:00Z",
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+                    "journal": "Journal of Materials Science",
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+                    "url": "https://doi.org/10.1007/s10853-024-10285-4",
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+                    "formatted_citation": "Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal."
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+                  "specifically at an incident beam energy of 5 keV",
+                  "Analysis followed the standards-based measurement protocol",
+                  "using the EDS analytical software NIST DTSA-II.",
+                  "SRM 470 K411 glass (O-Mg-Si-Ca-Fe)",
+                  "SRM 470 K412 glass (O-Mg-Al-Si-Ca-Fe)",
+                  "SRM 479 (Fe-Cr-Ni Stainless Steel)",
+                  "SRM 481, Gold-Silver alloys (nominal 20, 40, 60, and 80 weight percent)",
+                  "SRM 482, Gold-Copper alloys (nominal 20, 40, 60, and 80 weight percent)",
+                  "SRM 1871 K456 glass (O-Si-Pb)",
+                  "SRM 1872 K453 glass (O-Ge-Pb)",
+                  "SRM 1873 K458 glass (O-Si-Zn-Ba)",
+                  "SRM 1875 K496 glass (O-Mg-Al-P)",
+                  "Fe3C (CRM BCR-726)",
+                  "Reagent compounds, e.g., \u200bBaTiO3, PbS, \u200bMoS2",
+                  "Stoichiometric binary compounds, e.g., TiN, \u200bTiO2, \u200bCr2N",
+                  "Minerals of known composition and micro-homogeneity, e.g., albite, arsenopyrite, calcite, chalcopyrite, cinnabar, cryolite, dolomite, fluorapatite, galena, jadeite, kyanite, hematite, magnetite, pyrite, rhodonite, scheelite, willemite, wollastonite, zircon"
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+                "context": "From Newbury & Ritchie (2018, NIST DTSA\u2011II examples): EDS quantitative results include raw totals, RDEV, \u03c3 (seven replicates) and relative \u03c3, and decomposed uncertainties (k, A\u2011factor, Z\u2011factor) with a combined uncertainty. Examples (E0 = 10 keV): for SrWO4 mean raw total = \"1.0017\"; O = 0.6660, Sr = 0.1678, W = 0.1661; single\u2011analysis mass: O = 0.1913 (ideal 0.1908), Sr = 0.2627 (ideal 0.2612), W = 0.5489 (ideal 0.5480). Reported k uncertainties: Sr 0.0007 (0.27%), A\u2011factor Sr 0.0093 (3.5%), Z\u2011factor Sr 2.7\u00d710\u22125 (0.01%); combined Sr uncertainty 0.0093 (3.5%). The text stresses iterative peak fitting: \"After each round of peak fitting, the residual spectrum is inspected...\"",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                "context": "The excerpt notes: EDS detectors may be on a retractable arm so the analyst can choose r (distance) and that the Faraday-cup aperture at center collects the total incident beam current. For SDDs it recommends choosing beam current so the dead\u2011time on the most highly excited standard is <10% (classic Si(Li) practice: \u226430%). It shows OCR vs ICR for arrays (e.g. four 10\u2011mm2 detectors; 30 mm2 SDD) and spectra (NIST SRM470/K412 at E0=20 keV; dead\u2011time 3% and 29%). \u201cDead\u2011time (%) = [(ICR \u2212 OCR)/ICR]*100.\u201d \u201cOnce the analytical conditions (...) have been chosen, these conditions should be used for all standards and unknowns.\u201d",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                "context": "- The excerpt gives the k\u2011ratio error metric: \"RDEV = ((Analyzed value \u2212 expected value) / expected value) \u00d7 100%\".  \n- Example SDD\u2011EDS analyses (E0=20 keV, dead\u2011time \u224810%) show integrated counts: FeS 7,048,000; FeS2 7,765,000; at 10 keV: 5,630,000 and 6,253,000.  \n- Reported corrections and results: Cav (atom frac) ~0.50/0.50 (FeS) or 0.67/0.33 (FeS2); Z\u2011, A\u2011, F\u2011factors near unity (e.g. A=1.118\u21921.041, Z\u22480.95\u21920.97, F\u22481.001\u20131.003).  \n- Precision: \u03c3Rel \u22480.11\u20130.15%; RDEV typically \u22641%. Counting errors, A\u2011factor and Z\u2011factor contributions are reported numerically (counting error ~2\u00d710\u22124; A\u2011factor error ~1.7\u00d710\u22123; Z\u2011factor errors reported to ~10\u22125).  \n- DTSA\u2011II \"includes for each analyzed element the ZAF factors and the estimated uncertainties\" and notes \"Reducing the uncertainty due to the counting statistics requires increasing the dose.\"  \n- Fig.20.4 demonstrates raw and residual spectra after peak\u2011fitting, illustrating peak fitting residuals used in DTSA\u2011II analyses.",
+                "question": "I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
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+                    "citation": "Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20.",
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+                    "authors": [
+                      "Joseph I. Goldstein",
+                      "Dale E. Newbury",
+                      "Joseph R. Michael",
+                      "Nicholas W. M. Ritchie",
+                      "John Henry J. Scott",
+                      "David C. Joy"
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+                    "publication_date": "2017-11-18T00:00:00Z",
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+                    "pages": "309-339",
+                    "journal": "ArXiv",
+                    "publisher": "Springer New York",
+                    "url": "https://doi.org/10.1007/978-1-4939-6676-9_20",
+                    "title": "Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step",
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+                    "formatted_citation": "Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations."
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+            "references": "1. (newbury2015performingelementalmicroanalysis pages 1-2): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n2. (newbury2015performingelementalmicroanalysis pages 11-13): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n3. (goldstein2018energydispersivexray pages 14-15): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n4. (goldstein2018quantitativeanalysisthe pages 6-8): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n5. (newbury2015performingelementalmicroanalysis pages 2-4): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n6. (tsuji2010xrayspectrometry. pages 9-10): Kouichi Tsuji, Kazuhiko Nakano, Yoshio Takahashi, Kouichi Hayashi, and Chul-Un Ro. X-ray spectrometry. Analytical chemistry, 82 12:4950-87, May 2010. URL: https://doi.org/10.1021/ac101069d, doi:10.1021/ac101069d. This article has 78 citations and is from a highest quality peer-reviewed journal.\n\n7. (goldstein2018energydispersivexray pages 15-16): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n8. (goldstein2018energydispersivexray pages 18-20): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n9. (newbury2019electronexcitedxraymicroanalysis pages 2-3): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n10. (newbury2015performingelementalmicroanalysis pages 9-11): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n11. (goldstein2018quantitativeanalysisthe pages 1-4): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n12. (dumit2025challengesandfuture pages 9-10): Ver\u00f3nica I. Dumit, Irini Furxhi, Penny Nymark, Antreas Afantitis, Ammar Ammar, Monica J. B. Amorim, Dalila Antunes, Svetlana Avramova, Chiara L. Battistelli, Gianpietro Basei, Cecilia Bossa, Emil Cimpan, Mihaela Roxana Cimpan, Dmitri Ciornii, Anna Costa, Camilla Delpivo, Maria Dusinska, Ana Sofia Fonseca, Steffi Friedrichs, Vasile\u2010Dan Hodoroaba, Danail Hristozov, Panagiotis Isigonis, Nina Jeliazkova, Nikolay Kochev, Eva Kranjc, Dieter Maier, Georgia Melagraki, Anastasios G. Papadiamantis, Tomasz Puzyn, Hubert Rauscher, Katie Reilly, Araceli S\u00e1nchez Jim\u00e9nez, Janeck J. Scott\u2010Fordsmand, Neeraj Shandilya, Hyun Kil Shin, Gergana Tancheva, Jeaphianne P. M. van Rijn, Egon L. Willighagen, Ewelina Wyrzykowska, Martine I. Bakker, Damjana Drobne, Thomas E. Exner, Martin Himly, and Iseult Lynch. Challenges and future directions in assessing the quality and completeness of advanced materials safety data for re\u2010usability: a position paper from the nanosafety community. Advanced Sustainable Systems, Dec 2026. URL: https://doi.org/10.1002/adsu.202500567, doi:10.1002/adsu.202500567. This article has 2 citations and is from a peer-reviewed journal.\n\n13. (goldstein2018energydispersivexray pages 16-18): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n14. (newbury2015performingelementalmicroanalysis pages 20-21): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n15. (ritchie2018exploringthelimits pages 1-4): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\n16. (tong2026measurementuncertaintiesof pages 8-11): V. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.\n\n17. (goldstein2018energydispersivexray pages 1-2): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n18. (newbury2011isscanningelectron pages 13-16): Dale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\n19. (giunto2025harnessingautomatedsemeds pages 4-6): Andrea Giunto, Yuxing Fei, Pragnay Nevatia, Bernardus Rendy, Nathan Szymanski, and Gerbrand Ceder. Harnessing automated sem-eds and machine learning to unlock high-throughput compositional characterization of powder materials. Unknown journal, Oct 2025. URL: https://doi.org/10.21203/rs.3.rs-7837297/v1, doi:10.21203/rs.3.rs-7837297/v1.\n\n20. (newbury2015performingelementalmicroanalysis pages 17-20): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n21. (newbury2019electronexcitedxraymicroanalysis pages 5-6): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n22. (newbury2024testingtheaccuracy pages 1-3): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n23. (newbury2024testingtheaccuracy pages 22-24): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n24. (newbury2019electronexcitedxraymicroanalysis pages 13-15): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n25. (ritchie2018exploringthelimits pages 4-5): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\n26. (newbury2015performingelementalmicroanalysis pages 7-9): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n27. (newbury2019electronexcitedxraymicroanalysis pages 16-18): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n28. (newbury2024testingtheaccuracy pages 14-16): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n29. (newbury2024testingtheaccuracy pages 16-18): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n30. (newbury2024testingtheaccuracy pages 18-22): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n31. (newbury2024testingtheaccuracy pages 4-6): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.",
+            "formatted_answer": "Question: I am doing quantitative SEM-EDS (EDAX Octane Plus silicon drift detector on a Thermo Fisher Apreo SEM) on a laser-powder-bed-fusion AlSi10Mg aluminium alloy at 5 kV accelerating voltage, and I want to move from standardless quantification to standards-based k-ratio quantification using NIST DTSA-II. My measured Mg is ~0.9-1.6 wt% against a specification of 0.20-0.45 wt%, and the dominant suspected error is the Al Ka (1.487 keV) peak tail and detector response under the trace Mg Ka peak (1.254 keV).\n\nPlease answer the following, with citations to primary literature, standards documents, vendor/instrument documentation, and named data repositories:\n\n1. WHAT IS AN EDS STANDARD SPECTRUM, INFORMATIONALLY? Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.\n\n# Standards-Based k-Ratio Quantification for Low-kV SEM-EDS of AlSi10Mg: A Comprehensive Technical Guide\n\n## 1. What Is an EDS Standard Spectrum, Informationally?\n\nAn EDS standard spectrum is far more than an array of channel counts. For it to be usable in standards-based k-ratio quantification, a standard spectrum must be accompanied by a comprehensive set of metadata that documents the exact conditions under which it was acquired, so that the fundamental ratio k = I_unknown / I_standard is meaningful. The k-ratio protocol requires that unknown and standard be measured \"under identical conditions of beam energy, known dose, and detector efficiency\" (newbury2015performingelementalmicroanalysis pages 1-2). Specifically, the following metadata must be recorded and archived with each standard spectrum:\n\n**Instrumental parameters:** beam energy (accelerating voltage), probe current (measured with a Faraday cup and digital picoammeter for rigorous work), live time and real time (to calculate effective dose and dead time), and the EDS detector's process time/time constant (which must remain fixed\u2014adaptive process time is explicitly discouraged for standards-based work) (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 14-15). The dead time should be kept below approximately 10% to minimize coincidence artifacts, which grow significantly above ~15% dead time (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 6-8).\n\n**Geometric parameters:** detector elevation (take-off) angle, detector azimuthal angle, specimen tilt (preferably zero), detector-to-specimen distance (which sets the solid angle), and the detector active area (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4).\n\n**Detector characterization:** window type and thickness (polymer/Moxtek AP3/AP5 vs. Be vs. windowless), support grid geometry and open area fraction (typically 76\u201380%), detector dead layer thickness, energy resolution (FWHM at Mn K\u03b1, typically 122\u2013150 eV for modern SDDs), and the energy calibration (zero offset and gain, typically 5 eV/channel) (tsuji2010xrayspectrometry. pages 9-10, goldstein2018energydispersivexray pages 14-15, goldstein2018energydispersivexray pages 15-16, goldstein2018energydispersivexray pages 18-20).\n\n**Standard material parameters:** the identity and known composition of the standard (whether certified by an independent method), its microscopic homogeneity (confirmed by EPMA), and its certification traceability (e.g., NIST SRM certificate) (newbury2019electronexcitedxraymicroanalysis pages 2-3). When pure elements are incompatible with vacuum or suffer oxidation/beam damage, stoichiometric compounds are substituted\u2014e.g., MgO for Mg, KCl for K and Cl, FeS\u2082 for S, GaP for Ga and P, CaF\u2082 for Ca and F (newbury2015performingelementalmicroanalysis pages 1-2).\n\n**Sample condition parameters:** surface preparation state (highly polished, not chemically etched; surface roughness <50 nm rms for measurements of photons below 1 keV), coating material and thickness (typically ~8\u201310 nm carbon), and contamination/oxidation/tarnish state (newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 9-11, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4).\n\n**Administrative parameters:** date and time of acquisition, operator, and instrument identifier (newbury2015performingelementalmicroanalysis pages 11-13).\n\n**The EMSA/MAS .msa format (ISO 22029)** is the standardized spectrum data file format for microbeam analysis, originally defined by Fiori, Swyt, and others and adopted as ISO 22029 \"Microbeam Analysis \u2013 EMSA/MAS Standard File Format for Spectral-Data Exchange\" (dumit2025challengesandfuture pages 9-10). Its required keywords include `#FORMAT`, `#VERSION`, `#TITLE`, `#DATE`, `#TIME`, `#OWNER`, `#NPOINTS`, `#NCOLUMNS`, `#XUNITS`, `#YUNITS`, `#DATATYPE`, `#XPERCHAN`, `#OFFSET`, `#SIGNALTYPE`, and `#SPECTRUM`. Optional but analytically critical keywords include `#BEAMKV`, `#PROBECUR`, `#LIVETIME`, `#REALTIME`, `#ELEVANGLE`, `#AZIMANGLE`, and `#XTILTSTGE`/`#YTILTSTGE`. Notably, the classic EMSA/MAS keyword set does not include dedicated fields for detector window type, dead layer thickness, incomplete charge collection parameters, or FWHM at Mn K\u03b1\u2014these must be recorded in comment fields or external documentation. Scott, Wight, and Thorne (2002, Microsc. Microanal. 8:646\u2013647) proposed extending the format to XML-based \"EMSA/MAS 2.0,\" but the original ASCII format remains dominant.\n\nThe following table summarizes the complete metadata requirements:\n\n| Metadata Parameter | Description/Purpose | EMSA/MAS Keyword (where applicable) |\n|---|---|---|\n| Beam energy / accelerating voltage | Required because k-ratios are valid only when unknown and standard are measured under the same excitation conditions; changes ionization cross-sections, overvoltage, depth of generation, and matrix corrections. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 1-2, goldstein2018quantitativeanalysisthe pages 1-4) | `#BEAMKV` |\n| Probe current | Needed to document electron dose and to verify reproducibility/linearity of X-ray intensity; rigorous k-ratio work should measure current with a Faraday cup/picoammeter. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 18-20, goldstein2018quantitativeanalysisthe pages 6-8) | `#PROBECUR` |\n| Live time | Dose in EDS is probe current \u00d7 live time; live time, not real time, determines effective dose because dead time removes useful counts. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 16-18, goldstein2018energydispersivexray pages 18-20) | `#LIVETIME` |\n| Real time / dead time | Important to assess pulse pile-up/coincidence and detector operating regime; Newbury & Ritchie recommend conservative operation around ~10% dead time for standards-based work, especially when weak peaks sit near coincidence/tail artifacts. (newbury2015performingelementalmicroanalysis pages 20-21, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 18-20, goldstein2018quantitativeanalysisthe pages 6-8) | `#REALTIME`, `#DEADTIME` |\n| Detector elevation / take-off angle | Required geometric parameter for absorption correction; should match between unknown and standard and be verified physically if necessary. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, goldstein2018energydispersivexray pages 14-15) | often `#ELEVANGLE` or vendor-specific |\n| Detector azimuth angle | Needed because detector orientation changes X-ray path length and effective efficiency; should be fixed and recorded for reusable standards. (newbury2015performingelementalmicroanalysis pages 11-13) | often vendor-specific / not always standardized |\n| Specimen tilt | Changes take-off geometry and absorption; Goldstein/Newbury specify tilt should be controlled, preferably zero for bulk standards unless intentionally used. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4) | often `#XTILTSTGE`, `#YTILTSTGE` or vendor-specific |\n| Detector-to-specimen distance / working distance | Sets solid angle and count rate; must be reproducible between standard and unknown. Off-axis position also changes apparent low-energy efficiency because of window-grid/trap shadowing. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, goldstein2018energydispersivexray pages 15-16) | often `#WORKING`, `#DISTANCE` or vendor-specific |\n| Detector active area / solid angle | Needed to interpret count rate and portability of archived spectra; different detector geometries change throughput and sensitivity. (newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 9-11) | usually not in classic MSA core keywords; vendor-specific |\n| Detector window type and thickness | Critical below ~2 keV because polymer/SiN vs Be windows transmit low-energy X-rays very differently; affects Mg K, Al K, O K, etc. (tsuji2010xrayspectrometry. pages 9-10, ritchie2018exploringthelimits pages 1-4, tong2026measurementuncertaintiesof pages 8-11, goldstein2018energydispersivexray pages 15-16) | usually vendor-specific / not a required classic MSA keyword |\n| Window support grid / electron trap details | Off-axis shadowing and low-energy attenuation can change intensity and background, especially for light elements. (goldstein2018energydispersivexray pages 15-16) | vendor-specific |\n| Detector dead layer / front contact / Si absorption characteristics | Needed when comparing detectors or simulating spectra because fluorescence in dead layer, escape peaks, and efficiency roll-off alter low-energy response. (tsuji2010xrayspectrometry. pages 9-10, goldstein2018energydispersivexray pages 1-2) | vendor-specific |\n| Detector response function / incomplete charge collection behavior | Essential for fitting trace peaks under tails; low-energy tailing and peak-shape differences are detector-specific and limit transferability of standard spectra. (tsuji2010xrayspectrometry. pages 9-10, newbury2011isscanningelectron pages 13-16, giunto2025harnessingautomatedsemeds pages 4-6) | not represented in classic MSA keyword set |\n| Energy calibration zero offset | Required so standard and unknown spectra align channel-for-channel for integrated-peak k-ratios and peak fitting. (goldstein2018quantitativeanalysisthe pages 1-4, goldstein2018energydispersivexray pages 18-20) | `#OFFSET` |\n| Energy calibration gain / channel width | Required to define energy-per-channel; Goldstein recommends fixed channel width (e.g., 5 eV/channel) and consistent calibration. (goldstein2018quantitativeanalysisthe pages 1-4, goldstein2018energydispersivexray pages 18-20) | `#XPERCHAN`, sometimes paired with `#OFFSET` |\n| Number of channels / energy range | Needed to reconstruct spectrum and assure same fitting range; spectra should span low-energy region through the Duane\u2013Hunt limit. (goldstein2018quantitativeanalysisthe pages 1-4, goldstein2018energydispersivexray pages 18-20) | `#NPOINTS`, `#XUNITS` |\n| Energy resolution / FWHM at Mn K\u03b1 | Peak overlap sensitivity depends on detector resolution; should be documented because different FWHM values change deconvolution and low-energy tail contributions. (goldstein2018energydispersivexray pages 14-15, ritchie2018exploringthelimits pages 1-4, goldstein2018energydispersivexray pages 1-2) | often `#MNFWHM` or vendor-specific |\n| Process time / shaping time / time constant | Must be fixed; adaptive process time is specifically discouraged for standards-based quantification because it changes peak shape and resolution. (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018energydispersivexray pages 14-15) | often `#TIMECNST` or vendor-specific |\n| Count total / integrated counts | High-count spectra are needed for robust MLLS fitting and trace-level overlap correction; archive the total counts or dose associated with the standard. (newbury2015performingelementalmicroanalysis pages 20-21, newbury2015performingelementalmicroanalysis pages 11-13, newbury2015performingelementalmicroanalysis pages 17-20) | `#DATATYPE` with counts array; total counts often derived or vendor-specific |\n| Standard identity | The material used as the standard must be named explicitly so composition, homogeneity, and suitability can be checked. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2, newbury2019electronexcitedxraymicroanalysis pages 5-6, newbury2024testingtheaccuracy pages 1-3) | `#SAMPLE` |\n| Standard composition | Required because k-ratio denominator must correspond to a known concentration in the standard. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2, newbury2019electronexcitedxraymicroanalysis pages 5-6, newbury2024testingtheaccuracy pages 1-3) | no single core keyword; usually comment/header text |\n| Certification / traceability | For rigorous work, the standard composition should be certified or independently established and microscopically homogeneous. (newbury2015performingelementalmicroanalysis pages 2-4, newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2024testingtheaccuracy pages 1-3) | usually comment/header text |\n| Date/time of acquisition | Needed for traceability, detector stability checks, and QA of archived reusable standards. (newbury2015performingelementalmicroanalysis pages 11-13) | `#DATE`, `#TIME` |\n| Operator / instrument identifier | Supports QA and cross-checking of archived standards; important when spectra are reused. (newbury2015performingelementalmicroanalysis pages 11-13) | `#OWNER`, `#TITLE`, vendor-specific instrument fields |\n| Specimen surface preparation state | Surface roughness/topography directly affects low-energy X-rays; for photons below ~1 keV surfaces should be extremely flat, and standards/unknowns should be prepared similarly. (newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4) | usually comment/header text |\n| Coating material and thickness | Carbon or metal coatings absorb low-energy X-rays; mismatch between standard and unknown coatings can cause significant error at low kV. (newbury2015performingelementalmicroanalysis pages 9-11, newbury2015performingelementalmicroanalysis pages 11-13, newbury2024testingtheaccuracy pages 22-24) | usually comment/header text |\n| Contamination / oxidation / tarnish state | Surface films create composite specimens and strongly bias low-energy analysis; should be documented, especially for reactive standards like Mg-bearing materials. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2024testingtheaccuracy pages 22-24) | usually comment/header text |\n| Vacuum / chamber conditions | Useful for assessing contamination growth and detector performance stability during acquisition. (newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2024testingtheaccuracy pages 22-24) | vendor-specific |\n| Peak-family / line selection used for quantification | EDS often quantifies whole line families rather than a single line; the selected family must be known to interpret k-ratios and matrix corrections. (newbury2015performingelementalmicroanalysis pages 1-2, ritchie2018exploringthelimits pages 4-5) | usually analysis metadata, not core MSA |\n| Background/fit model or peak-shape reference linkage | Particularly valuable for trace-overlap cases, because usability of a stored standard also depends on the associated peak-shape references and fitting strategy. (ritchie2018exploringthelimits pages 4-5, newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9) | not in classic MSA core; DTSA-II/project metadata |\n| QA status / same-conditions verification | Archived standards are reusable only if a QA protocol confirms the unknown was measured under the same beam energy, dose, and EDS parameters. (newbury2015performingelementalmicroanalysis pages 11-13) | not a classic MSA keyword; external QA record |\n\n\n*Table: This table summarizes the metadata that must accompany an EDS standard spectrum for rigorous standards-based k-ratio quantification. It combines the practical requirements emphasized by Goldstein/Newbury/Ritchie with the fields typically represented in the EMSA/MAS .msa format and notes where classic MSA keywords are incomplete for modern detector-response details.*\n\n## 2. Are Standard Spectra Transferable Between Instruments?\n\n**The short answer is: generally no, not without significant correction, especially for low-energy lines below ~2 keV.**\n\nThe fundamental problem is that the k-ratio protocol requires that unknown and standard spectra be acquired under identical conditions. The stability of modern SDD-EDS detectors permits reuse of previously measured, stored standard spectra on the *same* instrument, provided a quality-assurance protocol confirms that the unknown was measured under the same documented conditions (beam energy, dose, and EDS parameters) (newbury2015performingelementalmicroanalysis pages 11-13). SDDs show nearly constant resolution and calibration across a wide range of input count rates, which enables practical spectrum archiving on a given instrument (newbury2015performingelementalmicroanalysis pages 9-11).\n\nHowever, cross-instrument transfer faces several detector-specific barriers:\n\n**Resolution differences:** Different SDDs have different FWHM values (typically 122\u2013150 eV at Mn K\u03b1), which change peak shapes and the extent of tails under adjacent peaks\u2014directly relevant to the Al K\u03b1 tail under Mg K\u03b1 in your case (ritchie2018exploringthelimits pages 1-4, goldstein2018energydispersivexray pages 1-2, goldstein2018energydispersivexray pages 14-15).\n\n**Window transmission:** The choice of window material (polymer/SiN vs. Be vs. windowless) dramatically affects transmission below ~2 keV. Moxtek AP3 and AP5 windows have different thicknesses (380 \u00b5m vs. 265 \u00b5m ribs), rib widths, and acceptance angles, creating different low-energy efficiencies (goldstein2018energydispersivexray pages 15-16). Be windows absorb essentially all X-rays below ~1 keV, making spectra taken with Be-window detectors incomparable to those from polymer-window detectors for light-element lines (tong2026measurementuncertaintiesof pages 8-11).\n\n**Silicon dead layer and incomplete charge collection (ICC):** Scholze and Procop modeled the EDS spectral response accounting for statistical and electronic noise, ICC (which causes peak tailing on the low-energy side), escape effects, and fluorescence from the front contact/dead layer (tsuji2010xrayspectrometry. pages 9-10). These processes are detector-specific and alter both peak shapes and the continuum particularly at low energies. The ICC tailing is the precise artifact creating your Al K\u03b1 tail under Mg K\u03b1.\n\n**Published \"standards transfer\" methodologies:** Newbury and Ritchie describe a \"remote standards standardless\" approach in which a library of standard measurements made on another instrument supplies standard intensities, with calculated corrections applied for beam energy and spectrometer efficiency differences. However, they note that no dose calibration is attempted in this approach, so the raw analytical total has no validity and normalization is required\u2014thereby removing important diagnostic indicators of geometric or other deviations (newbury2011isscanningelectron pages 13-16). Newbury and Ritchie (2019) also reference a \"golden detector\" calibration-transfer technique (from Alvisi et al., 2006), in which a detector calibrated at a synchrotron beamline is used with a carefully chosen reference material to transfer the calibration to other instruments\u2014an approach they note is inherently more accurate than purely first-principles standardless methods (newbury2019electronexcitedxraymicroanalysis pages 16-18).\n\n**Quantitative accuracy penalty:** When comparing measured and DTSA-II simulated spectra for bulk K411 at 20 keV (a surrogate for cross-instrument transfer using a modeled detector response), Newbury and Ritchie found discrepancies ranging from +1.2% for Fe K\u03b1 to +19% for Mg K, with the low-energy region showing systematically larger deviations (newbury2011isscanningelectron pages 13-16). This +19% discrepancy for Mg K specifically underscores the severity of the problem for your Mg K\u03b1 / Al K\u03b1 overlap situation.\n\n**Practical recommendation:** For your specific case (trace Mg K\u03b1 at 1.254 keV under the tail of the dominant Al K\u03b1 at 1.487 keV), standard spectra should be acquired on your own EDAX Octane Plus SDD on your Apreo SEM under the same conditions as your unknowns. Cross-instrument transfer of standards is not recommended for this challenging low-energy overlap problem.\n\n## 3. Simulated / Synthetic Standards\n\nNIST DTSA-II includes built-in spectrum simulation tools (based on NISTMonte, a Monte Carlo electron trajectory simulator) that can generate synthetic standard spectra from first-principles physics to yield absolute intensities (newbury2011isscanningelectron pages 13-16). The simulation models electron scattering, X-ray generation, self-absorption, secondary fluorescence, and the detector response function.\n\n**Published accuracy assessments:**\n\nWhen Newbury and Ritchie (2015) used DTSA-II simulated standards to analyze NIST microanalysis glass K2496 at 10 keV, the resulting concentrations were very close to the as-synthesized values, with RDEV values of approximately \u22121.0% to +1.7% for the constituent elements and precision metrics of ~0.08\u20131.8% relative (newbury2015performingelementalmicroanalysis pages 20-21). This demonstrates that simulated standards can provide accurate quantification for moderate-to-high-energy X-ray lines in well-controlled measurements.\n\nHowever, for bulk K411 at 20 keV, a direct comparison of measured and simulated spectra (without scaling) showed discrepancies of +1.2% for Fe K\u03b1 up to +19% for Mg K (newbury2011isscanningelectron pages 13-16). The systematically larger error at low photon energies (Mg K at 1.254 keV) reflects the difficulty of accurately modeling the detector response\u2014particularly ICC, dead layer absorption, and window transmission effects\u2014in the sub-2 keV energy range.\n\n**Where simulated standards are acceptable:** Simulated standards are most useful when a flat, bulk reference of the desired composition is unavailable\u2014for example, when analyzing irregularly shaped particles or microstructural features. DTSA-II can simulate a bulk reference spectrum from an estimated composition, with a first normalized analysis serving as that estimate (newbury2011isscanningelectron pages 13-16). For higher-energy lines (>2 keV) and well-characterized detector parameters, simulated standards can approach the accuracy of measured standards.\n\n**Where simulated standards specifically fail:** The simulation's accuracy critically depends on the fidelity of the detector response model. Key failure modes include:\n- **Low-energy peak tailing and ICC:** The incomplete charge collection process, which creates low-energy tails on peaks, is detector-specific and difficult to parameterize accurately from first principles. Giunto et al. (2025) note that detector artifacts \"particularly below 2 keV\" complicate background fitting and quantification (giunto2025harnessingautomatedsemeds pages 4-6).\n- **Contamination layers and surface effects:** Real specimens accumulate carbon contamination and may have oxidation layers; these are not included in the simulation but strongly affect low-energy X-ray intensities (newbury2024testingtheaccuracy pages 22-24).\n- **Absorption edge structure:** The continuum under characteristic peaks contains absorption edge structures that are broadened by the detector function; at higher beam energies, the peak fitting residuals show non-physical zero-intensity regions, indicating modeling limitations (newbury2024testingtheaccuracy pages 22-24).\n\n**For your specific case:** A simulated Al standard would not accurately reproduce the ICC tail that extends from Al K\u03b1 into the Mg K\u03b1 region on your specific Octane Plus detector. This tail is the dominant suspected source of your Mg over-estimation, and it is highly detector-specific. A measured Al standard acquired on your own detector is essential to characterize this tail empirically.\n\n## 4. Where to Obtain Physical Standards for Al, Si, and Mg\n\nThe following table provides a comprehensive listing of standards suppliers and CRMs relevant to your Al-Si-Mg system:\n\n| Supplier/Source | Product/CRM | Catalogue/SRM Number | Elements/Composition | Notes |\n|---|---|---|---|---|\n| NIST | Glass for microanalysis, K411 | SRM 470 K411 | O-Mg-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; useful as a multi-element glass containing Mg and Si. (newbury2024testingtheaccuracy pages 1-3) |\n| NIST | Glass for microanalysis, K412 | SRM 470 K412 | O-Mg-Al-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; directly relevant to Al-Mg-Si calibration and overlap studies. (newbury2024testingtheaccuracy pages 1-3) |\n| NIST | Gold-silver alloy set | SRM 481 | Au-Ag alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study as a certified alloy series suitable for microanalysis challenge specimens and standards work. (newbury2024testingtheaccuracy pages 1-3) |\n| NIST | Gold-copper alloy set | SRM 482 | Au-Cu alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study; Newbury & Ritchie also discuss spectra of SRM 482 at multiple beam energies. (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 22-24) |\n| NIST | Stainless steel CRM | SRM 479 | Fe-Cr-Ni stainless steel | Explicitly listed in the 5 kV study among NIST microanalysis challenge materials. (newbury2024testingtheaccuracy pages 1-3) |\n| NIST | Transformer steel CRM | SRM 483 | Fe-3Si steel | Mentioned by Newbury & Ritchie 2019 as an EPMA/EDS reference material in quantitative work. (newbury2019electronexcitedxraymicroanalysis pages 5-6) |\n| NIST | Thin-film microanalysis SRM | SRM 2063a | Thin film; composition not verified here | Relevant NIST microanalysis SRM class, but exact composition/details were not verified in the retrieved sources; include only after checking the current NIST certificate. |\n| NIST | K-glass / oxide glass series | SRM 1871, 1872, 1873, 1875 | SRM 1871 K456: O-Si-Pb; SRM 1872 K453: O-Ge-Pb; SRM 1873 K458: O-Si-Zn-Ba; SRM 1875 K496: O-Mg-Al-P | Explicitly listed in the 5 kV study as microanalysis-qualified SRMs. SRM 1875 is especially relevant because it contains Mg and Al. (newbury2024testingtheaccuracy pages 1-3) |\n| Geller MicroAnalytical Laboratory (Topsfield, MA, USA) | Stoichiometric binary compounds prepared for microanalysis | Vendor product line; specific catalogue IDs not verified here | MgO, Al2O3, SiO2, TiN, TiO2, Cr2N, etc. | Explicitly named by Newbury & Ritchie 2024 as a source of stoichiometric compounds with surfaces prepared for microanalysis. Recommended route for MgO, Al2O3, SiO2 standards. (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 14-16) |\n| SPI Supplies (West Chester, PA, USA) | Mineral standards / well-characterized minerals | Vendor product line; specific catalogue IDs not verified here | Minerals such as calcite, dolomite, fluorapatite, wollastonite, zircon; user-requested examples periclase/forsterite/spinel should be checked in current catalog | Explicitly named by Newbury & Ritchie 2024 as a source of minerals of known composition and micro-homogeneity used in the challenge set. (newbury2024testingtheaccuracy pages 1-3) |\n| Astimex Standards Ltd (Toronto, Canada) | Mounted pure-element and compound microanalysis standards | Vendor product line; specific catalogue IDs not verified here | Pure Al, Si, alloys, oxides, silicates, custom mounts | Common EPMA/SEM-EDS supplier, but specific products were not verified in the retrieved literature; check current catalog for Al, Si, Mg-bearing mounts before purchase. |\n| Ted Pella, Inc. | Microanalysis standards and mounts | Vendor product line; specific catalogue IDs not verified here | Pure elements, compounds, calibration mounts | Widely used supplier, but no product-specific verification in retrieved sources; confirm current catalog details. |\n| Micro-Analysis Consultants (MAC), St Ives, UK | Mineral and synthetic EPMA standards | Vendor product line; specific catalogue IDs not verified here | Silicates, oxides, sulfides, synthetic compounds | Common EPMA standards source, but exact catalog entries were not verified in retrieved sources. |\n| P&H Developments | Electron microprobe standards | Vendor product line; specific catalogue IDs not verified here | Mineral and synthetic standards | Named by user request; no product-specific verification found in retrieved sources, so verify directly with supplier. |\n| Alfa Aesar (now Thermo Fisher chemicals) | Reagent compounds | Reagent-grade products; specific catalogue IDs not verified here | BaTiO3, PbS, MoS2 and other compounds | Explicitly named by Newbury & Ritchie 2024 as source of reagent compounds used as challenge specimens; reagent grade is not automatically a microanalysis standard, so homogeneity/prep must be checked. (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 14-16) |\n| Smithsonian microbeam standards collection | Mineral reference materials | Collection-level resource; no single catalogue number | Mineral standards, including Mg-bearing silicates/carbonates depending on collection | Valuable institutional standards resource, but not documented in the retrieved contexts; verify access and material list directly with Smithsonian microbeam facility. |\n| Recommended Mg standard chemistry | MgO (periclase chemistry) | Not a single catalog number | Mg and O | Newbury & Ritchie\u2019s 5 kV study repeatedly used MgO as the Mg standard; their standards table maps Mg to MgO at 5 kV. This is the best-supported Mg standard in the retrieved sources. (newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18) |\n| Recommended Al standard chemistry | Al2O3 | Not a single catalog number | Al and O | In the 5 kV study, Al was standardized with Al2O3 in the standards table; practical if oxide standards are already in the block. (newbury2024testingtheaccuracy pages 14-16) |\n| Recommended Si standard chemistry | SiO2 or pure Si | Not a single catalog number | Si and O, or Si | The 5 kV study shows SiO2 used as a Si standard in multiple entries; Newbury & Ritchie also note that pure Si can be used among pure-element standards. (newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18) |\n| Caution on pure Mg metal | Pure Mg metal | Not recommended as first-choice standard for routine low-kV SEM-EDS | Mg metal, rapidly oxidizing surface | Not directly evaluated in the retrieved papers, but the literature retrieved strongly supports substitution with MgO; this is consistent with the practical oxidation/contamination problem for Mg metal and the repeated use of stoichiometric compounds when pure elements are unstable. (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2, newbury2024testingtheaccuracy pages 16-18) |\n\n\n*Table: This table summarizes physical standards sources and certified reference materials relevant to Al, Si, and Mg SEM-EDS/EPMA work, emphasizing items explicitly documented in the Newbury & Ritchie 2024 5 kV study. It distinguishes directly verified standards from commonly used suppliers whose current catalogue details should still be checked before procurement.*\n\n**Standards used in the Newbury & Ritchie 2024 study at 5 keV:** At E\u2080 = 5 keV, their Table 1 explicitly documents the use of **MgO** as the standard for Mg, **Al\u2082O\u2083** for Al, and **SiO\u2082** (or pure Si) for Si (newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18). Their materials sources included NIST SRMs (SRM 470 K411/K412, SRM 479, SRM 481, SRM 482, SRM 1871\u20131875 series), minerals from SPI Supplies (West Chester, PA), stoichiometric compounds from Geller MicroAnalytical Laboratory (Topsfield, MA), and reagent compounds from Alfa Aesar (newbury2024testingtheaccuracy pages 1-3).\n\n**On pure Mg metal as a standard:** Newbury and Ritchie consistently use MgO rather than pure Mg metal for their Mg standard (newbury2015performingelementalmicroanalysis pages 1-2, newbury2024testingtheaccuracy pages 14-16, newbury2024testingtheaccuracy pages 16-18). The general principle stated is that when pure elements are \"incompatible with vacuum or suffer electron-beam damage,\" stoichiometric compounds are substituted (newbury2019electronexcitedxraymicroanalysis pages 2-3, newbury2015performingelementalmicroanalysis pages 1-2). Pure Mg metal oxidizes rapidly, forming a surface MgO layer that grows under the electron beam and in ambient air; this creates a composite specimen that violates the homogeneity assumption of the k-ratio protocol. The EPMA community conventionally uses MgO (periclase), MgAl\u2082O\u2084 (spinel), Mg\u2082SiO\u2084 (forsterite), or CaMg(CO\u2083)\u2082 (dolomite) as Mg standards, with MgO being the simplest and most widely used.\n\n**Specific additional suppliers (not directly verified in the retrieved literature but well-established in the EPMA community):**\n- **Astimex Standards Ltd** (Toronto, Canada): Supplies mounted pure-element and compound standard blocks commonly used in EPMA laboratories.\n- **Micro-Analysis Consultants (MAC)** (St. Ives, UK): Supplies mineral and synthetic microanalysis standards.\n- **Ted Pella, Inc.**: Distributes microanalysis standards and specimen preparation supplies.\n- **P&H Developments**: Supplies EPMA standard materials.\n- **Smithsonian microbeam standards collection**: Curated mineral standards used by the Smithsonian Institution's microbeam facility and distributed to the community.\n\n*Note: Specific catalogue identifiers for Astimex, MAC, Ted Pella, and P&H Developments were not verified in the retrieved literature and should be confirmed with the vendors' current catalogues.*\n\n## 5. Public Repositories of EDS/EPMA Spectra\n\n**NIST DTSA-II internal standards database:** The DTSA-II software distribution (freely available from NIST at https://www.nist.gov/services-resources/software/nist-dtsa-ii) includes a built-in standards/k-ratio database. This database contains reference data for standard spectra and compositions used in the k-ratio quantification engine. However, these are primarily used as the software's internal reference framework for matrix corrections rather than as a downloadable library of measured spectra transferable to other instruments (newbury2011isscanningelectron pages 13-16, newbury2019electronexcitedxraymicroanalysis pages 16-18).\n\n**EMSA/MAS format (ISO 22029):** The standard data exchange format for microbeam analysis spectra is the EMSA/MAS .msa ASCII format, now codified as ISO 22029 (dumit2025challengesandfuture pages 9-10). This format is supported by DTSA-II and most vendor software for import/export of EDS spectra.\n\n**Key limitation on transferability of archived spectra:** Even when spectra are available in .msa format from repositories or community resources, they are generally usable only as **reference/identification spectra** (for qualitative comparison and peak identification) rather than as quantification standards on a different instrument. This is because the spectra encode the detector-specific response function (resolution, tailing, efficiency) of the instrument on which they were acquired (tsuji2010xrayspectrometry. pages 9-10, ritchie2018exploringthelimits pages 1-4, newbury2011isscanningelectron pages 13-16). Newbury and Ritchie's \"remote standards\" approach can partially address this limitation by applying corrections for spectrometer efficiency differences, but the raw analytical total loses validity and normalization is required (newbury2011isscanningelectron pages 13-16).\n\n**Other resources:**\n- **de-ma.ch web database** (Allaz, 2024, Microsc. Microanal. 30:489\u2013500): A web database for electron and X-ray microanalysis to assist lab managers and users. The detailed contents were not fully verified in the retrieved literature.\n- **NEXL** (Ritchie, 2022, Microsc. Microanal. 28:478\u2013495): Ritchie's reproducible spectrum and hyperspectrum data analysis framework using a defined data format.\n- **University of Oregon CAMCOR**: Maintains standard block documentation that can serve as a community reference but is not a downloadable spectral library.\n- **Zenodo/Figshare deposits**: Individual researchers occasionally deposit EDS datasets; these should be evaluated case-by-case for usability as quantification standards.\n\n**Practical conclusion:** No large, publicly downloadable library of measured EDS standard spectra exists that would be directly usable as quantification standards on an arbitrary instrument. The most reliable path remains acquiring your own standards on your own detector.\n\n## 6. The Specific Low-kV Case: 5 kV Mg K\u03b1 in an Al-Rich Matrix\n\n**The analytical challenge:** At 5 kV, Mg K\u03b1 (1.254 keV) and Al K\u03b1 (1.487 keV) are separated by only ~233 eV. With a typical SDD FWHM of ~55\u201365 eV at these energies, the peaks are nominally resolved, but the Al K\u03b1 peak\u2014which is enormously intense in an 84+ wt% Al matrix\u2014generates a low-energy tail due to incomplete charge collection that extends beneath the much smaller Mg K\u03b1 peak. Your measured Mg concentration (0.9\u20131.6 wt% vs. specification 0.20\u20130.45 wt%) represents a 2\u20134\u00d7 overestimate that is entirely consistent with inadequate characterization of this Al K\u03b1 low-energy tail artifact in a standardless quantification framework.\n\n**Accuracy demonstrated at 5 keV with the k-ratio protocol:** Newbury and Ritchie (2024) systematically tested accuracy at E\u2080 = 5 keV using NIST DTSA-II with the standards-based k-ratio protocol, making 263 concentration measurements for 39 elements in 113 materials. More than 98% of their results fell within \u00b15% RDEV, and 82% fell within \u00b12% RDEV (newbury2024testingtheaccuracy pages 1-3, newbury2024testingtheaccuracy pages 18-22). This demonstrates that high-accuracy quantification at 5 keV is achievable with proper standards and protocol. Their analytical platform was a JEOL 8500f with a Bruker Quad SDD array (newbury2024testingtheaccuracy pages 4-6, newbury2024testingtheaccuracy pages 1-3).\n\n**Standards selection for Al, Si, Mg at 5 keV:** In the 5 keV study, MgO was used as the Mg standard, Al\u2082O\u2083 as the Al standard, and SiO\u2082 as the Si standard (newbury2024testingtheaccuracy pages 14-16). These compound standards avoid the surface oxidation problem of pure Mg metal and provide reliable, reproducible compositions.\n\n**Practical recommendations for your measurement:**\n\n1. **Acquire a measured Al standard spectrum on your own detector.** This is the single most important step to characterize the detector-specific Al K\u03b1 low-energy tail under Mg K\u03b1. The Al standard spectrum (pure Al metal or Al\u2082O\u2083) serves as both a quantification standard and a peak-shape reference for the MLLS fitting in DTSA-II (ritchie2018exploringthelimits pages 4-5, newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9). In DTSA-II, this is accomplished by setting up a \"Standard Bundle\" that combines the standard spectrum with peak-shape references (ritchie2018exploringthelimits pages 4-5).\n\n2. **Consider acquiring a \"blank\" spectrum from pure Al** (or an Al-Si binary alloy with no Mg) specifically to characterize and subtract the Al K\u03b1 tail contribution under the Mg K\u03b1 region. This provides an empirical characterization of the ICC tailing on your specific Octane Plus detector. The peak fitting residual spectrum after fitting Al should show whether any counts remain in the Mg K\u03b1 region (newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9).\n\n3. **Collect high-count spectra.** For trace-level Mg (0.2\u20130.45 wt% is in the minor/trace boundary), long acquisition times are needed to improve counting statistics and detection limits. Detection limits scale as C_DL = [3 \u00d7 N_B^(1/2) / (N_S \u2212 N_B)] \u00d7 C_S, and practical LODs can reach ~200\u2013500 ppm with sufficient counts (newbury2019electronexcitedxraymicroanalysis pages 13-15). Total spectrum counts of 3\u201310 million (0.1\u20135 keV range) were typical in the Newbury & Ritchie 5 keV study (newbury2024testingtheaccuracy pages 4-6, newbury2024testingtheaccuracy pages 1-3).\n\n4. **Use conservative dead time (~10%).** At 5 kV in an Al-rich matrix, the Al K\u03b1 peak will be extremely intense. Coincidence peaks (Al+Al at ~2.97 keV, Al+Si, etc.) become significant above ~10\u201315% dead time and can distort the continuum shape in the fitting region. Choose beam current to keep dead time below 10% on the most highly excited standard (newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 6-8).\n\n5. **Surface preparation is critical.** At 5 kV, the electron range is very short (~200\u2013300 nm in Al), so surface roughness, oxidation, and carbon contamination have a proportionally larger effect. Surface roughness should be <50 nm rms for measurements of photon energies below 1 keV, and the same preparation/coating protocol must be applied to both standards and unknowns (newbury2015performingelementalmicroanalysis pages 2-4, newbury2015performingelementalmicroanalysis pages 11-13, goldstein2018quantitativeanalysisthe pages 1-4). Carbon coatings should be ~8\u201310 nm and matched between standard and unknown; mismatched coating thickness introduces significant error at low beam energies (newbury2015performingelementalmicroanalysis pages 9-11).\n\n6. **Inspect the peak fitting residual spectrum.** After fitting Al and Si peaks, inspect the residual spectrum in the Mg K\u03b1 region to verify whether a genuine Mg peak remains above the fitted background, and whether the residual shows any systematic structure indicating inadequate tail modeling (newbury2015performingelementalmicroanalysis pages 17-20, newbury2015performingelementalmicroanalysis pages 7-9).\n\n7. **The raw analytical total is diagnostic.** When using the k-ratio protocol (not normalized), the raw analytical total should fall near 1.00 (typically 0.98\u20131.02 at conventional beam energies). At 5 keV, a broader range of 0.8\u20131.2 is observed even for carefully vetted materials (newbury2024testingtheaccuracy pages 18-22, newbury2024testingtheaccuracy pages 22-24). A total significantly deviating from unity signals potential problems (missing elements, surface layers, or fitting artifacts).\n\n8. **Verify with a known Mg-bearing reference material.** Analyze NIST SRM 470 K412 glass (which contains Mg, Al, Si, Ca, Fe, and O) at 5 keV to validate your Mg measurement against the certified composition before analyzing the AlSi10Mg alloy. This serves as an independent accuracy check for the specific Al-Mg overlap situation on your instrument.\n\n**Root cause of your Mg overestimate:** In standardless quantification, the vendor's built-in peak model may not accurately represent the ICC tail of Al K\u03b1 on your specific Octane Plus detector, leading to systematic misattribution of Al K\u03b1 tail counts to the Mg K\u03b1 channel. Switching to standards-based k-ratio quantification with DTSA-II, using a measured Al standard from your own detector as both standard and peak-shape reference, should dramatically reduce this systematic error by empirically capturing the actual detector response (newbury2011isscanningelectron pages 13-16, newbury2019electronexcitedxraymicroanalysis pages 16-18).\n\n\nReferences\n\n1. (newbury2015performingelementalmicroanalysis pages 1-2): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n2. (newbury2015performingelementalmicroanalysis pages 11-13): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n3. (goldstein2018energydispersivexray pages 14-15): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n4. (goldstein2018quantitativeanalysisthe pages 6-8): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n5. (newbury2015performingelementalmicroanalysis pages 2-4): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n6. (tsuji2010xrayspectrometry. pages 9-10): Kouichi Tsuji, Kazuhiko Nakano, Yoshio Takahashi, Kouichi Hayashi, and Chul-Un Ro. X-ray spectrometry. Analytical chemistry, 82 12:4950-87, May 2010. URL: https://doi.org/10.1021/ac101069d, doi:10.1021/ac101069d. This article has 78 citations and is from a highest quality peer-reviewed journal.\n\n7. (goldstein2018energydispersivexray pages 15-16): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n8. (goldstein2018energydispersivexray pages 18-20): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n9. (newbury2019electronexcitedxraymicroanalysis pages 2-3): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n10. (newbury2015performingelementalmicroanalysis pages 9-11): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n11. (goldstein2018quantitativeanalysisthe pages 1-4): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n12. (dumit2025challengesandfuture pages 9-10): Ver\u00f3nica I. Dumit, Irini Furxhi, Penny Nymark, Antreas Afantitis, Ammar Ammar, Monica J. B. Amorim, Dalila Antunes, Svetlana Avramova, Chiara L. Battistelli, Gianpietro Basei, Cecilia Bossa, Emil Cimpan, Mihaela Roxana Cimpan, Dmitri Ciornii, Anna Costa, Camilla Delpivo, Maria Dusinska, Ana Sofia Fonseca, Steffi Friedrichs, Vasile\u2010Dan Hodoroaba, Danail Hristozov, Panagiotis Isigonis, Nina Jeliazkova, Nikolay Kochev, Eva Kranjc, Dieter Maier, Georgia Melagraki, Anastasios G. Papadiamantis, Tomasz Puzyn, Hubert Rauscher, Katie Reilly, Araceli S\u00e1nchez Jim\u00e9nez, Janeck J. Scott\u2010Fordsmand, Neeraj Shandilya, Hyun Kil Shin, Gergana Tancheva, Jeaphianne P. M. van Rijn, Egon L. Willighagen, Ewelina Wyrzykowska, Martine I. Bakker, Damjana Drobne, Thomas E. Exner, Martin Himly, and Iseult Lynch. Challenges and future directions in assessing the quality and completeness of advanced materials safety data for re\u2010usability: a position paper from the nanosafety community. Advanced Sustainable Systems, Dec 2026. URL: https://doi.org/10.1002/adsu.202500567, doi:10.1002/adsu.202500567. This article has 2 citations and is from a peer-reviewed journal.\n\n13. (goldstein2018energydispersivexray pages 16-18): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n14. (newbury2015performingelementalmicroanalysis pages 20-21): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n15. (ritchie2018exploringthelimits pages 1-4): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\n16. (tong2026measurementuncertaintiesof pages 8-11): V. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.\n\n17. (goldstein2018energydispersivexray pages 1-2): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n18. (newbury2011isscanningelectron pages 13-16): Dale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\n19. (giunto2025harnessingautomatedsemeds pages 4-6): Andrea Giunto, Yuxing Fei, Pragnay Nevatia, Bernardus Rendy, Nathan Szymanski, and Gerbrand Ceder. Harnessing automated sem-eds and machine learning to unlock high-throughput compositional characterization of powder materials. Unknown journal, Oct 2025. URL: https://doi.org/10.21203/rs.3.rs-7837297/v1, doi:10.21203/rs.3.rs-7837297/v1.\n\n20. (newbury2015performingelementalmicroanalysis pages 17-20): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n21. (newbury2019electronexcitedxraymicroanalysis pages 5-6): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n22. (newbury2024testingtheaccuracy pages 1-3): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n23. (newbury2024testingtheaccuracy pages 22-24): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n24. (newbury2019electronexcitedxraymicroanalysis pages 13-15): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n25. (ritchie2018exploringthelimits pages 4-5): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\n26. (newbury2015performingelementalmicroanalysis pages 7-9): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 611 citations and is from a peer-reviewed journal.\n\n27. (newbury2019electronexcitedxraymicroanalysis pages 16-18): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n28. (newbury2024testingtheaccuracy pages 14-16): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n29. (newbury2024testingtheaccuracy pages 16-18): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n30. (newbury2024testingtheaccuracy pages 18-22): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.\n\n31. (newbury2024testingtheaccuracy pages 4-6): Dale E. Newbury and Nicholas W. M. Ritchie. Testing the accuracy of low-beam-energy electron-excited x-ray microanalysis with energy-dispersive spectrometry. Journal of Materials Science, 59:19088-19111, Oct 2024. URL: https://doi.org/10.1007/s10853-024-10285-4, doi:10.1007/s10853-024-10285-4. This article has 15 citations and is from a peer-reviewed journal.",
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+              "artifact-00": "| Metadata Parameter | Description/Purpose | EMSA/MAS Keyword (where applicable) |\n|---|---|---|\n| Beam energy / accelerating voltage | Required because k-ratios are valid only when unknown and standard are measured under the same excitation conditions; changes ionization cross-sections, overvoltage, depth of generation, and matrix corrections. (pqac-00000000, pqac-00000002, pqac-00000005, pqac-00000022) | `#BEAMKV` |\n| Probe current | Needed to document electron dose and to verify reproducibility/linearity of X-ray intensity; rigorous k-ratio work should measure current with a Faraday cup/picoammeter. (pqac-00000000, pqac-00000013, pqac-00000035, pqac-00000046) | `#PROBECUR` |\n| Live time | Dose in EDS is probe current \u00d7 live time; live time, not real time, determines effective dose because dead time removes useful counts. (pqac-00000000, pqac-00000013, pqac-00000025, pqac-00000035) | `#LIVETIME` |\n| Real time / dead time | Important to assess pulse pile-up/coincidence and detector operating regime; Newbury & Ritchie recommend conservative operation around ~10% dead time for standards-based work, especially when weak peaks sit near coincidence/tail artifacts. (pqac-00000006, pqac-00000013, pqac-00000035, pqac-00000046) | `#REALTIME`, `#DEADTIME` |\n| Detector elevation / take-off angle | Required geometric parameter for absorption correction; should match between unknown and standard and be verified physically if necessary. (pqac-00000000, pqac-00000002, pqac-00000013, pqac-00000026) | often `#ELEVANGLE` or vendor-specific |\n| Detector azimuth angle | Needed because detector orientation changes X-ray path length and effective efficiency; should be fixed and recorded for reusable standards. (pqac-00000000, pqac-00000013) | often vendor-specific / not always standardized |\n| Specimen tilt | Changes take-off geometry and absorption; Goldstein/Newbury specify tilt should be controlled, preferably zero for bulk standards unless intentionally used. (pqac-00000000, pqac-00000013, pqac-00000022) | often `#XTILTSTGE`, `#YTILTSTGE` or vendor-specific |\n| Detector-to-specimen distance / working distance | Sets solid angle and count rate; must be reproducible between standard and unknown. Off-axis position also changes apparent low-energy efficiency because of window-grid/trap shadowing. (pqac-00000000, pqac-00000002, pqac-00000027) | often `#WORKING`, `#DISTANCE` or vendor-specific |\n| Detector active area / solid angle | Needed to interpret count rate and portability of archived spectra; different detector geometries change throughput and sensitivity. (pqac-00000000, pqac-00000002, pqac-00000015) | usually not in classic MSA core keywords; vendor-specific |\n| Detector window type and thickness | Critical below ~2 keV because polymer/SiN vs Be windows transmit low-energy X-rays very differently; affects Mg K, Al K, O K, etc. (pqac-00000009, pqac-00000010, pqac-00000019, pqac-00000027) | usually vendor-specific / not a required classic MSA keyword |\n| Window support grid / electron trap details | Off-axis shadowing and low-energy attenuation can change intensity and background, especially for light elements. (pqac-00000027) | vendor-specific |\n| Detector dead layer / front contact / Si absorption characteristics | Needed when comparing detectors or simulating spectra because fluorescence in dead layer, escape peaks, and efficiency roll-off alter low-energy response. (pqac-00000009, pqac-00000011) | vendor-specific |\n| Detector response function / incomplete charge collection behavior | Essential for fitting trace peaks under tails; low-energy tailing and peak-shape differences are detector-specific and limit transferability of standard spectra. (pqac-00000009, pqac-00000012, pqac-00000037) | not represented in classic MSA keyword set |\n| Energy calibration zero offset | Required so standard and unknown spectra align channel-for-channel for integrated-peak k-ratios and peak fitting. (pqac-00000022, pqac-00000035) | `#OFFSET` |\n| Energy calibration gain / channel width | Required to define energy-per-channel; Goldstein recommends fixed channel width (e.g., 5 eV/channel) and consistent calibration. (pqac-00000022, pqac-00000035) | `#XPERCHAN`, sometimes paired with `#OFFSET` |\n| Number of channels / energy range | Needed to reconstruct spectrum and assure same fitting range; spectra should span low-energy region through the Duane\u2013Hunt limit. (pqac-00000022, pqac-00000035) | `#NPOINTS`, `#XUNITS` |\n| Energy resolution / FWHM at Mn K\u03b1 | Peak overlap sensitivity depends on detector resolution; should be documented because different FWHM values change deconvolution and low-energy tail contributions. (pqac-00000026, pqac-00000010, pqac-00000011) | often `#MNFWHM` or vendor-specific |\n| Process time / shaping time / time constant | Must be fixed; adaptive process time is specifically discouraged for standards-based quantification because it changes peak shape and resolution. (pqac-00000000, pqac-00000013, pqac-00000026) | often `#TIMECNST` or vendor-specific |\n| Count total / integrated counts | High-count spectra are needed for robust MLLS fitting and trace-level overlap correction; archive the total counts or dose associated with the standard. (pqac-00000006, pqac-00000007, pqac-00000017) | `#DATATYPE` with counts array; total counts often derived or vendor-specific |\n| Standard identity | The material used as the standard must be named explicitly so composition, homogeneity, and suitability can be checked. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | `#SAMPLE` |\n| Standard composition | Required because k-ratio denominator must correspond to a known concentration in the standard. (pqac-00000003, pqac-00000005, pqac-00000039, pqac-00000042) | no single core keyword; usually comment/header text |\n| Certification / traceability | For rigorous work, the standard composition should be certified or independently established and microscopically homogeneous. (pqac-00000002, pqac-00000003, pqac-00000042) | usually comment/header text |\n| Date/time of acquisition | Needed for traceability, detector stability checks, and QA of archived reusable standards. (pqac-00000000, pqac-00000013) | `#DATE`, `#TIME` |\n| Operator / instrument identifier | Supports QA and cross-checking of archived standards; important when spectra are reused. (pqac-00000013) | `#OWNER`, `#TITLE`, vendor-specific instrument fields |\n| Specimen surface preparation state | Surface roughness/topography directly affects low-energy X-rays; for photons below ~1 keV surfaces should be extremely flat, and standards/unknowns should be prepared similarly. (pqac-00000002, pqac-00000007, pqac-00000022) | usually comment/header text |\n| Coating material and thickness | Carbon or metal coatings absorb low-energy X-rays; mismatch between standard and unknown coatings can cause significant error at low kV. (pqac-00000004, pqac-00000007, pqac-00000034) | usually comment/header text |\n| Contamination / oxidation / tarnish state | Surface films create composite specimens and strongly bias low-energy analysis; should be documented, especially for reactive standards like Mg-bearing materials. (pqac-00000003, pqac-00000018, pqac-00000034) | usually comment/header text |\n| Vacuum / chamber conditions | Useful for assessing contamination growth and detector performance stability during acquisition. (pqac-00000018, pqac-00000034) | vendor-specific |\n| Peak-family / line selection used for quantification | EDS often quantifies whole line families rather than a single line; the selected family must be known to interpret k-ratios and matrix corrections. (pqac-00000005, pqac-00000016, pqac-00000024) | usually analysis metadata, not core MSA |\n| Background/fit model or peak-shape reference linkage | Particularly valuable for trace-overlap cases, because usability of a stored standard also depends on the associated peak-shape references and fitting strategy. (pqac-00000016, pqac-00000017, pqac-00000023) | not in classic MSA core; DTSA-II/project metadata |\n| QA status / same-conditions verification | Archived standards are reusable only if a QA protocol confirms the unknown was measured under the same beam energy, dose, and EDS parameters. (pqac-00000000, pqac-00000013) | not a classic MSA keyword; external QA record |\n\n\n*Table: This table summarizes the metadata that must accompany an EDS standard spectrum for rigorous standards-based k-ratio quantification. It combines the practical requirements emphasized by Goldstein/Newbury/Ritchie with the fields typically represented in the EMSA/MAS .msa format and notes where classic MSA keywords are incomplete for modern detector-response details.*",
+              "artifact-01": "| Supplier/Source | Product/CRM | Catalogue/SRM Number | Elements/Composition | Notes |\n|---|---|---|---|---|\n| NIST | Glass for microanalysis, K411 | SRM 470 K411 | O-Mg-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; useful as a multi-element glass containing Mg and Si. (pqac-00000031, pqac-00000042) |\n| NIST | Glass for microanalysis, K412 | SRM 470 K412 | O-Mg-Al-Si-Ca-Fe | Explicitly listed by Newbury & Ritchie as a microanalysis-qualified NIST SRM used in the 5 kV challenge set; directly relevant to Al-Mg-Si calibration and overlap studies. (pqac-00000031, pqac-00000042) |\n| NIST | Gold-silver alloy set | SRM 481 | Au-Ag alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study as a certified alloy series suitable for microanalysis challenge specimens and standards work. (pqac-00000031, pqac-00000042) |\n| NIST | Gold-copper alloy set | SRM 482 | Au-Cu alloys, nominal 20/40/60/80 wt% Au | Explicitly listed in the 5 kV study; Newbury & Ritchie also discuss spectra of SRM 482 at multiple beam energies. (pqac-00000031, pqac-00000034, pqac-00000042) |\n| NIST | Stainless steel CRM | SRM 479 | Fe-Cr-Ni stainless steel | Explicitly listed in the 5 kV study among NIST microanalysis challenge materials. (pqac-00000031, pqac-00000042) |\n| NIST | Transformer steel CRM | SRM 483 | Fe-3Si steel | Mentioned by Newbury & Ritchie 2019 as an EPMA/EDS reference material in quantitative work. (pqac-00000039) |\n| NIST | Thin-film microanalysis SRM | SRM 2063a | Thin film; composition not verified here | Relevant NIST microanalysis SRM class, but exact composition/details were not verified in the retrieved sources; include only after checking the current NIST certificate. |\n| NIST | K-glass / oxide glass series | SRM 1871, 1872, 1873, 1875 | SRM 1871 K456: O-Si-Pb; SRM 1872 K453: O-Ge-Pb; SRM 1873 K458: O-Si-Zn-Ba; SRM 1875 K496: O-Mg-Al-P | Explicitly listed in the 5 kV study as microanalysis-qualified SRMs. SRM 1875 is especially relevant because it contains Mg and Al. (pqac-00000031, pqac-00000042) |\n| Geller MicroAnalytical Laboratory (Topsfield, MA, USA) | Stoichiometric binary compounds prepared for microanalysis | Vendor product line; specific catalogue IDs not verified here | MgO, Al2O3, SiO2, TiN, TiO2, Cr2N, etc. | Explicitly named by Newbury & Ritchie 2024 as a source of stoichiometric compounds with surfaces prepared for microanalysis. Recommended route for MgO, Al2O3, SiO2 standards. (pqac-00000031, pqac-00000040) |\n| SPI Supplies (West Chester, PA, USA) | Mineral standards / well-characterized minerals | Vendor product line; specific catalogue IDs not verified here | Minerals such as calcite, dolomite, fluorapatite, wollastonite, zircon; user-requested examples periclase/forsterite/spinel should be checked in current catalog | Explicitly named by Newbury & Ritchie 2024 as a source of minerals of known composition and micro-homogeneity used in the challenge set. (pqac-00000031, pqac-00000042) |\n| Astimex Standards Ltd (Toronto, Canada) | Mounted pure-element and compound microanalysis standards | Vendor product line; specific catalogue IDs not verified here | Pure Al, Si, alloys, oxides, silicates, custom mounts | Common EPMA/SEM-EDS supplier, but specific products were not verified in the retrieved literature; check current catalog for Al, Si, Mg-bearing mounts before purchase. |\n| Ted Pella, Inc. | Microanalysis standards and mounts | Vendor product line; specific catalogue IDs not verified here | Pure elements, compounds, calibration mounts | Widely used supplier, but no product-specific verification in retrieved sources; confirm current catalog details. |\n| Micro-Analysis Consultants (MAC), St Ives, UK | Mineral and synthetic EPMA standards | Vendor product line; specific catalogue IDs not verified here | Silicates, oxides, sulfides, synthetic compounds | Common EPMA standards source, but exact catalog entries were not verified in retrieved sources. |\n| P&H Developments | Electron microprobe standards | Vendor product line; specific catalogue IDs not verified here | Mineral and synthetic standards | Named by user request; no product-specific verification found in retrieved sources, so verify directly with supplier. |\n| Alfa Aesar (now Thermo Fisher chemicals) | Reagent compounds | Reagent-grade products; specific catalogue IDs not verified here | BaTiO3, PbS, MoS2 and other compounds | Explicitly named by Newbury & Ritchie 2024 as source of reagent compounds used as challenge specimens; reagent grade is not automatically a microanalysis standard, so homogeneity/prep must be checked. (pqac-00000031, pqac-00000040) |\n| Smithsonian microbeam standards collection | Mineral reference materials | Collection-level resource; no single catalogue number | Mineral standards, including Mg-bearing silicates/carbonates depending on collection | Valuable institutional standards resource, but not documented in the retrieved contexts; verify access and material list directly with Smithsonian microbeam facility. |\n| Recommended Mg standard chemistry | MgO (periclase chemistry) | Not a single catalog number | Mg and O | Newbury & Ritchie\u2019s 5 kV study repeatedly used MgO as the Mg standard; their standards table maps Mg to MgO at 5 kV. This is the best-supported Mg standard in the retrieved sources. (pqac-00000040, pqac-00000041, pqac-00000043) |\n| Recommended Al standard chemistry | Al2O3 | Not a single catalog number | Al and O | In the 5 kV study, Al was standardized with Al2O3 in the standards table; practical if oxide standards are already in the block. (pqac-00000040, pqac-00000041) |\n| Recommended Si standard chemistry | SiO2 or pure Si | Not a single catalog number | Si and O, or Si | The 5 kV study shows SiO2 used as a Si standard in multiple entries; Newbury & Ritchie also note that pure Si can be used among pure-element standards. (pqac-00000040, pqac-00000041, pqac-00000043) |\n| Caution on pure Mg metal | Pure Mg metal | Not recommended as first-choice standard for routine low-kV SEM-EDS | Mg metal, rapidly oxidizing surface | Not directly evaluated in the retrieved papers, but the literature retrieved strongly supports substitution with MgO; this is consistent with the practical oxidation/contamination problem for Mg metal and the repeated use of stoichiometric compounds when pure elements are unstable. (pqac-00000003, pqac-00000005, pqac-00000043) |\n\n\n*Table: This table summarizes physical standards sources and certified reference materials relevant to Al, Si, and Mg SEM-EDS/EPMA work, emphasizing items explicitly documented in the Newbury & Ritchie 2024 5 kV study. It distinguishes directly verified standards from commonly used suppliers whose current catalogue details should still be checked before procurement.*"
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Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify."
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Beyond the channel counts, what specific metadata must accompany a standard spectrum for it to be usable in standards-based k-ratio quantification (e.g. beam energy, probe current, live time / probe dose, take-off angle, detector window and active-layer parameters, energy calibration zero and gain, resolution/FWHM at Mn Ka, amplifier process/shaping time, standard composition and its certification traceability, date of acquisition, contamination/coating state)? Cite the EMSA/MAS .msa / MSA-AS-1 spectrum data file format specification and its required keyword set, and Goldstein et al. \"Scanning Electron Microscopy and X-Ray Microanalysis\" (4th ed., 2018) on the requirements of standards.\n\n2. ARE STANDARD SPECTRA TRANSFERABLE BETWEEN INSTRUMENTS? What does the literature say quantitatively about whether a standard spectrum acquired on one EDS detector can be used to quantify an unknown acquired on a DIFFERENT detector or a different microscope? Specifically address detector-to-detector variation in resolution, window transmission (polymer/Moxtek vs Be), silicon dead layer, incomplete charge collection and low-energy peak tailing, and how those affect k-ratios for light elements below 2 keV. Is there any published \"standards transfer\", \"standards library portability\", or \"detector response matching\" methodology (e.g. Fiori, Newbury, Ritchie, Statham) that makes cross-instrument standard reuse valid, and what accuracy penalty is reported?\n\n3. SIMULATED / SYNTHETIC STANDARDS. What is the published accuracy of using Monte Carlo or analytical simulated standard spectra (e.g. NIST DTSA-II's simulation tools, NISTMonte) in place of measured standards for bulk quantification? Cite Ritchie's papers on DTSA-II and NISTMonte and any accuracy assessments. Under what conditions is a simulated standard acceptable, and where does it specifically fail (e.g. low-energy detector tailing, incomplete charge collection, contamination layers)?\n\n4. WHERE DO YOU OBTAIN PHYSICAL STANDARDS for Al, Si, and Mg for electron probe microanalysis? Name specific certified reference materials and suppliers with catalogue identifiers where possible: NIST Standard Reference Materials relevant to microanalysis (e.g. SRM 481, 482, 483, 470/K-glasses, 2063a thin film), Astimex Standards Ltd, SPI Supplies, Ted Pella, Micro-Analysis Consultants (MAC), Structure Probe, Geller MicroAnalytical, P&H Developments, and any national metrology institute equivalents (BAM, NMIJ, LGC). For Mg specifically: is pure Mg metal usable as a standard given its rapid oxidation, and what compound standards are conventionally substituted (MgO, periclase, dolomite, MgAl2O4 spinel, forsterite)? Cite EPMA standard practice literature (e.g. Jercinovic, Donovan, Armstrong; the Probe Software / CalcZAF documentation; Reed's \"Electron Microprobe Analysis\").\n\n5. PUBLIC REPOSITORIES OF EDS/EPMA SPECTRA. Are there any publicly downloadable libraries of measured EDS standard spectra in .msa/EMSA format? Consider: the NIST DTSA-II distribution's own included spectrum/standard database, the NIST Data Gateway, the Materials Data Repository, the EPMA listserv / Probe Software's community resources, the Smithsonian microbeam standards, the University of Oregon CAMCOR standard block documentation, the \"Microanalysis Society\" resources, Zenodo/Figshare deposits, and the \"SEM-EDS spectral database\" literature. If such repositories exist, state exactly what they contain and whether the spectra are usable as quantification standards on a different instrument or only as reference/identification spectra.\n\n6. THE SPECIFIC LOW-kV CASE. At 5 kV, quantifying ~0.3-1 wt% Mg Ka in an Al-rich (>84 wt%) matrix: what does the literature recommend for standard selection and acquisition (counts on standard, dead time, whether to use pure Al metal versus an Al alloy, whether to acquire a \"blank\" Al standard specifically to characterise the Al Ka low-energy tail under Mg Ka)? Cite work on low-voltage SEM-EDS quantification (Newbury & Ritchie's low-kV papers), on trace element detection limits in EDS, and on peak overlap / spectral tail correction for adjacent light-element lines.\n\nPrioritise concrete, actionable, verifiable facts: named products with supplier and part numbers, named files/databases with how to obtain them, and numerical accuracy figures with citations. Explicitly flag anything you cannot verify.",
+  "started_at": "2026-08-21T20:40:03.503536Z",
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+  "task_summary": "Standards-Based EDS K\u2011Ratio Quantification Workflow And Limitations For Low\u2011Voltage AlSi10Mg Analysis",
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+{
+  "task_id": "2a23935c-f686-488e-a0a6-0faada1cb90f",
+  "job_name": "LITERATURE_HIGH",
+  "submitted_at_utc": "2026-08-20T19:40:40.434641+00:00",
+  "query": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy)."
+}
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+## Derivation of Recommended Acquisition Parameters in SEM-EDS: From Physics Models to Standard Practice
+
+### 1. Overvoltage Ratio (U₀ ≈ 2–3)
+
+The recommendation to set the accelerating voltage E₀ at roughly two to three times the critical excitation energy Ec of the highest-energy line of interest (i.e., overvoltage U₀ = E₀/Ec ≈ 2–3) derives from the interplay of three physics models.
+
+**Ionization cross-section.** The Bethe (1930) formulation of the inner-shell ionization cross-section Q predicts that Q rises steeply from the threshold (U = 1), passes through a broad maximum at overvoltages of a few (typically U ≈ 2–4 depending on the shell and the specific formulation), and then decreases slowly as ln(U)/U at high overvoltages. Green and Cosslett (1961, 1968) validated this behavior experimentally by measuring K-, L-, and M-shell X-ray production efficiencies from thick pure-element targets bombarded by electrons, confirming that characteristic X-ray yield per unit beam current rises rapidly above threshold but saturates at modest overvoltages. Powell, Llovet, and Salvat (2016) later evaluated the accuracy of the Bethe equation against distorted-wave Born-approximation calculations and experiment, finding that the Bethe formula provides a useful approximation in the overvoltage range relevant to microanalysis. These studies collectively established that the marginal gain in ionization efficiency diminishes above U ≈ 2–3.
+
+**Electron range and interaction volume.** Countering the benefit of higher overvoltage, the electron range R in a solid scales approximately as E₀^1.67/ρ in the Kanaya–Okayama (1972) formulation. This means that raising E₀ expands the interaction volume roughly as R³, degrading lateral and depth spatial resolution. As Goldstein et al. (2018) note, the beam energy of 20 keV provides sufficient overvoltage (E₀/Ec > 1.5) for K-shell excitation up to Br and L-shell excitation up to Bi, with photon energies up to ~12 keV (goldstein2018quantitativeanalysisthe pages 4-6). Reducing E₀ from 20 to 10 keV substantially reduces the absorption correction factor uncertainty, as demonstrated for the FeS system where the S absorption factor dropped from 1.118 to 1.04, improving the relative error from 1.0% to 0.59% (goldstein2018quantitativeanalysisthe pages 9-11).
+
+**Depth distribution ϕ(ρz).** Castaing's original tracer experiments (1951 onward) measured the distribution of X-ray production with depth by sandwiching a thin marker layer of known composition at varying depths within a substrate, establishing the ϕ(ρz) function that forms the basis of ZAF and ϕ(ρz) matrix corrections. The ϕ(ρz) function shows that at high overvoltage, X-ray production extends deeper into the specimen, increasing absorption losses and reducing the fraction of generated X-rays that escape to the detector. This provides the physics basis for the practical rule: the overvoltage of ~2–3 sits near the broad maximum of the ratio of useful (escaped) characteristic signal to interaction volume. ISO 22309:2011 codified this as a minimum overvoltage of 1.8 for quantitative analysis (tong2026measurementuncertaintiesof pages 8-11). Goldstein et al. recommend E₀/Ec > 1.5 as a minimum and note that a beam energy of 5 keV is the lowest at which at least one characteristic X-ray peak can be excited for all elements except H and He (newbury2019electronexcitedxraymicroanalysis pages 13-15).
+
+### 2. Dead-Time and Throughput Optimization (20–40% Historical; ≤10% for Modern SDD)
+
+The dead-time recommendation comes directly from detector counting-rate theory. X-rays arrive randomly, but the EDS can process only one photon at a time. The dead-time percentage is defined as DT(%) = (ICR − OCR)/ICR × 100%, where ICR is the input count rate and OCR is the output count rate (goldstein2018energydispersivexray pages 9-10).
+
+**Paralyzable model.** For a truly paralyzable (extending) dead-time system, the output count rate is OCR = ICR × exp(−ICR × τ), where τ is the dead-time constant per event. This function has a maximum at ICR = 1/τ, corresponding to a dead-time fraction of 1 − 1/e ≈ 63.2%. Beyond this point, further increases in ICR actually decrease OCR—the system paralyzes. In practice, the useful operating range is well below this mathematical maximum because (a) the dead-time correction accuracy degrades at high rates, and (b) coincidence (sum/pile-up) peaks grow rapidly.
+
+**Non-paralyzable model.** For a non-paralyzable system, OCR = ICR/(1 + ICR × τ). The OCR rises monotonically but with diminishing returns, and dead-time correction is mathematically straightforward. Real EDS systems exhibit behavior between these two limits, with modern SDD digital pulse processors closer to non-paralyzable at moderate rates.
+
+**Practical optimum.** The classic Si(Li)-EDS strategy was to operate at ≤30% dead-time on a strongly excited pure element standard (goldstein2018quantitativeanalysisthe pages 6-8). With modern SDD-EDS, Goldstein et al. recommend a more conservative approach: keeping dead-time below 10% on the most highly excited standard because coincidence peaks become significant above this threshold, particularly when trace constituents must be measured in spectral regions affected by sum peaks (goldstein2018quantitativeanalysisthe pages 6-8). At 3% dead-time, coincidence artifacts are minimal; at 29% dead-time on the same glass K412, extensive coincidence peaks (Al+Al, Si+O, Si+Mg, Si+Si, Si+Ca, Mg+Ca) become visible (goldstein2018quantitativeanalysisthe pages 6-8). Donovan et al. (2023) showed that the traditional linear dead-time correction expression Icps = icps/(1 − icps·τ) becomes inaccurate above ~50 kcps, requiring higher-order correction expressions (Willis 2-term, 6-term expansion, or logarithmic models) for accurate quantification at higher count rates (donovan2023anewmethod pages 2-3, donovan2023anewmethod pages 3-4).
+
+Thus the 20–40% guidance for Si(Li) detectors was a practical compromise maximizing stored counts while keeping dead-time correction errors tolerable; the shift to ≤10% for SDD-based quantitative work reflects the greater throughput capacity of SDDs and the more stringent demands of modern peak fitting for trace analysis.
+
+### 3. Pulse Process Time (Shaping Time): Electronic Noise Trade-off
+
+The choice of process time (also called shaping time, time constant, or throughput setting) in EDS is governed by a fundamental noise trade-off in the front-end electronics (goldstein2018energydispersivexray pages 14-15).
+
+**Noise components.** Lechner et al. (2004) express the equivalent noise charge (ENC) of an SDD as:
+
+ENC² = (2kᵦT/gₘ)·C²·A₁/τ + afC²·A₂ + q·Il·A₃·τ
+
+where the three terms represent serial white noise (proportional to 1/τ, dominated by detector capacitance C and FET transconductance gₘ), 1/f noise (independent of τ), and parallel noise (proportional to τ, dominated by leakage current Il) (lechner2004novelhighresolutionsilicon pages 2-4). At short shaping times, the serial (voltage) noise dominates and energy resolution degrades hyperbolically; at long shaping times, the parallel (current) noise and pile-up probability increase. The optimal shaping time sits at the broad minimum of ENC versus τ, typically around 0.5–3 μs for SDDs depending on detector area, temperature, and capacitance (schlosser2010expandingthedetection pages 2-4, lechner2004novelhighresolutionsilicon pages 4-5).
+
+**Practical implementation.** Goldstein et al. describe the trade-off as three-way: throughput, resolution, and coincidence rate. Longer process times achieve better resolution but poor throughput; shorter process times maximize throughput but increase coincidence events. The optimal setting for quantitative analysis is a moderate process time that degrades resolution by only a few percent (e.g., from 122–128 eV to 130–135 eV FWHM at Mn Kα) while substantially increasing throughput (goldstein2018energydispersivexray pages 14-15, goldstein2018energydispersivexray pages 25-26). Modern SDDs with 500 ns time constants can achieve resolution below 130 eV at Mn Kα while maintaining maximum OCR of ~130 kHz per detector chip (newbury2011isscanningelectron pages 2-3). The precision of quantitative analysis is more determined by the number of measured X-rays than by spectral resolution alone (goldstein2018energydispersivexray pages 14-15). Critically, for standards-based analysis, the same process time must be used for all standards and unknowns; adaptive process times that change resolution with throughput make spectrum fitting challenging and less accurate (goldstein2018energydispersivexray pages 14-15).
+
+### 4. Counting Statistics: Why ~10⁴ Counts Gives ~1% RSD
+
+The count-time recommendation derives directly from Poisson counting statistics. For a measured number of counts N drawn from a Poisson process, the standard deviation is σ = √N, so the relative standard deviation (RSD) is σ/N = 1/√N. Thus:
+
+- N = 10⁴ → RSD = 1%
+- N = 10⁶ → RSD = 0.1%
+- N = 10² → RSD = 10%
+
+This is a mathematical identity, not an empirical convention. Newbury and Ritchie (2019) tabulate the separate contributions of counting error, absorption-factor error, and atomic-number-factor error to the combined uncertainty budget for standards-based SDD-EDS analysis. For example, in the analysis of FeS at 20 keV with 7 × 10⁶ integrated spectrum counts, the counting error for the standard contributes ±0.0002 mass fraction and for the unknown ±0.0007, while the absorption factor error dominates at ±0.0017 (goldstein2018quantitativeanalysisthe pages 8-9). This demonstrates that at sufficiently high counts, counting statistics become a minor contributor and systematic errors (matrix corrections) dominate.
+
+Guyett et al. (2024) empirically validated the counting precision relationship for glass analyses: with only 10k–20k total counts (<1 s acquisition), RSD exceeded 5% even for major element oxides above 10 wt%; above 100k counts, all elements above 1.5 wt% exhibited RSD < 5%; and above 1M counts, major element oxide RSD was consistently below 2% (guyett2024optimizingsemedxfor pages 4-6). They recommended a minimum of 1M total spectrum counts for fully quantitative major-element SEM-EDX analysis, achievable in approximately 15 seconds with modern multi-detector SDD systems.
+
+### 5. Currie's Detection-Limit Framework (the "3-sigma" Criterion)
+
+The widely used "3-sigma" detection criterion traces to Currie's seminal 1968 paper in Analytical Chemistry, which rigorously separated three quantities using hypothesis-testing theory (currie1999detectionandquantification pages 2-4, currie1999detectionandquantification pages 1-2):
+
+1. **Critical value (decision threshold) Lc = z₁₋α·σ₀ = 1.645σ₀** (for α = 0.05): the threshold above which the analyst decides "detected." This controls only the false-positive rate.
+
+2. **Detection limit Ld = Lc + z₁₋β·σd ≈ 2×Lc = 3.29σ₀** (for α = β = 0.05, homoscedastic Gaussian): the true signal level at which the probability of a false negative is also limited to β = 0.05. The factor 3.29 (not 3) arises from the sum of two one-sided z-quantiles: 1.645 + 1.645 = 3.29.
+
+3. **Quantification limit Lq = kq·σ₀ = 10σ₀** (for 10% RSD at the quantification limit).
+
+The casual shorthand "3-sigma detection limit" conflates the decision threshold (1.645σ) with the detection limit (3.29σ) and slightly misquotes the coefficient. Currie (1999) reviewed this confusion, noting that prior approaches ignoring false negatives effectively set β = 0.50, yielding detection capability estimates that differed by up to three orders of magnitude from the hypothesis-testing result (currie1999detectionandquantification pages 1-2, currie1999detectionandquantification pages 4-6).
+
+In the EDS microanalysis context, Newbury and Ritchie (2019) express the concentration detection limit as CDL = [3√NB/(NS − NB)]·CS, where NB is the background counts under the peak, NS is the total peak integral counts, and CS is the known concentration (newbury2019electronexcitedxraymicroanalysis pages 13-15). This functional form traces directly to Ziebold's (1967) sensitivity expression CDL > 3.29a/(ntP × P/B)^(1/2), where a relates composition to intensity, n is the number of observations, tP is counting time, and P/B is the peak-to-background ratio (rinaldi2015electronprobemicroanalysis pages 4-5). Both formulations encode the same Poisson-statistics–based detection theory.
+
+### 6. Standards vs. Genuine Optima vs. Committee Convention
+
+The table below synthesizes how each parameter was derived and whether it represents a true optimum or a codified convention:
+
+| Parameter | Common recommended value | How the number was derived | Key primary literature / anchor reference | True optimum or convention? | Shift at low-kV / trace analysis |
+|---|---|---|---|---|---|
+| Overvoltage ratio U0 = E0/Ec | Typically ~2–3; ISO floor for quant often stated as ≥1.8 | From the inner-shell ionization cross-section rising steeply just above threshold and then flattening or declining in benefit per added kV, as described by Bethe-type formulations and later evaluated by Powell, Llovet, and Salvat; thick-target X-ray production efficiency measurements by Green and Cosslett showed characteristic yield peaking broadly near modest overvoltage, not at the highest beam energy. The competing penalty is that electron range and interaction volume grow strongly with E0, approximately by Kanaya–Okayama scaling, while phi(rho-z) depth distributions show X-ray generation moving deeper, increasing absorption and reducing spatial resolution. Thus the rule came from maximizing useful characteristic production per unit interaction volume, not from committee preference alone. (goldstein2018quantitativeanalysisthe pages 4-6, goldstein2018quantitativeanalysisthe pages 9-11, rinaldi2015electronprobemicroanalysis pages 7-8, newbury2019electronexcitedxraymicroanalysis pages 13-15, rinaldi2015electronprobemicroanalysis pages 2-4, tong2026measurementuncertaintiesof pages 8-11) | Bethe theory; Green and Cosslett 1961, 1968 measurements; Kanaya and Okayama 1972; Castaing-origin phi(rho-z) framework as summarized in later reviews | Mostly a genuine physics optimum, but broad rather than sharp; committees codified a robust operating zone | At ≤5 keV the optimum is often driven by line accessibility and spatial resolution rather than by the classic 2–3 rule alone; one may accept lower overvoltage (~1.25–1.8) to keep the interaction volume small or to reach only available L or M lines, with increased sensitivity to absorption, surface films, and matrix-correction error. For Mg K-alpha at 5 keV, U0 ≈ 5/1.254 ≈ 4.0: excitation is ample, but the practical limit becomes background, absorption, and overlap handling rather than insufficient ionization. (newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2019electronexcitedxraymicroanalysis pages 16-18, rinaldi2015electronprobemicroanalysis pages 7-8, wuhrer2016lowvoltageimaging pages 7-10, wuhrer2016lowvoltageimaging pages 10-12) |
+| Detector dead time / throughput | Historically ~20–40% for Si(Li); modern standards-based SDD quant often kept much lower, commonly <10–15% on the most intense peak if coincidence artifacts matter | Derived from counting-system dead-time theory. For a paralyzable model, stored rate behaves approximately as OCR = ICR × exp(-ICR × tau), which peaks at ICR × tau = 1, i.e. 36.8% dead time; for a non-paralyzable model OCR = ICR/(1 + ICR × tau), throughput keeps rising but with diminishing returns. Real EDS electronics also have anti-coincidence rejection and pile-up artifacts, so the practical maximum useful throughput occurs before the mathematical maximum if sum peaks will compromise quantification. Goldstein shows OCR–ICR curves and coincidence-peak growth; Donovan shows why simple linear dead-time correction breaks down at higher rates. (goldstein2018quantitativeanalysisthe pages 6-8, goldstein2018energydispersivexray pages 9-10, donovan2023anewmethod pages 3-4, donovan2023anewmethod pages 2-3, donovan2023anewmethod pages 4-5) | Classic dead-time theory; modern microanalysis implementation in Goldstein and Donovan | A real throughput optimum exists mathematically, but the widely taught 20–40% band is partly a practical convention balancing throughput against pile-up; with SDD quantitative work the optimum for accuracy often shifts lower | For low-kV and trace work, keep dead time lower because weak trace peaks can be hidden by coincidence peaks and by calibration or resolution drift at high rates. Modern SDDs can run at high OCR, but if looking for 0.5–1 wt% Mg in AlSi10Mg at 5 keV, a conservative dead time (~10–20%, or even lower if sum peaks intrude) is usually preferable to maximize spectral cleanliness. (goldstein2018quantitativeanalysisthe pages 6-8, goldstein2018energydispersivexray pages 9-10, guyett2024optimizingsemedxfor pages 4-6, guyett2024optimizingsemedxfor pages 3-4) |
+| Pulse processor shaping / process time | Choose a moderate setting: a few eV worse than best resolution, but far better throughput; avoid adaptive shaping for standards-based quant | Derived from the equivalent-noise-charge minimum. Lechner gives ENC^2 = serial white term proportional to 1/tau + a 1/f term + a parallel-noise term proportional to tau: short shaping times increase series white noise and ballistic-deficit sensitivity; long shaping times increase parallel-noise contribution and pile-up probability. Therefore the optimum is at the broad minimum of ENC versus shaping time, then adjusted upward or downward depending on count-rate needs. Goldstein describes the three-way trade-off among resolution, throughput, and coincidence rate; Schlosser and Niculae show measured FWHM versus shaping time for SDDs. (goldstein2018energydispersivexray pages 25-26, goldstein2018energydispersivexray pages 14-15, newbury2011isscanningelectron pages 2-3, niculae2006optimizedreadoutmethods pages 2-3, niculae2006optimizedreadoutmethods pages 3-6, schlosser2010expandingthedetection pages 2-4, lechner2004novelhighresolutionsilicon pages 2-4, lechner2004novelhighresolutionsilicon pages 4-5) | Semiconductor-detector noise theory; Lechner 2004; Niculae 2006; Schlosser 2010; later digital-pulse work such as Blaj 2017 | Genuine electronics optimum, but broad; the exact chosen setting is instrument-specific and thus partly conventional in practice | At low-kV, low-energy peaks are narrow and often crowded, so somewhat longer shaping than for fast mapping may be justified if resolving Mg, Al, Si low-energy structure matters. For trace analysis, prioritize stability and peak shape over absolute OCR; sacrificing a small amount of throughput for cleaner low-energy deconvolution is often worthwhile. (goldstein2018energydispersivexray pages 14-15, newbury2011isscanningelectron pages 2-3, schlosser2010expandingthedetection pages 2-4, wuhrer2016lowvoltageimaging pages 10-12) |
+| Live time / counts for precision | Rule of thumb: ~10,000 net counts in a peak of interest gives ~1% counting RSD; major-element whole-spectrum quant often uses 10^6 total counts or more | Pure Poisson statistics: for net peak counts N, sigma/N ≈ 1/sqrt(N). Thus N = 10^4 gives 1% relative standard deviation from counting alone. Real net-peak precision is worse when background subtraction is needed, so standards and unknowns both require sufficient dose. Newbury and Goldstein tables separate counting error from matrix-correction error; Guyett empirically found >10^5 counts gives <5% RSD for >1.5 wt% oxides and recommends ~10^6 counts for robust quantitative SEM-EDX of majors. (goldstein2018quantitativeanalysisthe pages 8-9, goldstein2018quantitativeanalysisthe pages 9-11, newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2015performingelementalmicroanalysis pages 2-4, guyett2024optimizingsemedxfor pages 4-6) | Poisson counting law; Ziebold 1967 sensitivity framework; Currie 1968 and 1999 for limits; Newbury and Ritchie applications | This is a true statistical relationship, not convention; the exact count targets are practical translations of desired precision | Low-kV reduces continuum volume but often lowers usable peak-to-background and can worsen matrix sensitivity for low-energy lines, so more counts may be needed than the simple 10^4 rule suggests. For 0.5–1 wt% Mg in AlSi10Mg at 5 keV, several 10^5 to ~10^6 total counts, or repeated acquisitions summed after drift or damage checks, is more realistic if one wants robust sub-wt% precision. (newbury2019electronexcitedxraymicroanalysis pages 13-15, ritchie2018exploringthelimits pages 9-11, ritchie2018exploringthelimits pages 4-5, guyett2024optimizingsemedxfor pages 4-6) |
+| Detection criterion | Currie 3-sigma family: LC = 1.645 sigma0, LD = 3.29 sigma0 for alpha = beta = 0.05; often simplified in practice to 3 sigma detection | Currie’s 1968 hypothesis-testing framework separated the decision threshold LC from the true minimum detectable amount LD. Under Gaussian, homoscedastic approximation and equal Type-I and Type-II risks of 0.05, LC = 1.645 sigma0, and LD = LC + 1.645 sigmaD ≈ 3.29 sigma0. For counting data, sigma is usually controlled by blank or background counts, which is why detection capability depends on the background under the peak. Newbury expresses the same idea in concentration form as CDL = [3 × sqrt(NB)/(NS − NB)] × CS. (currie1999detectionandquantification pages 4-6, currie1999detectionandquantification pages 2-4, currie1999detectionandquantification pages 1-2, newbury2019electronexcitedxraymicroanalysis pages 13-15, rinaldi2015electronprobemicroanalysis pages 4-5) | Currie 1968; Currie 1999 retrospective; Ziebold 1967 concentration sensitivity expression | A genuine statistical derivation; the casual phrase 3-sigma is a simplified convention for Currie’s more exact 3.29-sigma detection limit | At low-kV the blank and low-energy artifacts become more dominant, so sigma is often set by background modeling, contamination, and deconvolution residuals rather than by raw peak counts alone. For Mg K-alpha at 0.5–1 wt% in AlSi10Mg at 5 keV, formal detectability is usually not the bottleneck; reliable quantification is limited more by standards and matrix-correction quality, low-energy peak fitting, and reproducibility than by passing the Currie decision threshold. (wuhrer2016lowvoltageimaging pages 10-12, newbury2019electronexcitedxraymicroanalysis pages 13-15, tong2026measurementuncertaintiesof pages 8-11) |
+
+
+*Table: This table summarizes how the standard SEM-EDS acquisition parameters were justified from physics, electronics, and counting statistics rather than merely adopted by standards committees. It also shows which values are true optima, which are practical conventions, and how they shift for low-voltage and trace-level analysis.*
+
+Several observations emerge regarding the nature of these recommendations:
+
+- The **overvoltage ratio** of ~2–3 reflects a genuine but broad physics optimum: the Bethe cross-section maximum is broad, and the exact best value depends on whether one prioritizes intensity, spatial resolution, or matrix-correction accuracy. ISO 22309:2011 codified a floor of 1.8, which is a conservative standardization of the physics (tong2026measurementuncertaintiesof pages 8-11).
+
+- The **dead-time** guidance evolved from 20–40% (Si(Li) era, optimizing stored-count rate) to <10% (SDD era, minimizing coincidence peaks for trace analysis) as detector technology changed. No published round-robin explicitly validated the 20–40% range; it was derived from dead-time throughput curves and practical experience (goldstein2018quantitativeanalysisthe pages 6-8).
+
+- The **process time** setting has a genuine electronics optimum (the ENC minimum), but the commercially available settings and naming conventions differ between vendors, making the specific recommendation partly instrument-dependent (goldstein2018energydispersivexray pages 14-15, lechner2004novelhighresolutionsilicon pages 2-4).
+
+- The **10,000-count rule** is a direct mathematical consequence of Poisson statistics and is not convention. The translation into specific live-times depends entirely on count rates, which depend on all other parameters.
+
+- **Currie's 3.29σ detection limit** is a rigorous derivation from Neyman-Pearson hypothesis testing at specified error rates, not an empirical guess. The common simplification to "3σ" is a minor approximation that has become conventional shorthand (currie1999detectionandquantification pages 2-4).
+
+Regarding interlaboratory validation, Newbury and Ritchie (2015) demonstrated that the k-ratio/matrix correction protocol with SDD-EDS achieves accuracy matching the WDS distribution established in 1975 (approximately 2.5% relative standard deviation for major constituents, with ~95% of analyses falling within ±5% relative error) (newbury2015performingelementalmicroanalysis pages 2-4). However, no published round-robin study was identified that systematically varied EDS acquisition parameters (overvoltage, dead-time, process time) across laboratories to validate the specific recommended ranges. The standards appear to have been written by codifying well-understood physics relationships and experienced practitioners' consensus within ISO TC 202 and ASTM E04 committees.
+
+### 7. Shifts for Low-Voltage Microanalysis and Trace Quantification
+
+**Low beam energy (≤5 keV).** At low voltage, the conventional parameter optima shift significantly. A beam energy of 5 keV represents the lowest value at which at least one characteristic X-ray peak can be excited for all elements of the periodic table except H and He (newbury2019electronexcitedxraymicroanalysis pages 13-15). At lower voltages, an increasing number of elements becomes inaccessible. The analyst is forced to use unfamiliar X-ray families (e.g., Ba M-family instead of Ba L-family) which may suffer severe mutual interferences, as demonstrated for YBa₂Cu₃O₇ analyzed at 5 keV where O K, Cu L, and Ba M families overlap (newbury2019electronexcitedxraymicroanalysis pages 16-18). Rinaldi and Llovet (2015) documented systematic deviations in transition-element analysis at low voltages (5–6 keV), including Cr underestimation (−0.7% to −17%) and Fe/Ni overestimation (+14% to +42%), attributed to problems with mass absorption coefficients and low fluorescence yields for L-lines (rinaldi2015electronprobemicroanalysis pages 7-8). The interaction volume reduction (approximately 100-fold decrease from 20 keV to 1 keV) improves spatial resolution to the sub-micrometer scale but reduces absolute X-ray yield per electron, requiring higher beam currents or longer counting times (gollaschindler2026edswithlowvoltage pages 3-6). Surface contamination layers and native oxides, which are negligible at 20 keV, become significant contributors to the measured spectrum at low voltage (newbury2019electronexcitedxraymicroanalysis pages 13-15).
+
+**Trace-element quantification near 0.5–1 wt%.** For Mg Kα (1.254 keV) at 0.5–1 wt% in AlSi10Mg measured at 5 keV with an SDD, the overvoltage is generous (U₀ ≈ 4.0), so excitation efficiency is not limiting. The challenges are instead: (a) the Mg K peak sits in a crowded low-energy region where Al K (1.486 keV) is a dominant neighboring peak; (b) peak-to-background ratios for the Mg peak depend on the continuum modeling and the detector response at low energies; (c) the absorption correction for low-energy photons becomes large and uncertain; and (d) surface contamination carbon deposition can increase absorption of X-rays near the carbon K-edge (0.284 keV) and affect quantification of light elements. Newbury and Ritchie showed that detection limits of 200–500 ppm (0.02–0.05 wt%) are achievable at conventional voltages within 500 s counting time (newbury2019electronexcitedxraymicroanalysis pages 13-15), but at low voltage the effective detection limit for a given counting time may be worse due to increased background relative to peak and poorer matrix-correction accuracy (wuhrer2016lowvoltageimaging pages 10-12). For reliable quantification of 0.5–1 wt% Mg, standards-based analysis with well-characterized standards and careful peak fitting is essential; standardless methods showed ~95% of results within ±25% relative deviation in early testing, an unacceptable error for trace-level work (newbury2019electronexcitedxraymicroanalysis pages 18-20). The practical recommendation is to collect substantially more counts than the simple 10⁴-count rule would suggest (several 10⁵ to 10⁶ total spectrum counts), use a moderate process time prioritizing spectral stability over maximum throughput, keep dead time conservatively low to avoid pile-up artifacts in the energy region of interest, and employ multiple replicate measurements with statistical quality-control tests to monitor drift and damage (ritchie2018exploringthelimits pages 4-5, guyett2024optimizingsemedxfor pages 4-6).
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+| Parameter | Common recommended value | How the number was derived | Key primary literature / anchor reference | True optimum or convention? | Shift at low-kV / trace analysis |
+|---|---|---|---|---|---|
+| Overvoltage ratio U0 = E0/Ec | Typically ~2–3; ISO floor for quant often stated as ≥1.8 | From the inner-shell ionization cross-section rising steeply just above threshold and then flattening or declining in benefit per added kV, as described by Bethe-type formulations and later evaluated by Powell, Llovet, and Salvat; thick-target X-ray production efficiency measurements by Green and Cosslett showed characteristic yield peaking broadly near modest overvoltage, not at the highest beam energy. The competing penalty is that electron range and interaction volume grow strongly with E0, approximately by Kanaya–Okayama scaling, while phi(rho-z) depth distributions show X-ray generation moving deeper, increasing absorption and reducing spatial resolution. Thus the rule came from maximizing useful characteristic production per unit interaction volume, not from committee preference alone. (pqac-00000007, pqac-00000008, pqac-00000028, pqac-00000043, pqac-00000050, pqac-00000053) | Bethe theory; Green and Cosslett 1961, 1968 measurements; Kanaya and Okayama 1972; Castaing-origin phi(rho-z) framework as summarized in later reviews | Mostly a genuine physics optimum, but broad rather than sharp; committees codified a robust operating zone | At ≤5 keV the optimum is often driven by line accessibility and spatial resolution rather than by the classic 2–3 rule alone; one may accept lower overvoltage (~1.25–1.8) to keep the interaction volume small or to reach only available L or M lines, with increased sensitivity to absorption, surface films, and matrix-correction error. For Mg K-alpha at 5 keV, U0 ≈ 5/1.254 ≈ 4.0: excitation is ample, but the practical limit becomes background, absorption, and overlap handling rather than insufficient ionization. (pqac-00000043, pqac-00000045, pqac-00000028, pqac-00000029, pqac-00000030) |
+| Detector dead time / throughput | Historically ~20–40% for Si(Li); modern standards-based SDD quant often kept much lower, commonly <10–15% on the most intense peak if coincidence artifacts matter | Derived from counting-system dead-time theory. For a paralyzable model, stored rate behaves approximately as OCR = ICR × exp(-ICR × tau), which peaks at ICR × tau = 1, i.e. 36.8% dead time; for a non-paralyzable model OCR = ICR/(1 + ICR × tau), throughput keeps rising but with diminishing returns. Real EDS electronics also have anti-coincidence rejection and pile-up artifacts, so the practical maximum useful throughput occurs before the mathematical maximum if sum peaks will compromise quantification. Goldstein shows OCR–ICR curves and coincidence-peak growth; Donovan shows why simple linear dead-time correction breaks down at higher rates. (pqac-00000009, pqac-00000011, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049) | Classic dead-time theory; modern microanalysis implementation in Goldstein and Donovan | A real throughput optimum exists mathematically, but the widely taught 20–40% band is partly a practical convention balancing throughput against pile-up; with SDD quantitative work the optimum for accuracy often shifts lower | For low-kV and trace work, keep dead time lower because weak trace peaks can be hidden by coincidence peaks and by calibration or resolution drift at high rates. Modern SDDs can run at high OCR, but if looking for 0.5–1 wt% Mg in AlSi10Mg at 5 keV, a conservative dead time (~10–20%, or even lower if sum peaks intrude) is usually preferable to maximize spectral cleanliness. (pqac-00000009, pqac-00000046, pqac-00000054, pqac-00000055) |
+| Pulse processor shaping / process time | Choose a moderate setting: a few eV worse than best resolution, but far better throughput; avoid adaptive shaping for standards-based quant | Derived from the equivalent-noise-charge minimum. Lechner gives ENC^2 = serial white term proportional to 1/tau + a 1/f term + a parallel-noise term proportional to tau: short shaping times increase series white noise and ballistic-deficit sensitivity; long shaping times increase parallel-noise contribution and pile-up probability. Therefore the optimum is at the broad minimum of ENC versus shaping time, then adjusted upward or downward depending on count-rate needs. Goldstein describes the three-way trade-off among resolution, throughput, and coincidence rate; Schlosser and Niculae show measured FWHM versus shaping time for SDDs. (pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027) | Semiconductor-detector noise theory; Lechner 2004; Niculae 2006; Schlosser 2010; later digital-pulse work such as Blaj 2017 | Genuine electronics optimum, but broad; the exact chosen setting is instrument-specific and thus partly conventional in practice | At low-kV, low-energy peaks are narrow and often crowded, so somewhat longer shaping than for fast mapping may be justified if resolving Mg, Al, Si low-energy structure matters. For trace analysis, prioritize stability and peak shape over absolute OCR; sacrificing a small amount of throughput for cleaner low-energy deconvolution is often worthwhile. (pqac-00000015, pqac-00000016, pqac-00000025, pqac-00000030) |
+| Live time / counts for precision | Rule of thumb: ~10,000 net counts in a peak of interest gives ~1% counting RSD; major-element whole-spectrum quant often uses 10^6 total counts or more | Pure Poisson statistics: for net peak counts N, sigma/N ≈ 1/sqrt(N). Thus N = 10^4 gives 1% relative standard deviation from counting alone. Real net-peak precision is worse when background subtraction is needed, so standards and unknowns both require sufficient dose. Newbury and Goldstein tables separate counting error from matrix-correction error; Guyett empirically found >10^5 counts gives <5% RSD for >1.5 wt% oxides and recommends ~10^6 counts for robust quantitative SEM-EDX of majors. (pqac-00000006, pqac-00000008, pqac-00000034, pqac-00000041, pqac-00000043, pqac-00000054) | Poisson counting law; Ziebold 1967 sensitivity framework; Currie 1968 and 1999 for limits; Newbury and Ritchie applications | This is a true statistical relationship, not convention; the exact count targets are practical translations of desired precision | Low-kV reduces continuum volume but often lowers usable peak-to-background and can worsen matrix sensitivity for low-energy lines, so more counts may be needed than the simple 10^4 rule suggests. For 0.5–1 wt% Mg in AlSi10Mg at 5 keV, several 10^5 to ~10^6 total counts, or repeated acquisitions summed after drift or damage checks, is more realistic if one wants robust sub-wt% precision. (pqac-00000034, pqac-00000036, pqac-00000038, pqac-00000054) |
+| Detection criterion | Currie 3-sigma family: LC = 1.645 sigma0, LD = 3.29 sigma0 for alpha = beta = 0.05; often simplified in practice to 3 sigma detection | Currie’s 1968 hypothesis-testing framework separated the decision threshold LC from the true minimum detectable amount LD. Under Gaussian, homoscedastic approximation and equal Type-I and Type-II risks of 0.05, LC = 1.645 sigma0, and LD = LC + 1.645 sigmaD ≈ 3.29 sigma0. For counting data, sigma is usually controlled by blank or background counts, which is why detection capability depends on the background under the peak. Newbury expresses the same idea in concentration form as CDL = [3 × sqrt(NB)/(NS − NB)] × CS. (pqac-00000018, pqac-00000021, pqac-00000022, pqac-00000034, pqac-00000051) | Currie 1968; Currie 1999 retrospective; Ziebold 1967 concentration sensitivity expression | A genuine statistical derivation; the casual phrase 3-sigma is a simplified convention for Currie’s more exact 3.29-sigma detection limit | At low-kV the blank and low-energy artifacts become more dominant, so sigma is often set by background modeling, contamination, and deconvolution residuals rather than by raw peak counts alone. For Mg K-alpha at 0.5–1 wt% in AlSi10Mg at 5 keV, formal detectability is usually not the bottleneck; reliable quantification is limited more by standards and matrix-correction quality, low-energy peak fitting, and reproducibility than by passing the Currie decision threshold. (pqac-00000030, pqac-00000034, pqac-00000043, pqac-00000053) |
+
+
+*Table: This table summarizes how the standard SEM-EDS acquisition parameters were justified from physics, electronics, and counting statistics rather than merely adopted by standards committees. It also shows which values are true optima, which are practical conventions, and how they shift for low-voltage and trace-level analysis.*
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+1. (goldstein2018quantitativeanalysisthe pages 4-6): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_20, doi:10.1007/978-1-4939-6676-9\_20. This article has 9 citations.
+
+2. (goldstein2018quantitativeanalysisthe pages 9-11): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_20, doi:10.1007/978-1-4939-6676-9\_20. This article has 9 citations.
+
+3. (tong2026measurementuncertaintiesof pages 8-11): V. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.
+
+4. (newbury2019electronexcitedxraymicroanalysis pages 13-15): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.
+
+5. (goldstein2018energydispersivexray pages 9-10): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_16, doi:10.1007/978-1-4939-6676-9\_16. This article has 33 citations.
+
+6. (goldstein2018quantitativeanalysisthe pages 6-8): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_20, doi:10.1007/978-1-4939-6676-9\_20. This article has 9 citations.
+
+7. (donovan2023anewmethod pages 2-3): John J Donovan, Aurélien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050. This article has 18 citations.
+
+8. (donovan2023anewmethod pages 3-4): John J Donovan, Aurélien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050. This article has 18 citations.
+
+9. (goldstein2018energydispersivexray pages 14-15): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_16, doi:10.1007/978-1-4939-6676-9\_16. This article has 33 citations.
+
+10. (lechner2004novelhighresolutionsilicon pages 2-4): P. Lechner, A. Pahlke, and H. Soltau. Novel high-resolution silicon drift detectors. X-Ray Spectrometry, 33:256-261, Jul 2004. URL: https://doi.org/10.1002/xrs.717, doi:10.1002/xrs.717. This article has 111 citations and is from a peer-reviewed journal.
+
+11. (schlosser2010expandingthedetection pages 2-4): D.M. Schlosser, P. Lechner, G. Lutz, A. Niculae, H. Soltau, L. Strüder, R. Eckhardt, K. Hermenau, G. Schaller, F. Schopper, O. Jaritschin, A. Liebel, A. Simsek, C. Fiorini, and A. Longoni. Expanding the detection efficiency of silicon drift detectors. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 624:270-276, Dec 2010. URL: https://doi.org/10.1016/j.nima.2010.04.038, doi:10.1016/j.nima.2010.04.038. This article has 88 citations.
+
+12. (lechner2004novelhighresolutionsilicon pages 4-5): P. Lechner, A. Pahlke, and H. Soltau. Novel high-resolution silicon drift detectors. X-Ray Spectrometry, 33:256-261, Jul 2004. URL: https://doi.org/10.1002/xrs.717, doi:10.1002/xrs.717. This article has 111 citations and is from a peer-reviewed journal.
+
+13. (goldstein2018energydispersivexray pages 25-26): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_16, doi:10.1007/978-1-4939-6676-9\_16. This article has 33 citations.
+
+14. (newbury2011isscanningelectron pages 2-3): Dale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.
+
+15. (goldstein2018quantitativeanalysisthe pages 8-9): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\_20, doi:10.1007/978-1-4939-6676-9\_20. This article has 9 citations.
+
+16. (guyett2024optimizingsemedxfor pages 4-6): Paul C. Guyett, David Chew, Vitor Azevedo, Lucy C. Blennerhassett, Carolina Rosca, and Emma Tomlinson. Optimizing sem-edx for fast, high-quality and non-destructive elemental analysis of glass. Journal of Analytical Atomic Spectrometry, 39:2565-2579, Jan 2024. URL: https://doi.org/10.1039/d4ja00212a, doi:10.1039/d4ja00212a. This article has 50 citations and is from a peer-reviewed journal.
+
+17. (currie1999detectionandquantification pages 2-4): Lloyd A. Currie. Detection and quantification limits: origins and historical overview1adapted from the proceedings of the 1996 joint statistical meetings (american statistical association, 1997). original title: “foundations and future of detection and quantification limits”. contribution of the national institute of standards and technology; not subject to copyright.1. May 1999. URL: https://doi.org/10.1016/s0003-2670(99)00105-1, doi:10.1016/s0003-2670(99)00105-1. This article has 701 citations and is from a domain leading peer-reviewed journal.
+
+18. (currie1999detectionandquantification pages 1-2): Lloyd A. Currie. Detection and quantification limits: origins and historical overview1adapted from the proceedings of the 1996 joint statistical meetings (american statistical association, 1997). original title: “foundations and future of detection and quantification limits”. contribution of the national institute of standards and technology; not subject to copyright.1. May 1999. URL: https://doi.org/10.1016/s0003-2670(99)00105-1, doi:10.1016/s0003-2670(99)00105-1. This article has 701 citations and is from a domain leading peer-reviewed journal.
+
+19. (currie1999detectionandquantification pages 4-6): Lloyd A. Currie. Detection and quantification limits: origins and historical overview1adapted from the proceedings of the 1996 joint statistical meetings (american statistical association, 1997). original title: “foundations and future of detection and quantification limits”. contribution of the national institute of standards and technology; not subject to copyright.1. May 1999. URL: https://doi.org/10.1016/s0003-2670(99)00105-1, doi:10.1016/s0003-2670(99)00105-1. This article has 701 citations and is from a domain leading peer-reviewed journal.
+
+20. (rinaldi2015electronprobemicroanalysis pages 4-5): Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.
+
+21. (rinaldi2015electronprobemicroanalysis pages 7-8): Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.
+
+22. (rinaldi2015electronprobemicroanalysis pages 2-4): Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.
+
+23. (newbury2019electronexcitedxraymicroanalysis pages 16-18): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.
+
+24. (wuhrer2016lowvoltageimaging pages 7-10): Richard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.
+
+25. (wuhrer2016lowvoltageimaging pages 10-12): Richard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.
+
+26. (donovan2023anewmethod pages 4-5): John J Donovan, Aurélien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050. This article has 18 citations.
+
+27. (guyett2024optimizingsemedxfor pages 3-4): Paul C. Guyett, David Chew, Vitor Azevedo, Lucy C. Blennerhassett, Carolina Rosca, and Emma Tomlinson. Optimizing sem-edx for fast, high-quality and non-destructive elemental analysis of glass. Journal of Analytical Atomic Spectrometry, 39:2565-2579, Jan 2024. URL: https://doi.org/10.1039/d4ja00212a, doi:10.1039/d4ja00212a. This article has 50 citations and is from a peer-reviewed journal.
+
+28. (niculae2006optimizedreadoutmethods pages 2-3): A. Niculae, P. Lechner, H. Soltau, G. Lutz, L. Strüder, C. Fiorini, and A. Longoni. Optimized readout methods of silicon drift detectors for high-resolution x-ray spectroscopy. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 568:336-342, Nov 2006. URL: https://doi.org/10.1016/j.nima.2006.06.025, doi:10.1016/j.nima.2006.06.025. This article has 76 citations.
+
+29. (niculae2006optimizedreadoutmethods pages 3-6): A. Niculae, P. Lechner, H. Soltau, G. Lutz, L. Strüder, C. Fiorini, and A. Longoni. Optimized readout methods of silicon drift detectors for high-resolution x-ray spectroscopy. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 568:336-342, Nov 2006. URL: https://doi.org/10.1016/j.nima.2006.06.025, doi:10.1016/j.nima.2006.06.025. This article has 76 citations.
+
+30. (newbury2015performingelementalmicroanalysis pages 2-4): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 609 citations and is from a peer-reviewed journal.
+
+31. (ritchie2018exploringthelimits pages 9-11): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.
+
+32. (ritchie2018exploringthelimits pages 4-5): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.
+
+33. (gollaschindler2026edswithlowvoltage pages 3-6): Ute Golla-Schindler and Gerhard Schneider. Eds with low-voltage sem: possibilities and limitations of lithium detection and quantification. EPJ Web of Conferences, 349:01004, Jan 2026. URL: https://doi.org/10.1051/epjconf/202634901004, doi:10.1051/epjconf/202634901004. This article has 0 citations and is from a peer-reviewed journal.
+
+34. (newbury2019electronexcitedxraymicroanalysis pages 18-20): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.
\ No newline at end of file
diff --git a/outputs/issue-1-eds-parameters/task_response_verbose.json b/outputs/issue-1-eds-parameters/task_response_verbose.json
new file mode 100644
index 0000000..0890315
--- /dev/null
+++ b/outputs/issue-1-eds-parameters/task_response_verbose.json
@@ -0,0 +1,10195 @@
+{
+  "status": "success",
+  "query": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
+  "user": null,
+  "created_at": "2026-08-20T19:40:40.086476Z",
+  "job_name": "job-futurehouse-paperqa3-high",
+  "share_status": "private",
+  "permitted_accessors": {
+    "users": [],
+    "organizations": []
+  },
+  "build_owner": "FutureHouse",
+  "environment_name": null,
+  "agent_name": null,
+  "task_id": "2a23935c-f686-488e-a0a6-0faada1cb90f",
+  "project_id": null,
+  "agent_state": [
+    {
+      "id": "4c992d2e-9a91-4add-a306-53b999723cf4",
+      "trajectory_id": "2a23935c-f686-488e-a0a6-0faada1cb90f",
+      "trajectory_timestep": 17,
+      "step": "after_transition",
+      "state": {
+        "transition": {
+          "timestep": 17,
+          "agent_state": {
+            "tools": [
+              {
+                "type": "function",
+                "info": {
+                  "name": "paper_search",
+                  "description": "Search for papers in Google Scholar for you to look at.\n\nCan be called repeatedly with identical parameters to retrieve more results (max 2 repeats).\nA short summary of the retrieved papers will be returned, but to examine the full content of each paper,\nyou must use the gather_evidence tool.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "A Google Scholar search query, which can be a specific phrase, complete sentence,\nor general keywords, e.g. 'machine learning for immunology'. Also can be\ngiven search operators like 'author:'.",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "min_year": {
+                        "anyOf": [
+                          {
+                            "type": "integer"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "filter for minimum publication year.\nThe current year is 2026. If unsure about time range, do not set.",
+                        "title": "Min Year"
+                      },
+                      "max_year": {
+                        "anyOf": [
+                          {
+                            "type": "integer"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "filter for maximum publication year.\nThe current year is 2026. If unsure about time range, do not set.",
+                        "title": "Max Year"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "collect_cited_papers_in_evidence",
+                  "description": "Collect papers by traversing the citations of relevant papers to increase the paper count.\n\nThis tool has no effect if called when paper count or relevant papers are zero.\nThis tool will find papers that are likely to lead to more relevant evidence.\nThe papers found have a higher chance of relevance because this tool starts from relevant evidence.\nThis tool's usefulness increases with the amount of gathered evidence as there's more citations to consider.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {},
+                    "required": []
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "open_targets_search",
+                  "description": "Search for disease-target associations from OpenTargets database.\n\nAdds new disease-target association data to the state and returns top search results.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "disease_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of disease names to search for.\nUsage:\ndisease_names = [\"Alzheimer's\"] ->\n    Returns top targets for Alzheimer's\ndisease_names = [\"Alzheimer's\", \"Diabetes\"], target_names = [\"PSEN1\"] ->\n    Filters for only PSEN1-Alzheimer's/Diabetes evidence\ndisease_names = [\"Alzheimer's\"], drug_names = [\"Aducanumab\"] ->\n    Filters for Alzheimer's disease-target pairs treated by Aducanumab",
+                        "title": "Disease Names"
+                      },
+                      "target_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of target names to search for.\nUsage:\ntarget_names = [\"BACE1\"] ->\n    Returns top diseases associated with BACE1\ntarget_names = [\"BACE1\", \"APP\"], disease_names = [\"Alzheimer's\"] ->\n    Filters for only these target-Alzheimer's pairs\ntarget_names = [\"BACE1\"], drug_names = [\"Aducanumab\"] ->\n    Filters for BACE1 disease pairs treated by Aducanumab",
+                        "title": "Target Names"
+                      },
+                      "drug_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of drug names to generate or filter results.\nUsage:\ndrug_names = [\"Aducanumab\"] ->\n    Returns all disease-target pairs treated by Aducanumab\ndrug_names = [\"Aducanumab\"], disease_names = [\"Alzheimer's\"] ->\n    Filters for Alzheimer's pairs treated by Aducanumab\ndrug_names = [\"Aducanumab\"], target_names = [\"BACE1\"] ->\n    Filters for BACE1 disease pairs treated by Aducanumab",
+                        "title": "Drug Names"
+                      }
+                    },
+                    "required": []
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "create_artifact",
+                  "description": "Create an artifact that can be used in the final answer, based on information\nyou have collected so far.\n\nHow it works: the full message history thus far is passed to another LLM,\nalong with the question and your description. The LLM is tasked to create\nan artifact that matches your specifications, including a title, caption,\nand markdown content. You drive the process by specifying the type and\ndescribing what you want.\n\nOnly use this tool *after* you have gathered sufficient evidence or\ninformation to create a new artifact. Do not call this tool in parallel\nwith tools that are searching for information or evidence that would be\nnecessary to create this artifact.\n\nIt is very helpful after calls to several search tools,\nafter calls to the `gather_evidence` tool, but it is not required.\nHowever, it should be called before the `answer` tool at\nleast one time, but more may be given if specifically helpful for\nthe task, so that the `answer` tool can use the artifacts for the answer.\n\nAn artifact can be any string representable fact or list of facts,\nformatted using markdown syntax. The artifact will be generated as one of\nthe following types:\n- table: Markdown tables with rows and columns (e.g., findings, methods, molecules)\n- code_block: Code snippets in fenced code blocks\n- blockquote: Quoted text or important facts (using > prefix)\n- image: AI-generated image (chart, diagram, or visualization)\n\nEach artifact consists of:\n- A short title (3-8 words) that names what the artifact contains\n- A caption (1-2 sentences) describing what the artifact shows and why it's useful\n- Markdown content in a single element type (validated automatically with retries if needed)\n  For image type, content is a markdown image embed ``![title](data:image/png;base64,...)``,\n  embedding the PNG directly as a base64 data URL.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "artifact_type": {
+                        "description": "Artifact type to create. Must be one of: table,\ncode_block, blockquote, image.",
+                        "title": "Artifact Type",
+                        "type": "string"
+                      },
+                      "description": {
+                        "description": "Description of what you want in the artifact. Be specific\nabout what information should be included, how it should be organized,\nand what columns/sections/content you want. This guides the summary LLM.\nFor image type, describe the visual you want generated in detail.",
+                        "title": "Description",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "artifact_type",
+                      "description"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "clinical_trials_search",
+                  "description": "Search for clinical trials, with support for repeated calls and concurrent execution.\n\nWill add new clinical trials to the state, and return metadata about the number of trials found.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "The search query string. Supports complex boolean expressions, field-specific\nsearches, and query modifiers through operators. All configuration is done through\noperators in the query string.\nQuery Syntax:\n    Basic Search:\n        Simple text automatically uses default EXPANSION[Relaxation] and COVERAGE[Contains]\n        >>> \"heart attack\"\n\n    Modified Search:\n        Use operators to modify search behavior:\n        >>> 'EXPANSION[None]COVERAGE[FullMatch]\"exact phrase\"'\n        >>> 'EXPANSION[Concept]heart attack'\n\n    Field Search:\n        Specify fields using AREA operator:\n        >>> 'AREA[InterventionName]aspirin'\n        >>> 'AREA[Phase]PHASE3'\n\n    Location Search:\n        Use SEARCH operator for compound location queries:\n        >>> 'cancer AND SEARCH[Location](AREA[LocationCity]Boston AND AREA[LocationState]Massachusetts)'\n\n    Complex Boolean:\n        Combine terms with AND, OR, NOT and parentheses:\n        >>> '(cancer OR tumor) AND NOT (EXPANSION[None]pediatric OR AREA[StdAge]CHILD)'\n\n    Date Ranges:\n        Use RANGE to specify date ranges with formats like \"yyyy-MM\" or \"yyyy-MM-dd\".\n        Note that MIN and MAX can be used for open-ended ranges:\n        >>> AREA[ResultsFirstPostDate]RANGE[2015-01-01, MAX]\n\nOperators:\n    EXPANSION[type]: Controls term expansion\n        - None: Exact match only, case and accent sensitive\n        - Term: Includes lexical variants (plurals, spellings)\n        - Concept: Includes UMLS synonyms\n        - Relaxation: Relaxes adjacency requirements (default)\n        - Lossy: Allows missing partial terms\n\n    COVERAGE[type]: Controls text matching\n        - FullMatch: Must match entire field\n        - StartsWith: Must match beginning of field\n        - EndsWith: Must match end of field\n        - Contains: Must match part of field (default)\n\n    AREA[field]: Specifies field to search\n        - See Field Reference for available fields\n\n    SEARCH[type]: Groups field searches\n        - Location: Groups location-related fields\n        - Study: Groups study-related fields\n\nUsage Notes:\n    - All search expressions are implicitly OR expressions\n    - Operator precedence (highest to lowest): terms/source operators, NOT/context operators, AND, OR\n    - Use quotes for exact phrase matching: \"heart attack\"\n    - Use parentheses for grouping: (heart OR cardiac) AND attack\n    - Use backslash to escape operators: \\AND\n    - Default expansion is EXPANSION[Relaxation]\n    - Default coverage is COVERAGE[Contains]\n\nField Reference:\n    High Priority Fields (weight >= 0.8):\n        - NCTId (1.0): Trial identifier\n        - Acronym (1.0): Study acronym\n        - BriefTitle (0.89): Short title\n        - OfficialTitle (0.85): Full official title\n        - Condition (0.81): Medical condition\n        - InterventionName (0.8): Primary intervention name\n        - OverallStatus: Trial status\n\n    Medium Priority Fields (0.5-0.79):\n        - InterventionOtherName (0.75): Alternative intervention names\n        - Phase (0.65): Trial phase\n        - StdAge (0.65): Standard age groups\n        - Keyword (0.6): Study keywords\n        - BriefSummary (0.6): Short description\n        - SecondaryOutcomeMeasure (0.5): Secondary outcomes\n\n    Low Priority Fields (< 0.5):\n        - DesignPrimaryPurpose (0.3): Primary purpose of study\n        - StudyType (0.3)\n        - Various descriptive, location, and administrative fields\n\nSupported Enums:\n    Phase:\n        - EARLY_PHASE1: Early Phase 1\n        - PHASE1: Phase 1\n        - PHASE2: Phase 2\n        - PHASE3: Phase 3\n        - PHASE4: Phase 4\n        - NA: Not Applicable\n\n    StandardAge:\n        - CHILD: Child\n        - ADULT: Adult\n        - OLDER_ADULT: Older Adult\n\n    Status:\n        - RECRUITING: Currently recruiting participants\n        - ACTIVE_NOT_RECRUITING: Active but not recruiting\n        - COMPLETED: Study completed\n        - ENROLLING_BY_INVITATION: Enrolling by invitation only\n        - NOT_YET_RECRUITING: Not yet recruiting\n        - SUSPENDED: Study suspended\n        - TERMINATED: Study terminated\n        - WITHDRAWN: Study withdrawn\n        - AVAILABLE: Available\n        - NO_LONGER_AVAILABLE: No longer available\n        - TEMPORARILY_NOT_AVAILABLE: Temporarily not available\n        - APPROVED_FOR_MARKETING: Approved for marketing\n        - WITHHELD: Withheld\n        - UNKNOWN: Unknown status\n\n    StudyType:\n        - INTERVENTIONAL: Interventional studies\n        - OBSERVATIONAL: Observational studies\n        - EXPANDED_ACCESS: Expanded access studies\n\n    PrimaryPurpose:\n        - TREATMENT: Treatment\n        - PREVENTION: Prevention\n        - DIAGNOSTIC: Diagnostic\n        - ECT: Educational/Counseling/Training\n        - SUPPORTIVE_CARE: Supportive Care\n        - SCREENING: Screening\n        - HEALTH_SERVICES_RESEARCH: Health Services Research\n        - BASIC_SCIENCE: Basic Science\n        - DEVICE_FEASIBILITY: Device Feasibility\n        - OTHER: Other\n\n    InterventionType:\n        - BEHAVIORAL: Behavioral interventions\n        - BIOLOGICAL: Biological interventions\n        - COMBINATION_PRODUCT: Combination product interventions\n        - DEVICE: Device interventions\n        - DIAGNOSTIC_TEST: Diagnostic test interventions\n        - DIETARY_SUPPLEMENT: Dietary supplement interventions\n        - DRUG: Drug interventions\n        - GENETIC: Genetic interventions\n        - PROCEDURE: Procedure interventions\n        - RADIATION: Radiation interventions\n        - OTHER: Other interventions\n\n    DesignAllocation:\n        - RANDOMIZED: Randomized allocation\n        - NON_RANDOMIZED: Non-randomized allocation\n        - NA: Not applicable\n\n    InterventionalAssignment:\n        - SINGLE_GROUP: Single group assignment\n        - PARALLEL: Parallel assignment\n        - CROSSOVER: Crossover assignment\n        - FACTORIAL: Factorial assignment\n        - SEQUENTIAL: Sequential assignment\n\n    ObservationalModel:\n        - COHORT: Cohort\n        - CASE_CONTROL: Case-Control\n        - CASE_ONLY: Case-Only\n        - CASE_CROSSOVER: Case-Crossover\n        - ECOLOGIC_OR_COMMUNITY: Ecologic or Community\n        - FAMILY_BASED: Family-Based\n        - DEFINED_POPULATION: Defined Population\n        - NATURAL_HISTORY: Natural History\n        - OTHER: Other\n\n    DesignMasking:\n        - NONE: None (Open Label)\n        - SINGLE: Single\n        - DOUBLE: Double\n        - TRIPLE: Triple\n        - QUADRUPLE: Quadruple\n\n    WhoMasked:\n        - PARTICIPANT: Participant\n        - CARE_PROVIDER: Care Provider\n        - INVESTIGATOR: Investigator\n        - OUTCOMES_ASSESSOR: Outcomes Assessor",
+                        "title": "Query",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "patent_search",
+                  "description": "Search for patents to increase the patent count.\n\nRepeat previous calls with the same query to continue a search.\nOnly repeat a maximum of three times.\nThis tool can be called concurrently.\nThis tool introduces novel patents, so invoke it when just beginning\nor when unsatisfied with the current evidence.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "A search query for patents (using Google Patents). Never include temporal\nfilters here (e.g. specific years or dates); instead use the `after` and `before`\narguments. Never include author filters here; instead use the `inventor` argument.\nSupports the following syntax, but they can be brittle and are not preferred; try\nsimple queries where possible:\n- Boolean operators: AND (default), OR, and - (NOT)\n- Exact phrases: \"quoted text\"\n- Proximity: NEAR/x, ADJ/x (ordered), WITH (20 words), SAME (200 words)\n- Field search: TI=(title), AB=(abstract), CL=(claims)\n- CPC codes: cpc:A01B or CPC=B60R22/low (includes children)\n- Wildcards: ? (0-1 char), * (0+ chars), # (exactly 1 char)\n- Chemistry: exact molecule names, SSS=molecule (substructure),\n  ~molecule (similar), SMILES strings, SMARTS=pattern, InChI keys,\n  CL=~molecule (chemistry in claims)",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "after": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Minimum patent date. Format: YYYYMMDD.\nExample: '20150101' for patents after Jan 1, 2015.",
+                        "title": "After"
+                      },
+                      "before": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Maximum patent date. Format: YYYYMMDD.\nExample: '20200101' for patents before Jan 1, 2020.",
+                        "title": "Before"
+                      },
+                      "date_type": {
+                        "default": "publication",
+                        "description": "Type of date that after and before refer to. Must be either 'publication'\nor 'filing'. Only necessary to set if after and/or before are set.",
+                        "title": "Date Type",
+                        "type": "string"
+                      },
+                      "inventor": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Filter by inventor name(s). Comma-separated for multiple.",
+                        "title": "Inventor"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "create_plan",
+                  "description": "Create a plan for to construct a thorough and accurate answer.\n\nDecompose the input task into a set of sub-objectives that need to\nbe met in order to form the answer. Subsequently, when working on solving\nthe query, you can focus on these objectives one by one. Note that the\n`update_plan` tool allows you to change the objectives if needed.\n\nIn addition to the objectives you deem necessary, add one final objective\nto call the `answer` tool with your final answer, so that you do not\nforget to submit your answer.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "plan_json": {
+                        "description": "A JSON string representing the plan. It should be a dictionary\nwith top-level key \"objectives\", whose value is a list of objectives.\nEach objective should be a dictionary with the following keys:\n- \"id\": (int) an integer id for the plan objective\n- \"objective\": (str) a human readable description of the objective's goal\n- \"rationale\": (str) a human readable rationale\n    describing why this objective is necessary and appropriate for the query.\n- \"status\": (str) updated task status, default to pending,\n    one of: pending, in-progress, or completed.\n    \"pending\" is yet to be started,\n    \"in-progress\" is the current objective being solved,\n    \"completed\" is successfully completed with acceptance criteria met.\n- \"result\": (str|None) The result of the objective, default to None.\n- \"evaluation\": (str|None) Description of why the objective result\n    meets the criteria for being complete. Default to None.",
+                        "title": "Plan Json",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "plan_json"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "update_plan",
+                  "description": "Update the plan for a specific or new objective using a JSON string to create or\nreplace the existing objective.\n\nThe updated_json should be a JSON string representing a single plan objective object.\n\nYou may use this tool to update an objective, create a new one, or change\nstrategy if the current plan is not working. Only change strategy significantly\nas a last resort, after trying very hard to make the current plan work.\n\nOnly mark an objective as completed if you are absolutely sure that it has been fully\nmet. If it is only partially met, you may add additional objectives to the plan for\nwhat is missing.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "plan_objective_id": {
+                        "description": "The id of the objective to update.",
+                        "title": "Plan Objective Id",
+                        "type": "integer"
+                      },
+                      "updated_plan_objective_json": {
+                        "description": "A JSON string representing the updated objective.\nIt should be a dictionary with the with the following keys:\n- \"id\": (int) an integer id matching plan_objective_id, if not found, a new objective is created.\n- \"objective\": (str) a human readable description of the objective's goal\n- \"rationale\": (str) a human readable rationale\n    describing why this objective is necessary and appropriate for the query.\n- \"status\": (str) updated task status, default to pending,\n    one of: pending, in-progress, or completed.\n    \"pending\" is yet to be started,\n    \"in-progress\" is the current objective being solved,\n    \"completed\" is successfully completed with acceptance criteria met.\n- \"result\": (str|None) The result of the objective, default to None.\n- \"evaluation\": (str|None) Description of why the objective result\n    meets the criteria for being complete. Default to None.",
+                        "title": "Updated Plan Objective Json",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "plan_objective_id",
+                      "updated_plan_objective_json"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "gather_evidence",
+                  "description": "Given a specific question, gather evidence from full-text of documents that have been retrieved by\nprevious tool calls.\n\nHere is how the tool works: the provided question is posed to all texts retrieved thus far\nby other tools. An LLM sees each text independently and is prompted to find information relevant\nto the question.\n\nThat is, we sample evidence `e \\sim LLM(prompt, text, q)` for each text. We only return pieces of\nevidence `e` that are sufficiently relevant to the question; if the text is irrelevant, then `e`\nis not included in the final response of this tool. Note that this LLM does not see the conversation\nhistory thus far, only the question and each text. Note that it only sees text, no images or other\nmedia from the contents (though tables and formulae may be parseable in some cases).\n\nThink of this tool as an efficient way to deeply scan all retrieved documents for evidence. It\nis complementary to the `read_text` tool, which can be used to directly inspect a subset of the\nretrieved documents.\n\nA valuable time to invoke this tool is after another tool finds potentially relevant documents.\nFeel free to invoke this tool in parallel with other tools, but do not call this tool in parallel with itself.\nOnly invoke this tool when the document count is above zero, or this tool will be useless.\n\nIf you call this tool 2+ times and repeatedly get 'No relevant evidence found',\nconsider whether the answer might be in visual content (figures/tables) rather than text,\nand use appropriate tools if available to access that content.\n\nOnce you receive evidence from this tool:\n\n1. Read Carefully: Don't skim. The evidence may contain multiple similar terms\n   or values\u2014make sure you identify the RIGHT one.\n\n2. For Comparative Questions: If the question asks \"which X has greatest Y\",\n   check that the evidence includes information about ALL relevant X options, not\n   just one or two. If you only see partial information, gather more evidence.\n\n3. Check for Noise: Verify that numbers or terms aren't just metadata\n   (page numbers, reference IDs, dates). Look for the value in meaningful\n   scientific context.\n\n4. Context Matters: A term appearing 71 times doesn't mean it's always the answer.\n   Verify which occurrence actually answers the question asked.\n\nIf the evidence doesn't clearly answer the question, gather more evidence before\nconcluding. Don't guess based on partial information.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "question": {
+                        "description": "Specific question to gather evidence for.",
+                        "title": "Question",
+                        "type": "string"
+                      },
+                      "text_name_focus_list": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "if there are known text names that are relevant to the question,\nyou can specify them here. This will ensure that the tool will look at these text names\nfirst, and then look at the rest of the evidence. If left as `None`, an embedding\nsearch will be performed on underlying content to find most relevant texts.",
+                        "title": "Text Name Focus List"
+                      }
+                    },
+                    "required": [
+                      "question"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "read_text",
+                  "description": "Given a list of text names, read their contents.\n\nThis tool is valuable to read the full contents of specific parts of documents,\ncomplementing the `gather_evidence` tool's indirect approach.\nThis can be an especially useful tool if `gather_evidence` does not find evidence,\nbut you think it is very likely that specific documents are still relevant to the question.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "text_name_list": {
+                        "description": "A list of up to 10 text names to read.\nThese text names can be any valid text names retrieved by other tools.",
+                        "items": {
+                          "type": "string"
+                        },
+                        "title": "Text Name List",
+                        "type": "array"
+                      }
+                    },
+                    "required": [
+                      "text_name_list"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "view_images",
+                  "description": "Retrieve images from a document.\n\nUse this tool when you need to see figures, tables, or other visual content.\nThe tool works by asking a weaker LLM agent to scan through the document, looking for\nvisual content matching the query you provide. When the agent finds matches, it will\ncrop the page to the relevant region. It can be tasked to return multiple images,\nif desired. Note that the weaker LLM may be worse at *understanding* images than\nyou, so double-check its conclusions about the returned images. It is also stateless,\ni.e. it will not remember what you have asked it to find in the past.\n\nUse this tool carefully. It is difficult to retrieve images, and the images\nthemselves will fill up your context window quickly. Here are some guidelines:\n1. ALWAYS use this tool if the question explicitly mentions 'Table X' or 'Figure Y'.\n   These questions require visual content and cannot be answered with text alone.\n2. Use this tool as a fallback when gather_evidence fails repeatedly (2+ times\n   returning 'No relevant evidence'). This suggests the answer may be in visual content.\n3. When gather_evidence returns text mentioning 'see Figure X' or 'shown in Table Y',\n   you should call this tool to examine that specific visual reference.\n4. Only call this tool after directly inspecting relevant text with read_text\n   to confirm the document likely contains the visual you need.\n5. Don't use this tool in a broad-spectrum way (don't call on many documents\n   just to see what might be relevant).\n6. Never call this tool in parallel with itself.\n7. Users like visual evidence, so call this tool at least once before answering so you\n   can provide some image citations in the answer. Add this to your plan so you do not forget.\n   For images to be presented to the user, they must be cited in the final answer after retrieval\n   by this tool. You may ignore this instruction if the request is for the question is asking\n   for a specific piece of information and is not an open-ended research question.\n8. NEVER cite full-page images in your final answer, unless they are full-page panels figures or\n   tables. Cite relevant cropped regions if available, otherwise consider calling this tool again\n   to find a smaller region that answers the query.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "Query to search for visual content in the document. If you know the specific\nfigure/table/formula you are looking for, you can specify it here (e.g. \"find me\nFigure 3\" or \"extract the table on page 10\"). You can also request based on content\n(e.g. \"find me all volcano plots of gene X\" or \"I need the formula for the growth rate\").\nYou can even include explicit instructions for the LLM agent to follow (if helpful, not\nnecessarily required). The more specific and clear your query is here, the higher the\nchance of success.",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "text_name": {
+                        "description": "Name of a text chunk (e.g., 'smith2023example pages 1-5').",
+                        "title": "Text Name",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "query",
+                      "text_name"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "answer",
+                  "description": "Submit your final answer to the user. You MUST call this tool on your final answer.\nIf you mark all objectives as completed but have not yet called this tool, then\nthe answer will not be submitted. Note that this tool should only be called once, as it\nimmediately terminates the run and submits the answer.\n\nWrite an answer based on the evidence from gather_evidence results in message history.\nIf the context provides insufficient information, provide a partial answer and explain\nwhy it is partial (e.g. the question is currently an open question in the field,\nyou were unable to obtain certain papers, etc.).\n\nFor each part of your answer, indicate which sources most support it via citation IDs at\nthe end of sentences, like (pqac-0000ABCD).\nYou are only allowed to cite available context IDs, indicated in previous messages by \"Context IDs that may be cited:\".\n## Valid citation examples, only use comma/space delimited parentheticals:\n\n- (pqac-0000ABCD, pqac-0000EFGH)\n- (pqac-0000IJKL)\n\n## Invalid citation examples:\n\n- (pqac-0000ABCD and pqac-0000EFGH)\n- (pqac-0000ABCD;pqac-0000EFGH)\n- (pqac-0000ABCD-pqac-0000EFGH)\n- pqac-0000ABCD and pqac-0000EFGH\n- Example's work pqac-0000ABCD\n- (pages pqac-0000ABCD)\n- ![description](pqac-0000ABCD)\n- ()\n\nDo not concatenate citation ids, just use them as-is.\n\nWhen writing your answer, embed artifacts if relevant artifacts have been previously\ncreated by the `create_artifact` tool. To embed an artifact, simply include this in your\nanswer, on its own line and without any additional formatting (i.e. no backticks, code fences,\nquotes, additional tags, etc.).\nAlways provide at least some introductory sentence or paragraph before referring to an artifact,\nso that the artifact is properly contextualized.\nHere is an example reference to an artifact with ID \"artifact-XY\":\n<artifact id=\"artifact-XY\"/>\n\nValid artifact IDs are indicated in previous messages by 'Artifact IDs that may be injected into the answer:'.\n\n\nDouble-check your answer:\n\n1. Evidence Match: Re-read the specific evidence snippets you're citing. Does your\n   answer actually match what they say? Don't rely on memory from 20+ messages ago.\n\n2. For Comparative Questions (\"which X has greatest/maximum/highest Y\"):\n   - Did you examine ALL options mentioned in the evidence?\n   - Did you explicitly compare their values?\n   - Example: If evidence mentions \"Pancreatic: 0.92, Liver: 0.85, Lung: 0.78\",\n     verify you compared all three, not just two.\n\n3. For Specific Value Questions (\"How many\", \"What is the\", specific terms):\n   - Does the exact value you're stating appear in the evidence?\n   - Are you extracting from the right context (not noise like page numbers)?\n\n4. Sanity Check: Read your answer. Does it directly address what was asked?\n\nDon't use Markdown image syntax like ![...](...) to reference media in your answer,\nbecause media get automatically linked by the system based on your answer's citations.\n\nWrite in the style of a scientific article, with concise sentences and\ncoherent paragraphs. This answer will be used directly,\nso do not add any extraneous information.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "answer": {
+                        "description": "valid answer, cited with citation IDs.",
+                        "title": "Answer",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "answer"
+                    ]
+                  }
+                }
+              }
+            ],
+            "messages": [
+              {
+                "role": "user",
+                "content": "Use the tools to answer the question: How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).\n\nStart by making a plan, and update the plan as you go. Your answer will be returned to the user when all plan objectives are completed. Be thorough and ensure your evidence matches the user's question.",
+                "info": null
+              },
+              {
+                "role": "assistant",
+                "content": "\n\nI'll create a comprehensive plan to address this multi-faceted question about the derivation of SEM-EDS acquisition parameters.",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01LwY3zgz1Vt5ca3jNesx7YK",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_json\": \"{\\n  \\\"objectives\\\": [\\n    {\\n      \\\"id\\\": 1,\\n      \\\"objective\\\": \\\"Research the ionization cross-section physics (Bethe formulation, Green & Cosslett measurements) and overvoltage ratio optimization, including competing effects from electron range (Kanaya-Okayama) and phi(rho-z) models (Castaing)\\\",\\n      \\\"rationale\\\": \\\"Need to trace the physics basis for the U0 ~ 2-3 recommendation\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 2,\\n      \\\"objective\\\": \\\"Research dead-time models (paralyzable/non-paralyzable) and the derivation of the 20-40% dead-time guidance for optimal throughput\\\",\\n      \\\"rationale\\\": \\\"Need to explain the counting-rate optimization that yields the dead-time recommendation\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 3,\\n      \\\"objective\\\": \\\"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\\\",\\n      \\\"rationale\\\": \\\"Need to explain the detector electronics basis for process time recommendations\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 4,\\n      \\\"objective\\\": \\\"Research Poisson counting statistics for precision (10^4 counts \\u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\\\",\\n      \\\"rationale\\\": \\\"Need to trace the statistical foundations of count-time and detection-limit recommendations\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 5,\\n      \\\"objective\\\": \\\"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\\\",\\n      \\\"rationale\\\": \\\"Need to distinguish genuine optima from committee conventions\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 6,\\n      \\\"objective\\\": \\\"Research low-voltage microanalysis (\\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\\\",\\n      \\\"rationale\\\": \\\"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\\u03b1 in AlSi10Mg at 5 kV\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 7,\\n      \\\"objective\\\": \\\"Create summary artifacts and submit final answer\\\",\\n      \\\"rationale\\\": \\\"Synthesize all findings into a comprehensive answer with proper citations\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    }\\n  ]\\n}\"}",
+                      "name": "create_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Plan registered and formatted correctly, with some modifications:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research the ionization cross-section physics (Bethe formulation, Green & Cosslett measurements) and overvoltage ratio optimization, including competing effects from electron range (Kanaya-Okayama) and phi(rho-z) models (Castaing)\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models (paralyzable/non-paralyzable) and the derivation of the 20-40% dead-time guidance for optimal throughput\",\n      \"rationale\": \"Need to explain the counting-rate optimization that yields the dead-time recommendation\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\",\n      \"rationale\": \"Need to explain the detector electronics basis for process time recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "create_plan",
+                "tool_call_id": "toolu_01LwY3zgz1Vt5ca3jNesx7YK",
+                "info": {
+                  "start_ts": 2536.116590445,
+                  "end_ts": 2536.119787929
+                }
+              },
+              {
+                "role": "assistant",
+                "content": null,
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01MNW17Avg6HRHVjWYkr5euV",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 1, \"updated_plan_objective_json\": \"{\\\"id\\\": 1, \\\"objective\\\": \\\"Research ionization cross-section physics and overvoltage ratio optimization\\\", \\\"rationale\\\": \\\"Need to trace the physics basis for the U0 ~ 2-3 recommendation\\\", \\\"status\\\": \\\"in-progress\\\", \\\"result\\\": null, \\\"evaluation\\\": null}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"in-progress\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models (paralyzable/non-paralyzable) and the derivation of the 20-40% dead-time guidance for optimal throughput\",\n      \"rationale\": \"Need to explain the counting-rate optimization that yields the dead-time recommendation\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\",\n      \"rationale\": \"Need to explain the detector electronics basis for process time recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01MNW17Avg6HRHVjWYkr5euV",
+                "info": {
+                  "start_ts": 2544.693267786,
+                  "end_ts": 2544.694202496
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Let me launch multiple parallel searches to efficiently gather evidence on all the key topics:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_011mGuD8hMcrUFocjkLDpN6U",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Bethe ionization cross-section overvoltage ratio electron probe microanalysis\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_01WewFbrkPCiA6LqG8T7fbrT",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Green Cosslett ionization cross-section electron bombardment X-ray production\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_01F9PtJgwBy482vzc38PHvS6",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Kanaya Okayama electron range penetration depth microanalysis\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_01JTZVfeVBDWDe4iq2ZzHCdN",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Castaing phi rho z depth distribution X-ray microanalysis tracer experiments\"}",
+                      "name": "paper_search"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Electron Probe Microanalysis: A Review of the Past, Present, and Future\nValid Text Names:\n'rinaldi2015electronprobemicroanalysis pages 1-2', 'rinaldi2015electronprobemicroanalysis pages 2-4', 'rinaldi2015electronprobemicroanalysis pages 4-5', 'rinaldi2015electronprobemicroanalysis pages 5-7', 'rinaldi2015electronprobemicroanalysis pages 7-8', 'rinaldi2015electronprobemicroanalysis pages 8-10', 'rinaldi2015electronprobemicroanalysis pages 10-12', 'rinaldi2015electronprobemicroanalysis pages 12-13', 'rinaldi2015electronprobemicroanalysis pages 13-14', 'rinaldi2015electronprobemicroanalysis pages 14-15', 'rinaldi2015electronprobemicroanalysis pages 15-16', 'rinaldi2015electronprobemicroanalysis pages 16-17'\n\nBibTex:\n@article{rinaldi2015electronprobemicroanalysis,\n    author = \"Rinaldi, Romano and Llovet, Xavier\",\n    title = \"Electron Probe Microanalysis: A Review of the Past, Present, and Future\",\n    year = \"2015\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"21\",\n    pages = \"1053-1069\",\n    month = \"May\",\n    doi = \"10.1017/s1431927615000409\",\n    url = \"https://doi.org/10.1017/s1431927615000409\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"5\",\n    issn = \"1431-9276\"\n}\n\n\nRelevant Snippet:\n\u2026 As an example, the effective ionization range of 20 keV electrons incident on a light matrix \u2026 the analysis at low over-voltage is the low count rates and peak-to-background ratios, which \u2026\n\n\nUnobtainable Papers:\nRod Packwood. A comprehensive theory of electron probe microanalysis. ArXiv, pages 83-104, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_6, doi:10.1007/978-1-4899-2617-3\\_6.\nKFJ Heinrich and D Newbury. Electron probe quantitation. ArXiv, Jan 2013. URL: https://doi.org/10.1007/978-1-4899-2617-3, doi:10.1007/978-1-4899-2617-3.\nKenji Murata, Masatoshi Kotera, and Koichi Nagami. Quantitative electron microprobe analysis of thin films on substrates with a new monte carlo simulation. Journal of Applied Physics, 54:1110-1114, Feb 1983. URL: https://doi.org/10.1063/1.332127, doi:10.1063/1.332127.\nPeter Duncumb. Quantitative analysis with the electron microprobe. the first 50 years and beyond. Journal of Analytical Atomic Spectrometry, 14:357-366, Jan 1999. URL: https://doi.org/10.1039/a807315e, doi:10.1039/a807315e.\nS.J.B reed. The present state of quantitative electron probe microanalysis. Reviews of Physics in Technology, 2:92-115, Oct 1971. URL: https://doi.org/10.1088/0034-6683/2/2/i02, doi:10.1088/0034-6683/2/2/i02.\nPeter Rez. Electron ionization cross sections for atomic subshells. Microscopy and Microanalysis, 9:42-53, Jan 2003. URL: https://doi.org/10.1017/s1431927603030083, doi:10.1017/s1431927603030083.\nC. J. Powell. Cross sections for ionization of inner-shell electrons by electrons. Reviews of Modern Physics, 48:33-47, Jan 1976. URL: https://doi.org/10.1103/revmodphys.48.33, doi:10.1103/revmodphys.48.33.\nG Love, M G Cox, and V D Scott. A versatile atomic number correction for electron-probe microanalysis. Journal of Physics D: Applied Physics, 11:7-21, Jan 1978. URL: https://doi.org/10.1088/0022-3727/11/1/004, doi:10.1088/0022-3727/11/1/004.\nH. Yakowitz. Methods of quantitative x-ray analysis used in electron probe microanalysis and scanning electron microscopy. ArXiv, pages 327-372, Jan 1975. URL: https://doi.org/10.1007/978-1-4613-4422-3\\_9, doi:10.1007/978-1-4613-4422-3\\_9.\nCedric J. Powell, Xavier Llovet, and Francesc Salvat. Use of the bethe equation for inner-shell ionization by electron impact. Journal of applied physics, May 2016. URL: https://doi.org/10.1063/1.4948700, doi:10.1063/1.4948700.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=4 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nV Horvat and R L Watson. Target-atom k-shell ionization by binary-encounter electrons. Journal of Physics B: Atomic, Molecular and Optical Physics, 34:777-786, Feb 2001. URL: https://doi.org/10.1088/0953-4075/34/5/307, doi:10.1088/0953-4075/34/5/307.\nC. Hombourger. An empirical expression for k-shell ionization cross section by electron impact. Journal of Physics B, 31:3693-3702, Aug 1998. URL: https://doi.org/10.1088/0953-4075/31/16/020, doi:10.1088/0953-4075/31/16/020.\nM Green and V E Cosslett. The efficiency of production of characteristic x-radiation in thick targets of a pure element. ArXiv, 78:1206-1214, Dec 1961. URL: https://doi.org/10.1088/0370-1328/78/6/315, doi:10.1088/0370-1328/78/6/315.\nK. Shima, M. Okuda, E. Suzuki, T. Tsubota, and T. Mikumo. L\u03b1 x\u2010ray production efficiency from z=50\u201382 thick target elements by electron impacts from threshold energy to 30 kev. Journal of Applied Physics, 54:1202-1208, Mar 1983. URL: https://doi.org/10.1063/1.332200, doi:10.1063/1.332200.\nStephen M. Seltzer. Cross sections for bremsstrahlung production and electron-impact ionization. ArXiv, 38:81-114, Jan 1988. URL: https://doi.org/10.1007/978-1-4613-1059-4\\_4, doi:10.1007/978-1-4613-1059-4\\_4.\nD. B. Brown and R. E. Ogilvie. Efficiency of production of characteristic x radiation from pure elements bombarded by electrons. Journal of Applied Physics, 35:309-314, Feb 1964. URL: https://doi.org/10.1063/1.1713305, doi:10.1063/1.1713305.\nH. V. Rahangdale, M. Guerra, P. K. Das, S. De, J. P. Santos, D. Mitra, and S. Saha. Determination of subshell-resolved l-shell-ionization cross sections of gold induced by 15-40-kev electrons. Physical Review A, 89:052708, May 2014. URL: https://doi.org/10.1103/physreva.89.052708, doi:10.1103/physreva.89.052708.\nChanghuan Tang, Zhengming Luo, Zhu An, Fuqing He, Xiufeng Peng, and Xianguan Long. The atomic k- and l-shell ionization cross-sections by electron impact. ArXiv, pages 233-236, Jan 2002. URL: https://doi.org/10.1007/978-1-4419-8696-2\\_41, doi:10.1007/978-1-4419-8696-2\\_41.\nM. Green. A monte carlo calculation of the spatial distribution of characteristic x-ray production in a solid target. ArXiv, 82:204-215, Aug 1963. URL: https://doi.org/10.1088/0370-1328/82/2/307, doi:10.1088/0370-1328/82/2/307.\nChanghuan Tang, Zhu An, Zhengming Luo, and Mantian Liu. Measurements of germanium <i>k</i>-shell ionization cross sections and tin <i>l</i>-shell x-ray production cross sections by electron impact. May 2002. URL: https://doi.org/10.1063/1.1470248, doi:10.1063/1.1470248.\nXavier Llovet, Cedric J. Powell, Francesc Salvat, and Aleksander Jablonski. Cross sections for inner-shell ionization by electron impact. Journal of Physical and Chemical Reference Data, 43:013102, Jan 2014. URL: https://doi.org/10.1063/1.4832851, doi:10.1063/1.4832851.\nChang-huan Tang, Zheng-ming Luo, Zhu An, and Tai-hua Li. Measurement of zinc k-shell ionization cross sections by electron impact. Chinese Physics Letters, 16:505-507, Jul 1999. URL: https://doi.org/10.1088/0256-307x/16/7/013, doi:10.1088/0256-307x/16/7/013.\nR. Akselsson and T. B. Johansson. X-ray production by 1.5\u201311 mev protons. Zeitschrift f\u00fcr Physik, 266:245-255, Aug 1974. URL: https://doi.org/10.1007/bf01668816, doi:10.1007/bf01668816.\nM Green and V E Cosslett. Measurements of k, l and m shell x-ray production efficiencies. Journal of Physics D: Applied Physics, 1:425-436, Apr 1968. URL: https://doi.org/10.1088/0022-3727/1/4/303, doi:10.1088/0022-3727/1/4/303.\nSilvina P. Limandri, M. A. Z. Vasconcellos, Ruth Hinrichs, and Jorge C. Trincavelli. Experimental determination of cross sections for k-shell ionization by electron impact for c, o, al, si, and ti. Physical Review A, 86:042701, Oct 2012. URL: https://doi.org/10.1103/physreva.86.042701, doi:10.1103/physreva.86.042701.\nN A Dyson. The production of characteristic x-rays by proton bombardment, and the ratio of characteristic to continuous radiation. Journal of Physics B, 6:562-572, Mar 1973. URL: https://doi.org/10.1088/0022-3700/6/3/025, doi:10.1088/0022-3700/6/3/025.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=4 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_01WewFbrkPCiA6LqG8T7fbrT",
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+                  "start_ts": 2555.227472424,
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+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nSusumu Imashuku and Issei Narita. Effect of secondary fluorescence in thin\u2010film thickness on compositional determination using electron probe microanalysis. X-Ray Spectrometry, 55:184-189, Sep 2026. URL: https://doi.org/10.1002/xrs.70040, doi:10.1002/xrs.70040.\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Backscattered Electrons, pages 15-28. Springer New York, Nov 2017. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_2, doi:10.1007/978-1-4939-6676-9\\_2.\nYugo Kubo and Kotaro Hamada. Combination of high spatial resolution and low minimum detection limit using thinned specimens in cutting-edge electron probe microanalysis. Ultramicroscopy, 157:48-56, Oct 2015. URL: https://doi.org/10.1016/j.ultramic.2015.05.019, doi:10.1016/j.ultramic.2015.05.019.\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Low beam energy sem. ArXiv, pages 165-172, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_11, doi:10.1007/978-1-4939-6676-9\\_11.\nK. Kanaya and S. Ono. The energy dependence of a diffusion model of an electron probe into solid targets. Journal of Physics D, 11:1495-1498, Aug 1978. URL: https://doi.org/10.1088/0022-3727/11/11/008, doi:10.1088/0022-3727/11/11/008.\nTakahiro Nishihata, Mayuka Osaki, Maki Tanaka, Takuma Yamamoto, Akira Hamaguchi, Chihiro Ida, and Yusaku Suzuki. Depth measurement technique for extremely deep holes using back-scattered electron images with high voltage cd-sem. Metrology, Inspection, and Process Control for Microlithography XXXIII, 10959:109591B-109591B-9, Mar 2019. URL: https://doi.org/10.1117/12.2514799, doi:10.1117/12.2514799.\nMakoto Suzuki, Kazuhiro Kumagai, Takashi Sekiguchi, Alan M. Cassell, Tsutomu Saito, and Cary Y. Yang. Secondary electron emission from freely supported nanowires. Journal of Applied Physics, 104:114306, Dec 2008. URL: https://doi.org/10.1063/1.3032910, doi:10.1063/1.3032910.\nLai Chin Yung and Cheong Choke Fei. Verification of the thin film metal layer thickness by energy dispersive x-ray. 2015 IEEE Regional Symposium on Micro and Nanoelectronics (RSM), pages 1-4, Dec 2015. URL: https://doi.org/10.1109/rsm.2015.7355004, doi:10.1109/rsm.2015.7355004.\nJ. Seiter, Erich A. M\u00fcller, H. Blank, Helge Gehrke, Doris Marko, and D. Gerthsen. Backscattered electron sem imaging of cells and determination of the information depth. Journal of Microscopy, 254:75-83, May 2014. URL: https://doi.org/10.1111/jmi.12120, doi:10.1111/jmi.12120.\nMakoto Suzuki. Image formation mechanisms of scanning electron microscopy for characterization of nanoscale materials. Jan 2009. URL: https://doi.org/10.13140/2.1.1120.5765, doi:10.13140/2.1.1120.5765.\nMitsuo Suga and Yusuke Hirabayashi. Physical basics of scanning electron microscopy in volume electron microscopy. Microscopy, 74:201-214, Mar 2025. URL: https://doi.org/10.1093/jmicro/dfaf016, doi:10.1093/jmicro/dfaf016.\nK. Fleischer, M. Toth, M. Phillips, Jin Zou, Guoliang Li, and S. Chua. Depth profiling of gan by cathodoluminescence microanalysis. Feb 1999. URL: https://doi.org/10.1063/1.123460, doi:10.1063/1.123460.\nYuji Tanaka, Takako Yamashita, and Masayasu Nagoshi. Quantitative fe-epma measurement of formation and inhibition of carbon contamination on fe for trace carbon analysis. Microscopy, 66 2:68-77, Nov 2017. URL: https://doi.org/10.1093/jmicro/dfw102, doi:10.1093/jmicro/dfw102.\nK. Kanaya and S. Okayama. Penetration and energy-loss theory of electrons in solid targets. Journal of Physics D, 5:43-58, Jan 1972. URL: https://doi.org/10.1088/0022-3727/5/1/308, doi:10.1088/0022-3727/5/1/308.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=4 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Quantitative Measurement of Iron-Silicides by EPMA Using the Fe L\u03b1 and L\u03b2 X-ray Lines: A New Twist to an Old Approach\nValid Text Names:\n'moy2019quantitativemeasurementof pages 1-2', 'moy2019quantitativemeasurementof pages 2-3', 'moy2019quantitativemeasurementof pages 3-4', 'moy2019quantitativemeasurementof pages 4-5', 'moy2019quantitativemeasurementof pages 5-6', 'moy2019quantitativemeasurementof pages 6-7', 'moy2019quantitativemeasurementof pages 7-9', 'moy2019quantitativemeasurementof pages 9-10', 'moy2019quantitativemeasurementof pages 10-11', 'moy2019quantitativemeasurementof pages 10-10'\n\nBibTex:\n@article{moy2019quantitativemeasurementof,\n    author = \"Moy, Aur\u00e9lien and Fournelle, John and von der Handt, Anette\",\n    title = \"Quantitative Measurement of Iron-Silicides by EPMA Using the Fe L\u03b1 and L\u03b2 X-ray Lines: A New Twist to an Old Approach\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"664-674\",\n    month = \"Apr\",\n    doi = \"10.1017/s1431927619000436\",\n    url = \"https://doi.org/10.1017/s1431927619000436\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"3\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nAbstract The recent availability of Schottky-type field emission electron microprobes provides incentive to consider analyzing micrometer-sized features. Yet, to quantify sub-micrometer-sized features, the electron interaction volume must be reduced by decreasing accelerating voltage. However, the K lines of the transition elements (e.g., Fe) then cannot be excited, and the L lines must be used. The Fe L\u03b11,2 line is the most intense of the L series but bonding effects change its atomic parameters because it involves a valence band electron transition. For successful traditional electron probe microanalysis, the mass absorption coefficient (MAC) must be accurately known, but the MAC of Fe L\u03b11,2 radiation by Fe atoms varies from one Fe-compound to another and is not well known. We show that the conventional method of measuring the MAC by an electron probe cannot be used in close proximity to absorption edges, making its accurate determination impossible. Fortunately, we demonstrate, using a set of Fe\u2013silicide compounds, that it is possible to derive an accurate calibration curve, for a given accelerating voltage and takeoff angle, which can be used to quantify Fe in Fe\u2013silicide compounds. The calibration curve can be applied to any spectrometer without calibration and gives accurate quantification results.\n\nRelevant Snippet:\n\u2026 -called phi-rho-Z function that represents the ionization depth \u2026 by Castaing mainly consists of measuring the X-ray intensity \u2026 and for a given experimental setup. The concentration of the \u2026\n\n\n---\n\n## 2. Quantitative Speciation of Heavy Metals in Soils and Sediments by Synchrotron X-ray Techniques\nValid Text Names:\n'manceau2002quantitativespeciationof pages 6-9', 'manceau2002quantitativespeciationof pages 9-11', 'manceau2002quantitativespeciationof pages 15-18', 'manceau2002quantitativespeciationof pages 18-20', 'manceau2002quantitativespeciationof pages 20-23', 'manceau2002quantitativespeciationof pages 23-25', 'manceau2002quantitativespeciationof pages 25-27', 'manceau2002quantitativespeciationof pages 31-31', 'manceau2002quantitativespeciationof pages 33-36', 'manceau2002quantitativespeciationof pages 36-39', 'manceau2002quantitativespeciationof pages 39-42', 'manceau2002quantitativespeciationof pages 42-44', 'manceau2002quantitativespeciationof pages 47-49', 'manceau2002quantitativespeciationof pages 52-55', 'manceau2002quantitativespeciationof pages 57-59', 'manceau2002quantitativespeciationof pages 59-61', 'manceau2002quantitativespeciationof pages 66-68', 'manceau2002quantitativespeciationof pages 68-70', 'manceau2002quantitativespeciationof pages 75-76', 'manceau2002quantitativespeciationof pages 79-81', 'manceau2002quantitativespeciationof pages 81-83', 'manceau2002quantitativespeciationof pages 83-84', 'manceau2002quantitativespeciationof pages 84-86', 'manceau2002quantitativespeciationof pages 86-88', 'manceau2002quantitativespeciationof pages 88-88'\n\nBibTex:\n@article{manceau2002quantitativespeciationof,\n    author = \"Manceau, A. and Marcus, M. A. and Tamura, N.\",\n    title = \"Quantitative Speciation of Heavy Metals in Soils and Sediments by Synchrotron X-ray Techniques\",\n    year = \"2002\",\n    journal = \"Reviews in Mineralogy \\& Geochemistry\",\n    volume = \"49\",\n    pages = \"341-428\",\n    doi = \"10.2138/gsrmg.49.1.341\",\n    url = \"https://doi.org/10.2138/gsrmg.49.1.341\",\n    month = \"Jan\",\n    publisher = \"Mineralogical Society of America\",\n    issue = \"1\",\n    issn = \"1529-6466\"\n}\n\n\nRelevant Snippet:\n\u2026 at the molecular level how trace metals interact and are sequestered \u2026 X-ray microdiffraction to study the mineral composition and \u2026 experiment measures the variation of a material\u2019s X-ray \u2026\n\n\n---\n\n## 3. Petrographic Microscopy with Ray Tracing and Segmentation from Multi-Angle Polarisation Whole-Slide Images\nValid Text Names:\n'zamora2023petrographicmicroscopywith pages 1-2', 'zamora2023petrographicmicroscopywith pages 2-3', 'zamora2023petrographicmicroscopywith pages 3-6', 'zamora2023petrographicmicroscopywith pages 6-9', 'zamora2023petrographicmicroscopywith pages 9-11', 'zamora2023petrographicmicroscopywith pages 11-12', 'zamora2023petrographicmicroscopywith pages 12-17', 'zamora2023petrographicmicroscopywith pages 17-19', 'zamora2023petrographicmicroscopywith pages 19-22', 'zamora2023petrographicmicroscopywith pages 22-25', 'zamora2023petrographicmicroscopywith pages 25-27', 'zamora2023petrographicmicroscopywith pages 27-29', 'zamora2023petrographicmicroscopywith pages 29-31', 'zamora2023petrographicmicroscopywith pages 31-33', 'zamora2023petrographicmicroscopywith pages 33-35', 'zamora2023petrographicmicroscopywith pages 35-36', 'zamora2023petrographicmicroscopywith pages 36-37'\n\nBibTex:\n@article{zamora2023petrographicmicroscopywith,\n    author = \"Zamora, Marco Andres Acevedo and Kamber, Balz Samuel\",\n    title = \"Petrographic Microscopy with Ray Tracing and Segmentation from Multi-Angle Polarisation Whole-Slide Images\",\n    year = \"2023\",\n    journal = \"Minerals\",\n    month = \"Jan\",\n    doi = \"10.3390/min13020156\",\n    url = \"https://doi.org/10.3390/min13020156\",\n    volume = \"13\",\n    pages = \"156\",\n    publisher = \"MDPI AG\",\n    issue = \"2\",\n    issn = \"2075-163X\"\n}\n\n\nAbstract:\n\u2018Slide scanners\u2019 are rapid optical microscopes equipped with automated and accurate x-y travel stages with virtual z-motion that cannot be rotated. In biomedical microscopic imaging, they are widely deployed to generate whole-slide images (WSI) of tissue samples in various modes of illumination. The availability of WSI has motivated the development of instrument-agnostic advanced image analysis software, helping drug development, pathology, and many other areas of research. Slide scanners are now being modified to enable polarised petrographic microscopy by simulating stage rotation with the acquisition of multiple rotation angles of the polariser\u2013analyser pair for observing randomly oriented anisotropic materials. Here we report on the calibration strategy of one repurposed slide scanner and describe a pilot image analysis pipeline designed to introduce the wider audience to the complexity of performing computer-assisted feature recognition on mineral groups. The repurposed biological scanner produces transmitted light plane- and cross-polarised (TL-PPL and XPL) and unpolarised reflected light (RL) WSI from polished thin sections or slim epoxy mounts at various magnifications, yielding pixel dimensions from ca. 2.7 \u00d7 2.7 to 0.14 \u00d7 0.14 \u00b5m. A data tree of 14 WSI is regularly obtained, containing two RL and six of each PPL and XPL WSI (at 18\u00b0 rotation increments). This pyramidal image stack is stitched and built into a local server database simultaneously with acquisition. The pyramids (multi-resolution \u2018cubes\u2019) can be viewed with freeware locally deployed for teaching petrography and collaborative research. The main progress reported here concerns image analysis with a pilot open-source software pipeline enabling semantic segmentation on petrographic imagery. For this purpose, all WSI are post-processed and aligned to a \u2018fixed\u2019 reflective surface (RL), and the PPL and XPL stacks are then summarised in one image, each with ray tracing that describes visible light reflection, absorption, and O- and E-wave interference phenomena. The maximum red-green-blue values were found to best overcome the limitation of refractive index anisotropy for segmentation based on pixel-neighbouring feature maps. This strongly reduces the variation in dichroism in PPL and interference colour in XPL. The synthetic ray trace WSI is then combined with one RL to estimate modal mineralogy with multi-scale algorithms originally designed for object-based cell segmentation in pathological tissues. This requires generating a small number of polygonal expert annotations that inform a training dataset, enabling on-the-fly machine learning classification into mineral classes. The accuracy of the approach was tested by comparison with modal mineralogy obtained by energy-dispersive spectroscopy scanning electron microscopy (SEM-EDX) for a suite of rocks of simple mineralogy (granulites and peridotite). The strengths and limitations of the pixel-based classification approach are described, and phenomena from sample preparation imperfections to semantic segmentation artefacts around fine-grained minerals and/or of indiscriminate optical properties are discussed. Finally, we provide an outlook on image analysis strategies that will improve the status quo by using the first-pass mineralogy identification from optical WSI to generate a location grid to obtain targeted chemical data (e.g., by SEM-EDX) and by considering the rock texture.\n\nRelevant Snippet:\n\u2026 The synthetic ray trace WSI is then combined with one RL to \u2026 methods and energy-dispersive X-ray analysis with electron \u2026 The aim of this study was to conduct experiments to improve \u2026\n\n\nUnobtainable Papers:\nDing Ze-jun and Wu Zi-qin. Monte carlo calculation of x-ray depth profiles in si substrate coated with films. Journal of Physics D, 27:387-392, Feb 1994. URL: https://doi.org/10.1088/0022-3727/27/2/031, doi:10.1088/0022-3727/27/2/031.\nG Love, M G C Cox, and V D Scott. A simple monte carlo method for simulating electron-solid interactions and its application to electron probe microanalysis. Journal of Physics D, 10:7-23, Jan 1977. URL: https://doi.org/10.1088/0022-3727/10/1/002, doi:10.1088/0022-3727/10/1/002.\nP Van Espen. Electron Probe X-ray Microanalysis, pages 247-274. Routledge, Jul 2017. URL: https://doi.org/10.1201/9780203741528-11, doi:10.1201/9780203741528-11.\nKaustubh N. Kulkarni, Aparna Tripathi, Abhinav Varshney, Jyoti Chandra, Siva Kumar, Sandeep Sangal, Debajyoti Paul, and Kallol Mondal. Electron probe micro-analyzer: an equipment for accurate and precise micro-composition analysis. Electron Microscopy in Science and Engineering, pages 71-93, Jan 2022. URL: https://doi.org/10.1007/978-981-16-5101-4\\_6, doi:10.1007/978-981-16-5101-4\\_6.\nPeter Karduck and Werner Rehbach. The use of tracer experiments and monte carlo calculations in the \u03c6(\u03c1z) determination for electron probe microanalysis. ArXiv, pages 191-217, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_11, doi:10.1007/978-1-4899-2617-3\\_11.\nXavier Llovet and Claude Merlet. Electron probe microanalysis of thin films and multilayers using the computer program xfilm. Microscopy and Microanalysis, 16:21-32, Dec 2010. URL: https://doi.org/10.1017/s1431927609991218, doi:10.1017/s1431927609991218.\nJean-Louis Pouchou. X-ray microanalysis of stratified specimens. Analytica Chimica Acta, 283:81-97, Nov 1993. URL: https://doi.org/10.1016/0003-2670(93)85212-3, doi:10.1016/0003-2670(93)85212-3.\nJohn J. Friel and Charles E. Lyman. Tutorial review: x-ray mapping in electron-beam instruments. Microscopy and Microanalysis, 12:2-25, Jan 2006. URL: https://doi.org/10.1017/s1431927606060211, doi:10.1017/s1431927606060211.\nH. Demers and R. Gauvin. Evaluation of analytical models and monte carlo programs with experimental phi-rho-z depth distribution for quantitative microanalysis. Microscopy and Microanalysis, 18:1050-1051, Jul 2012. URL: https://doi.org/10.1017/s1431927612007106, doi:10.1017/s1431927612007106.\nD. A. Sewell, G. Love, and V. Scott. Universal correction procedure for electron-probe microanalysis. i. measurement of x-ray depth distributions in solids. Journal of Physics D, 18:1233-1243, Jul 1985. URL: https://doi.org/10.1088/0022-3727/18/7/010, doi:10.1088/0022-3727/18/7/010.\nKurt F. J. Heinrich. Strategies of electron probe data reduction. ArXiv, pages 9-18, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_2, doi:10.1007/978-1-4899-2617-3\\_2.\nEric Lifshin. In the beginning \u2013 a quick look at the origins of quantitative electron microprobe analysis and the need for monte carlo modeling. Microscopy and Microanalysis, 29:478-479, Jul 2023. URL: https://doi.org/10.1093/micmic/ozad067.226, doi:10.1093/micmic/ozad067.226.\nDing Ze-Jun and Wu Ziqin. A comparison of monte carlo simulations of electron scattering and x-ray production in solids. Journal of Physics D: Applied Physics, 26:507-516, Apr 1993. URL: https://doi.org/10.1088/0022-3727/26/4/001, doi:10.1088/0022-3727/26/4/001.\nIan McNulty, Barry Lai, J\u00f6rg Maser, David J. Paterson, Paul Evans, Steve M. Heald, Gene E. Ice, Eric D. Isaacs, Mark L. Rivers, and Stephen R. Sutton. X\u2010ray microscopy at the advanced photon source. Synchrotron Radiation News, 16:34-42, Jul 2003. URL: https://doi.org/10.1080/08940880308603031, doi:10.1080/08940880308603031.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=4 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nP. Zambon, J. J. P. Peters, and L. Jones. The dynamic retrigger concept: enhancing count rate performance in nonparalyzable x-ray and electron counting detectors. IEEE Transactions on Nuclear Science, 73(3):745-753, Mar 2026. URL: https://doi.org/10.1109/tns.2026.3659949, doi:10.1109/tns.2026.3659949.\nB. A. Sobott, Ch. Broennimann, B. Schmitt, P. Trueb, M. Schneebeli, V. Lee, D. J. Peake, S. Elbracht-Leong, A. Schubert, N. Kirby, M. J. Boland, C. T. Chantler, Z. Barnea, and R. P. Rassool. Success and failure of dead-time models as applied to hybrid pixel detectors in high-flux applications. Journal of Synchrotron Radiation, 20:347-354, Jan 2013. URL: https://doi.org/10.1107/s0909049513000411, doi:10.1107/s0909049513000411.\nMohamed S. El_Tokhy, Sergey Rozovs, Alexey Lubashevskiy, H. Kasban, and Elsayed H. Ali. Optimization of dead time correction for digital gamma ray spectroscopy based on social spider algorithm. Sep 2025. URL: https://doi.org/10.1016/j.nucana.2025.100183, doi:10.1016/j.nucana.2025.100183.\nWilliam C. Barber, Einar Nygard, Jan S. Iwanczyk, Mengxi Zhang, Eric C. Frey, Benjamin M. W. Tsui, Jan C. Wessel, Nail Malakhov, Gregor Wawrzyniak, Neal E. Hartsough, Thulasi Gandhi, and Katsuyuki Taguchi. Characterization of a novel photon counting detector for clinical ct: count rate, energy resolution, and noise performance. SPIE Proceedings, Feb 2009. URL: https://doi.org/10.1117/12.813915, doi:10.1117/12.813915.\nRasool Safari, Mohammadreza Parishan, Zahra Rakeb, and Reza Faghihi. Two sequential compton scatters method: a new method for radiation detector dead-time measurement. Jul 2026. URL: https://doi.org/10.1016/j.radmeas.2026.107705, doi:10.1016/j.radmeas.2026.107705.\nPeter Kappen, Jeremy Wykes, and Bernt Johannessen. Nonlinearities in solid-state fluorescence detectors, pages 528-536. International Union of Crystallography, Nov 2024. URL: https://doi.org/10.1107/s1574870720012240, doi:10.1107/s1574870720012240.\nRasool Safari, Mohammadreza Parishan, Zahra Rakeb, and reza faghihi. Double compton method: a new method for radiation detector dead time measurement using double compton scattering. Unknown journal, Jan 2025. URL: https://doi.org/10.2139/ssrn.5703276, doi:10.2139/ssrn.5703276.\nCinzia De cesare. FPGA-based algorithms for the stability improvement of high-flux X-ray spectrometric imaging detectors. PhD thesis, Agence Bibliographique de l\u2019Enseignement Sup\u00e9rieur, Oct 2018. URL: https://doi.org/10.70675/5c4e73f7z5331z43fczb765z54dfa912e395, doi:10.70675/5c4e73f7z5331z43fczb765z54dfa912e395.\nP. Zambon. Dead time model for x-ray photon counting detectors with retrigger capability. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 994:165087, Apr 2021. URL: https://doi.org/10.1016/j.nima.2021.165087, doi:10.1016/j.nima.2021.165087.\nLei Pan, Yihui He, Vladislav V. Klepov, Michael C. De Siena, and Mercouri G. Kanatzidis. Perovskite cspbbr<sub>3</sub> single crystal detector for high flux x-ray photon counting. Nov 2022. URL: https://doi.org/10.1109/tmi.2022.3176801, doi:10.1109/tmi.2022.3176801.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=16 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Detection and quantification limits: origins and historical overview1Adapted from the Proceedings of the 1996 Joint Statistical Meetings (American Statistical Association, 1997). Original title: \u201cFoundations and future of detection and quantification limits\u201d. Contribution of the National Institute of Standards and Technology; not subject to copyright.1\nValid Text Names:\n'currie1999detectionandquantification pages 1-2', 'currie1999detectionandquantification pages 2-4', 'currie1999detectionandquantification pages 4-6', 'currie1999detectionandquantification pages 6-7', 'currie1999detectionandquantification pages 7-8'\n\nBibTex:\n@misc{currie1999detectionandquantification,\n    author = \"Currie, Lloyd A.\",\n    title = \"Detection and quantification limits: origins and historical overview1Adapted from the Proceedings of the 1996 Joint Statistical Meetings (American Statistical Association, 1997). Original title: \u201cFoundations and future of detection and quantification limits\u201d. Contribution of the National Institute of Standards and Technology; not subject to copyright.1\",\n    year = \"1999\",\n    journal = \"Analytica Chimica Acta\",\n    volume = \"391\",\n    pages = \"127-134\",\n    month = \"May\",\n    doi = \"10.1016/s0003-2670(99)00105-1\",\n    url = \"https://doi.org/10.1016/s0003-2670(99)00105-1\",\n    publisher = \"Elsevier BV\",\n    issue = \"2\",\n    issn = \"0003-2670\"\n}\n\n\nRelevant Snippet:\n\u2026 hypothesis testing approach to detection decisions and limits \u2026 attached to the expression \u201cdetection limit\u201d led to numerical \u2026 detection test, \u03c3 0 is required to calculate the detection limit. \u2026\n\n\nUnobtainable Papers:\nL.A. Currie. Lower limit of detection: definition and elaboration of a proposed position for radiological effluent and environmental measurements. ArXiv, Sep 1984. URL: https://doi.org/10.2172/6411049, doi:10.2172/6411049.\nL. A. Currie. Nomenclature in evaluation of analytical methods including detection and quantification capabilities (iupac recommendations 1995). Pure and Applied Chemistry, 67:1699-1723, Jan 1995. URL: https://doi.org/10.1351/pac199567101699, doi:10.1351/pac199567101699.\nLloyd A. Currie. Detection capabilities: some historical footnotes. Journal of Radioanalytical and Nuclear Chemistry, 311:1099-1109, Feb 2017. URL: https://doi.org/10.1007/s10967-016-4925-z, doi:10.1007/s10967-016-4925-z.\nLloyd A. Currie. Detection: overview of historical, societal, and technical issues. ArXiv, pages 1-62, Dec 1988. URL: https://doi.org/10.1021/bk-1988-0361.ch001, doi:10.1021/bk-1988-0361.ch001.\nThomas M. Semkow, Xin Li, and Liang T. Chu. Overview of signal detection theory and detection limits. Detection Limits in Air Quality and Environmental Measurements, pages 60-77, Nov 2019. URL: https://doi.org/10.1520/stp161820180061, doi:10.1520/stp161820180061.\nL. A. Currie. On the detection of rare, and moderately rare, nuclear events. Journal of Radioanalytical and Nuclear Chemistry, 276:285-297, May 2008. URL: https://doi.org/10.1007/s10967-008-0501-5, doi:10.1007/s10967-008-0501-5.\nLloyd A. Currie and Robert M. Parr. Perspectives on detection limits: for nuclear measurements in selected national and international programs. ArXiv, pages 171-193, Dec 1987. URL: https://doi.org/10.1021/bk-1988-0361.ch009, doi:10.1021/bk-1988-0361.ch009.\nLloyd A. Currie. Limits for qualitative detection and quantitative determination. application to radiochemistry. Analytical Chemistry, 40:586-593, Mar 1968. URL: https://doi.org/10.1021/ac60259a007, doi:10.1021/ac60259a007.\nDonald A. Chambless, Stephanie S. Dubose, and Edwin L. Sensintaffar. Detection limit concepts: foundations, myths, and utilization. Health Physics, 63:338\u2013340, Sep 1992. URL: https://doi.org/10.1097/00004032-199209000-00010, doi:10.1097/00004032-199209000-00010.\nJ.M. Kirkpatrick, W. Russ, R. Venkataraman, and B.M. Young. Calculation of the detection limit in radiation measurements with systematic uncertainties. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 784:306-310, Jun 2015. URL: https://doi.org/10.1016/j.nima.2015.01.005, doi:10.1016/j.nima.2015.01.005.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=16 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Exploring the limits of EDS microanalysis: rare earth element analyses\nValid Text Names:\n'ritchie2018exploringthelimits pages 1-4', 'ritchie2018exploringthelimits pages 4-5', 'ritchie2018exploringthelimits pages 5-7', 'ritchie2018exploringthelimits pages 7-9', 'ritchie2018exploringthelimits pages 9-11', 'ritchie2018exploringthelimits pages 11-11'\n\nBibTex:\n@article{ritchie2018exploringthelimits,\n    author = \"Ritchie, N W M and Newbury, D E and Lowers, H and Mengason, M\",\n    title = \"Exploring the limits of EDS microanalysis: rare earth element analyses\",\n    year = \"2018\",\n    journal = \"IOP Conference Series: Materials Science and Engineering\",\n    volume = \"304\",\n    pages = \"012013\",\n    month = \"Aug\",\n    doi = \"10.1088/1757-899x/304/1/012013\",\n    url = \"https://doi.org/10.1088/1757-899x/304/1/012013\",\n    publisher = \"IOP Publishing\",\n    issn = \"1757-8981\"\n}\n\n\nAbstract:\nIt is a great time to be a microanalyst. After a few decades of incremental progress in energy-dispersive X-ray spectrometry (EDS), the last decade has seen the accuracy and precision surge forward. Today, the question is not whether EDS is generally useful but to identify the types of problems for which wavelength-dispersive X-ray spectrometry remains the better choice. The full extent of EDS\u2019s capabilities has surprised many. Low Z, low energy, and trace element detection have been demonstrated even in the presence of extreme peak interferences. In this paper, we will summarise the state-of-the-art and investigate a challenging problem domain, the analysis of minerals bearing multiple rare-earth elements.\n\nRelevant Snippet:\n\u2026 The latest revolution, the silicon drift detector (SDD), has brought \u2026 SEM stages often have rotate and tilt axis that hinder \u2026 with large error bars (\u201dstandardless analysis\u201d). Accurate electron \u2026\n\n\n---\n\n## 2. Chemical characterisation is rough: the impact of topography and measurement parameters on energy-dispersive X-ray spectroscopy in biominerals\nValid Text Names:\n'shirley2022chemicalcharacterisationis pages 1-2', 'shirley2022chemicalcharacterisationis pages 2-5', 'shirley2022chemicalcharacterisationis pages 5-7', 'shirley2022chemicalcharacterisationis pages 7-9', 'shirley2022chemicalcharacterisationis pages 9-12', 'shirley2022chemicalcharacterisationis pages 12-14', 'shirley2022chemicalcharacterisationis pages 14-15', 'shirley2022chemicalcharacterisationis pages 15-15'\n\nBibTex:\n@article{shirley2022chemicalcharacterisationis,\n    author = \"Shirley, Bryan and Jarochowska, Emilia\",\n    title = \"Chemical characterisation is rough: the impact of topography and measurement parameters on energy-dispersive X-ray spectroscopy in biominerals\",\n    year = \"2022\",\n    journal = \"Facies\",\n    volume = \"68\",\n    month = \"Mar\",\n    doi = \"10.1007/s10347-022-00645-4\",\n    url = \"https://doi.org/10.1007/s10347-022-00645-4\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"2\",\n    issn = \"0172-9179\"\n}\n\n\nAbstract:\nEnergy dispersive X-ray microscopy (EDX) is a widely available, inexpensive method of characterizing the in-situ elemental composition of samples in Earth and life sciences. Common protocols and textbooks focussing on material sciences address EDX analysis of metallic samples that can be polished perfectly, whereas geoscientists often investigate specimens with prominent topography and composed of light, difficult to resolve elements. This is further compounded by the scarcity of literature surrounding the methodology of SEM\u2013EDX in the field of palaeontology, leading to common misinterpretations and artefacts during data acquisition. Here, the common errors in elemental composition obtained with EDX arising from surface topography and from parameters subject to user decisions are quantified. As a model, fossil bioapatite (conodonts) and abiotic Durango apatite are used. It is shown that even microscale topography can distort measured composition by up to 34%, whereas topographic features such as tilt with respect to the electron beam lead to differences of up to 85%. Working distance was not the most important parameter affecting the results and led to differences in composition of up to 13%, whereas the choice of standard and its levelling with the sample surface led to inaccuracy reaching 33%. EDX results can be also affected by beam damage and the effects of acceleration voltage on sample acquisition and resolution are quantified. An estimate is provided of the severity of errors associated with samples which cannot satisfy preparation requirements for EDX fully, such as holotypes, and with user decisions. Using a palaeontological example, recommendations are offered for the best parameters and the relative importance of error sources are assessed.\n\nRelevant Snippet:\n\u2026 The first step in this analysis is to define the SEM parameters (detector type, \u2026 Ritchie NWM, Newbury DE, Davis JM (2012) EDS \u2026 accuracy using a silicon drift detector. In: Microscopy and \u2026\n\n\n---\n\n## 3. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (SEM/EDS) quantitative? Effect of specimen shape\nValid Text Names:\n'newbury2011isscanningelectron pages 1-2', 'newbury2011isscanningelectron pages 2-3', 'newbury2011isscanningelectron pages 3-7', 'newbury2011isscanningelectron pages 7-10', 'newbury2011isscanningelectron pages 10-13', 'newbury2011isscanningelectron pages 13-16', 'newbury2011isscanningelectron pages 16-16'\n\nBibTex:\n@article{newbury2011isscanningelectron,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Is scanning electron microscopy/energy dispersive x-ray spectroscopy (SEM/EDS) quantitative? Effect of specimen shape\",\n    year = \"2011\",\n    journal = \"SPIE Proceedings\",\n    volume = \"8036\",\n    pages = \"803602\",\n    month = \"May\",\n    doi = \"10.1117/12.881040\",\n    url = \"https://doi.org/10.1117/12.881040\",\n    publisher = \"SPIE\",\n    issn = \"0277-786X\"\n}\n\n\nRelevant Snippet:\n\u2026 The extraordinary throughput of the silicon drift detector energy dispersive x-ray \u2026 -standards standardless\u201d analysis procedure available in most commercial x-ray microanalysis software \u2026\n\n\n---\n\n## 4. Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\nValid Text Names:\n'newbury2019electronexcitedxraymicroanalysis pages 1-2', 'newbury2019electronexcitedxraymicroanalysis pages 2-3', 'newbury2019electronexcitedxraymicroanalysis pages 3-4', 'newbury2019electronexcitedxraymicroanalysis pages 4-5', 'newbury2019electronexcitedxraymicroanalysis pages 5-6', 'newbury2019electronexcitedxraymicroanalysis pages 6-8', 'newbury2019electronexcitedxraymicroanalysis pages 8-10', 'newbury2019electronexcitedxraymicroanalysis pages 10-13', 'newbury2019electronexcitedxraymicroanalysis pages 13-15', 'newbury2019electronexcitedxraymicroanalysis pages 15-16', 'newbury2019electronexcitedxraymicroanalysis pages 16-18', 'newbury2019electronexcitedxraymicroanalysis pages 18-20', 'newbury2019electronexcitedxraymicroanalysis pages 20-22', 'newbury2019electronexcitedxraymicroanalysis pages 22-26', 'newbury2019electronexcitedxraymicroanalysis pages 26-28', 'newbury2019electronexcitedxraymicroanalysis pages 28-29', 'newbury2019electronexcitedxraymicroanalysis pages 29-30', 'newbury2019electronexcitedxraymicroanalysis pages 29-29', 'newbury2019electronexcitedxraymicroanalysis pages 30-31'\n\nBibTex:\n@article{newbury2019electronexcitedxraymicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W.M.\",\n    title = \"Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"1075-1105\",\n    month = \"Oct\",\n    doi = \"10.1017/s143192761901482x\",\n    url = \"https://doi.org/10.1017/s143192761901482x\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"05\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nAbstract 2018 marked the 50th anniversary of the introduction of energy dispersive X-ray spectrometry (EDS) with semiconductor detectors to electron-excited X-ray microanalysis. Initially useful for qualitative analysis, EDS has developed into a fully quantitative analytical tool that can match wavelength dispersive spectrometry for accuracy in the determination of major (mass concentration C > 0.1) and minor (0.01 \u2264 C \u2264 0.1) constituents, and useful accuracy can extend well into the trace (0.001 < C < 0.01) constituent range even when severe peak interference occurs. Accurate analysis is possible for low atomic number elements (B, C, N, O, and F), and at low beam energy, which can optimize lateral and depth spatial resolution. By recording a full EDS spectrum at each picture element of a scan, comprehensive quantitative compositional mapping can also be performed.\n\nRelevant Snippet:\n\u2026 spectrometry (EDS) with semiconductor detectors to electron-excited X-ray microanalysis. Initially useful for qualitative analysis, EDS has developed into a fully quantitative analytical \u2026\n\n\n---\n\n## 5. Measurement uncertainties of energy dispersive X-ray spectroscopy in the scanning electron microscope (SEM-EDX/EDS)\nValid Text Names:\n'tong2026measurementuncertaintiesof pages 1-8', 'tong2026measurementuncertaintiesof pages 8-11', 'tong2026measurementuncertaintiesof pages 11-12', 'tong2026measurementuncertaintiesof pages 12-15', 'tong2026measurementuncertaintiesof pages 15-18', 'tong2026measurementuncertaintiesof pages 18-21', 'tong2026measurementuncertaintiesof pages 21-24', 'tong2026measurementuncertaintiesof pages 24-26'\n\nBibTex:\n@article{tong2026measurementuncertaintiesof,\n    author = \"Tong, V. and Mingard, K.\",\n    title = \"Measurement uncertainties of energy dispersive X-ray spectroscopy in the scanning electron microscope (SEM-EDX/EDS)\",\n    year = \"2026\",\n    journal = \"Unknown journal\",\n    month = \"Mar\",\n    doi = \"10.47120/npl.mat135\",\n    url = \"https://doi.org/10.47120/npl.mat135\",\n    publisher = \"National Physical Laboratory\"\n}\n\n\nRelevant Snippet:\n\u2026 using the un-normalised standardless quantification method. All spectra (\u2026 microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector \u2026\n\n\n---\n\n## 6. EDS with Low-Voltage SEM: Possibilities and limitations of lithium detection and quantification\nValid Text Names:\n'gollaschindler2026edswithlowvoltage pages 1-3', 'gollaschindler2026edswithlowvoltage pages 3-6', 'gollaschindler2026edswithlowvoltage pages 6-8', 'gollaschindler2026edswithlowvoltage pages 8-13', 'gollaschindler2026edswithlowvoltage pages 13-14', 'gollaschindler2026edswithlowvoltage pages 14-17', 'gollaschindler2026edswithlowvoltage pages 17-17'\n\nBibTex:\n@article{gollaschindler2026edswithlowvoltage,\n    author = \"Golla-Schindler, Ute and Schneider, Gerhard\",\n    title = \"EDS with Low-Voltage SEM: Possibilities and limitations of lithium detection and quantification\",\n    year = \"2026\",\n    journal = \"EPJ Web of Conferences\",\n    volume = \"349\",\n    pages = \"01004\",\n    month = \"Jan\",\n    doi = \"10.1051/epjconf/202634901004\",\n    url = \"https://doi.org/10.1051/epjconf/202634901004\",\n    publisher = \"EDP Sciences\",\n    issn = \"2100-014X\"\n}\n\n\nAbstract:\n<jats:p>Achieving reliable detection and quantification of lithium (Li) with high spatial resolution down to the nanometer (nm) range is a major challenge on the path to fully understanding lithium-ion batteries throughout their life span. This paper presents possible influencing factors, such as contamination, radiation damage and charging effects, on EDS analysis, as well as methods for detecting and avoiding these effects. A windowless EDS detector specialising in the detection of low-energy X-rays enables Li content analysis. Even in Li compounds with overlapping edges, the lithium content can be clarified. The systematic investigation of the detection of lithium in lithium metal and lithium compounds, lithium batteries, and the influence of sample preparation and storage is presented. The reliability and accuracy of EDS quantification on samples under non-ideal testing conditions is also investigated. A new method of quantifying lithium, 'Li by difference', is introduced, whereby the lithium content is calculated as the missing element fraction of a non-normalised EDS quantification.</jats:p>\n\nRelevant Snippet:\n\u2026 EDS analysis, as well as methods for detecting and avoiding these effects. A windowless EDS detector specialising in the detection of low\u2026 The next setting is standard-less and, therefore\u2026\n\n\nUnobtainable Papers:\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W.M. Ritchie, John Henry J. Scott, and David C. Joy. Scanning electron microscopy and x-ray microanalysis. Scanning Electron Microscopy and X-Ray Microanalysis, Jan 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9, doi:10.1007/978-1-4939-6676-9.\nDale E. Newbury and Nicholas W. M. Ritchie. Rigorous quantitative elemental microanalysis by scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds) with spectrum processing by nist dtsa-ii. SPIE Proceedings, 9236:92360H, Sep 2014. URL: https://doi.org/10.1117/12.2065842, doi:10.1117/12.2065842.\nDale E. Newbury. Developments in instrumentation for microanalysis in low-voltage scanning electron microscopy. ArXiv, pages 263-303, 2008. URL: https://doi.org/10.1007/978-0-387-72972-5\\_11, doi:10.1007/978-0-387-72972-5\\_11.\nDale E. Newbury* and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds) quantitative? Scanning, 35 3:141-68, May 2013. URL: https://doi.org/10.1002/sca.21041, doi:10.1002/sca.21041.\nDale E. Newbury and Nicholas W. M. Ritchie. Measurement of trace constituents by electron-excited x-ray microanalysis with energy-dispersive spectrometry. Microscopy and Microanalysis, 22:520-535, May 2016. URL: https://doi.org/10.1017/s1431927616000738, doi:10.1017/s1431927616000738.\nRobert A. Fletcher, Nicholas W. M. Ritchie, Ian M. Anderson, and John A. Small. Microscopy and microanalysis of individual collected particles. Aerosol Measurement, pages 179-232, Jun 2011. URL: https://doi.org/10.1002/9781118001684.ch10, doi:10.1002/9781118001684.ch10.\nDale E. Newbury and Nicholas W. M. Ritchie. Faults and foibles of quantitative scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds). SPIE Proceedings, 8378:837803, May 2012. URL: https://doi.org/10.1117/12.912770, doi:10.1117/12.912770.\nDale E. Newbury and Nicholas W. M. Ritchie. Elemental mapping of microstructures by scanning electron microscopy-energy dispersive x-ray spectrometry (sem-eds): extraordinary advances with the silicon drift detector (sdd). Journal of Analytical Atomic Spectrometry, 28:973-988, Jun 2013. URL: https://doi.org/10.1039/c3ja50026h, doi:10.1039/c3ja50026h.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=16 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)\nValid Text Names:\n'newbury2015performingelementalmicroanalysis pages 1-2', 'newbury2015performingelementalmicroanalysis pages 2-4', 'newbury2015performingelementalmicroanalysis pages 4-5', 'newbury2015performingelementalmicroanalysis pages 5-6', 'newbury2015performingelementalmicroanalysis pages 6-7', 'newbury2015performingelementalmicroanalysis pages 7-9', 'newbury2015performingelementalmicroanalysis pages 9-11', 'newbury2015performingelementalmicroanalysis pages 11-13', 'newbury2015performingelementalmicroanalysis pages 13-15', 'newbury2015performingelementalmicroanalysis pages 15-17', 'newbury2015performingelementalmicroanalysis pages 17-20', 'newbury2015performingelementalmicroanalysis pages 20-21', 'newbury2015performingelementalmicroanalysis pages 21-23', 'newbury2015performingelementalmicroanalysis pages 23-25', 'newbury2015performingelementalmicroanalysis pages 25-26', 'newbury2015performingelementalmicroanalysis pages 26-26'\n\nBibTex:\n@article{newbury2015performingelementalmicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)\",\n    year = \"2015\",\n    journal = \"Journal of Materials Science\",\n    volume = \"50\",\n    pages = \"493-518\",\n    month = \"Nov\",\n    doi = \"10.1007/s10853-014-8685-2\",\n    url = \"https://doi.org/10.1007/s10853-014-8685-2\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"2\",\n    issn = \"0022-2461\"\n}\n\n\nAbstract:\nElectron-excited X-ray microanalysis performed in the scanning electron microscope with energy-dispersive X-ray spectrometry (EDS) is a core technique for characterization of the microstructure of materials. The recent advances in EDS performance with the silicon drift detector (SDD) enable accuracy and precision equivalent to that of the high spectral resolution wavelength-dispersive spectrometer employed on the electron probe microanalyzer platform. SDD-EDS throughput, resolution, and stability provide practical operating conditions for measurement of high-count spectra that form the basis for peak fitting procedures that recover the characteristic peak intensities even for elemental combination where severe peak overlaps occur, such PbS, MoS2, BaTiO3, SrWO4, and WSi2. Accurate analyses are also demonstrated for interferences involving large concentration ratios: a major constituent on a minor constituent (Ba at 0.4299 mass fraction on Ti at 0.0180) and a major constituent on a trace constituent (Ba at 0.2194 on Ce at 0.00407; Si at 0.1145 on Ta at 0.0041). Accurate analyses of low atomic number elements, C, N, O, and F, are demonstrated. Measurement of trace constituents with limits of detection below 0.001 mass fraction (1000\u00a0ppm) is possible within a practical measurement time of 500\u00a0s.\n\nRelevant Snippet:\n\u2026 quantitative EDS microanalysis that employed the whole spectrum. The so-called \u2018\u2018standardless analysis\u2019\u2019 method requires only the EDS \u2026 \u2018\u2018Standardless analysis\u2019\u2019 seeks to provide the \u2026\n\n\n---\n\n## 2. Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\nValid Text Names:\n'goldstein2018energydispersivexray pages 1-2', 'goldstein2018energydispersivexray pages 2-4', 'goldstein2018energydispersivexray pages 4-6', 'goldstein2018energydispersivexray pages 6-7', 'goldstein2018energydispersivexray pages 7-9', 'goldstein2018energydispersivexray pages 9-10', 'goldstein2018energydispersivexray pages 10-11', 'goldstein2018energydispersivexray pages 11-14', 'goldstein2018energydispersivexray pages 14-15', 'goldstein2018energydispersivexray pages 15-16', 'goldstein2018energydispersivexray pages 16-18', 'goldstein2018energydispersivexray pages 18-20', 'goldstein2018energydispersivexray pages 20-22', 'goldstein2018energydispersivexray pages 22-25', 'goldstein2018energydispersivexray pages 25-26'\n\nBibTex:\n@article{goldstein2018energydispersivexray,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"209-234\",\n    doi = \"10.1007/978-1-4939-6676-9\\_16\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_16\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nAs illustrated in Fig. 16.1, the physical basis of energy dispersive X-ray spectrometry (EDS) with a semiconductor detector begins with photoelectric absorption of an X-ray photon in the active volume of the semiconductor (Si). The entire energy of the photon is transferred to a bound inner shell atomic electron, which is ejected with kinetic energy equal to the photon energy minus the shell ionization energy (binding energy), 1.838 keV for the Si K-shell and 0.098 keV for the Si L-shell. The ejected photoelectron undergoes inelastic scattering within the Si crystal. One of the consequences of the energy loss is the promotion of bound outer shell valence electrons to the conduction band of the semiconductor, leaving behind positively charged \u201choles\u201d in the valence band. In the conduction band, the free electrons can move in response to a potential applied between the entrance surface electrode and the back surface electrode across the thickness of the Si crystal, while the positive holes in the conduction band drift in the opposite direction, resulting in the collection of electrons at the anode on the back surface of the EDS detector. This charge generation process requires approximately 3.6 eV per electron hole pair, so that the number of charge carriers is proportional to the original photon energy, Ep: \n \n$$ n={E}_p/3.6\\ eV $$ \n \nFor a Mn K-L3 photon with an energy of 5.895 keV, approximately 1638 electron\u2013hole pairs are created, comprising a charge of 2.6 \u00d7 10\u221216 coulombs. Because the detector can respond to any photon energy from a threshold of approximately 50 eV to 30 keV or more, the process has been named \u201cenergy dispersive,\u201d although in the spectrometry sense there is no actual dispersion such as occurs in a diffraction element spectrometer.\n\nRelevant Snippet:\n\u2026 Over the last 10 years, the Si(Li)-EDS has been replaced by the silicon drift detector design (SDD-EDS), illustrated in . Fig. \u2026 performance of the detector is three-way trade-off between \u2026\n\n\n---\n\n## 3. Optimal Pulse Processing, Pile-Up Decomposition, and Applications of Silicon Drift Detectors at LCLS\nValid Text Names:\n'blaj2017optimalpulseprocessing pages 1-2', 'blaj2017optimalpulseprocessing pages 2-2', 'blaj2017optimalpulseprocessing pages 2-4', 'blaj2017optimalpulseprocessing pages 4-5', 'blaj2017optimalpulseprocessing pages 5-6', 'blaj2017optimalpulseprocessing pages 6-7', 'blaj2017optimalpulseprocessing pages 7-8', 'blaj2017optimalpulseprocessing pages 8-9', 'blaj2017optimalpulseprocessing pages 9-10', 'blaj2017optimalpulseprocessing pages 10-12', 'blaj2017optimalpulseprocessing pages 12-13', 'blaj2017optimalpulseprocessing pages 13-14', 'blaj2017optimalpulseprocessing pages 14-15', 'blaj2017optimalpulseprocessing pages 15-15'\n\nBibTex:\n@article{blaj2017optimalpulseprocessing,\n    author = \"Blaj, G. and Kenney, C. J. and Dragone, A. and Carini, G. and Herrmann, S. and Hart, P. and Tomada, A. and Koglin, J. and Haller, G. and Boutet, S. and Messerschmidt, M. and Williams, G. and Chollet, M. and Dakovski, G. and Nelson, S. and Pines, J. and Song, S. and Thayer, J.\",\n    title = \"Optimal Pulse Processing, Pile-Up Decomposition, and Applications of Silicon Drift Detectors at LCLS\",\n    year = \"2017\",\n    journal = \"IEEE Transactions on Nuclear Science\",\n    volume = \"64\",\n    pages = \"2854-2868\",\n    month = \"Jun\",\n    doi = \"10.48550/arxiv.1706.01211\",\n    url = \"https://doi.org/10.48550/arxiv.1706.01211\",\n    publisher = \"arXiv\"\n}\n\n\nAbstract:\nSilicon drift detectors (SDDs) revolutionized spectroscopy in fields as diverse as geology and dentistry. For a subset of experiments at ultrafast, X-ray free-electron lasers (FELs), SDDs can make substantial contributions. Often the unknown spectrum is interesting, carrying science data, or the background measurement is useful to identify unexpected signals. Many measurements involve only several discrete photon energies known a priori, allowing single-event decomposition of pile-up and spectroscopic photon counting. We designed a pulse function and demonstrated that the signal amplitude (i.e., proportional to the detected energy and obtained from fitting with the pulse function), rise time, and pulse height are interrelated, and at short peaking times, the pulse height and pulse area are not optimal estimators for detected energy; instead, the signal amplitude and rise time are obtained for each pulse by fitting, thus removing the need for pulse shaping. By avoiding pulse shaping, rise times of tens of nanoseconds resulted in reduced pulse pile-up and allowed decomposition of remaining pulse pile-up at photon separation times down to hundreds of nanoseconds while yielding time-of-arrival information with the precision of 10 ns. Waveform fitting yields simultaneously high energy resolution and high counting rates (two orders of magnitude higher than current digital pulse processors). At pulsed sources or high photon rates, photon pile-up still occurs. We showed that pile-up spectrum fitting is relatively simple and preferable to pile-up spectrum deconvolution. We developed a photon pile-up statistical model for constant intensity sources, extended it to variable intensity sources (typical for FELs), and used it to fit a complex pile-up spectrum. We subsequently developed a Bayesian pile-up decomposition method that allows decomposing pile-up of single events with up to six photons from six monochromatic lines with 99% accuracy. The usefulness of SDDs will continue into the X-ray FEL era of science. Their successors, the ePixS hybrid pixel detectors, already offer hundreds of pixels, each with a similar performance to an SDD, in a compact, robust and affordable package.\n\nRelevant Snippet:\n\u2026 We investigate the performance of SDDs at X-ray FELs. In particular, we study the ability to \u2026 fit for optimal energy resolution in the absence of pulse shaping. With this approach, \u2026\n\n\n---\n\n## 4. Optimized readout methods of silicon drift detectors for high-resolution X-ray spectroscopy\nValid Text Names:\n'niculae2006optimizedreadoutmethods pages 1-2', 'niculae2006optimizedreadoutmethods pages 2-3', 'niculae2006optimizedreadoutmethods pages 3-6', 'niculae2006optimizedreadoutmethods pages 6-7'\n\nBibTex:\n@article{niculae2006optimizedreadoutmethods,\n    author = \"Niculae, A. and Lechner, P. and Soltau, H. and Lutz, G. and Str\u00fcder, L. and Fiorini, C. and Longoni, A.\",\n    title = \"Optimized readout methods of silicon drift detectors for high-resolution X-ray spectroscopy\",\n    year = \"2006\",\n    journal = \"Nuclear Instruments \\& Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment\",\n    volume = \"568\",\n    pages = \"336-342\",\n    month = \"Nov\",\n    doi = \"10.1016/j.nima.2006.06.025\",\n    url = \"https://doi.org/10.1016/j.nima.2006.06.025\",\n    publisher = \"Elsevier BV\",\n    issue = \"1\",\n    issn = \"0168-9002\"\n}\n\n\nRelevant Snippet:\n\u2026 rates and constant energy resolution, pulsed-reset operation of the \u2026 reset pulses to a reset structure integrated on the detector \u2026 The performance of the 30 mm 2 SDD showing an energy \u2026\n\n\n---\n\n## 5. X-Ray Silicon Drift Detector\u2013CMOS Front-End System with High Energy Resolution at Room Temperature\nValid Text Names:\n'bertuccio2016xraysilicondrift pages 1-3', 'bertuccio2016xraysilicondrift pages 3-4', 'bertuccio2016xraysilicondrift pages 4-5', 'bertuccio2016xraysilicondrift pages 5-7', 'bertuccio2016xraysilicondrift pages 7-8', 'bertuccio2016xraysilicondrift pages 8-8'\n\nBibTex:\n@article{bertuccio2016xraysilicondrift,\n    author = \"Bertuccio, G. and Ahangarianabhari, M. and Graziani, C. and Macera, D. and Shi, Y. and Gandola, M. and Rachevski, A. and Rashevskaya, I. and Vacchi, A. and Zampa, G. and Zampa, N. and Bellutti, P. and Giacomini, G. and Picciotto, A. and Piemonte, C. and Zorzi, N.\",\n    title = \"X-Ray Silicon Drift Detector\u2013CMOS Front-End System with High Energy Resolution at Room Temperature\",\n    year = \"2016\",\n    journal = \"IEEE Transactions on Nuclear Science\",\n    volume = \"63\",\n    pages = \"400-406\",\n    month = \"Feb\",\n    doi = \"10.48550/arxiv.2201.01698\",\n    url = \"https://doi.org/10.48550/arxiv.2201.01698\",\n    publisher = \"Institute of Electrical and Electronics Engineers (IEEE)\",\n    issue = \"1\",\n    issn = \"0018-9499\"\n}\n\n\nAbstract:\nWe present a spectroscopic system constituted by a Silicon Drift Detector (SDD) coupled to a CMOS charge sensitive preamplifier, named SIRIO, specifically designed to reach ultimate low noise levels. The SDD, with an active area of 13 mm<sup>2</sup>, has been manufactured by optimizing the production processes in order to reduce the anode current, successfully reaching current densities between 17 pA/cm<sup>2</sup> and 25 pA/cm<sup>2</sup> at + 20 <sup>\u00b0</sup> C for drift fields ranging from 100 V/cm to 500 V/cm. The preamplifier shows minimum intrinsic noise levels of 1.27 and 1.0 electrons r.m.s. at +20 <sup>\u00b0</sup>C and -30 <sup>\u00b0</sup>C, respectively. At room temperature (+ 20<sup>\u00b0</sup> C) the <sup>55</sup>Fe 5.9 keV and the pulser lines have 136 eV and 64 eV FWHM, respectively, corresponding to an equivalent noise charge of 7.4 electrons r.m.s.; the noise threshold is at 165 eV. The energy resolution, as measured on the pulser line, ranges from 82 eV FWHM (9.4 electrons r.m.s.) at + 30 <sup>\u00b0</sup> C down to 29 eV FWHM (3.3 electrons r.m.s.) at - 30 <sup>\u00b0</sup> C.\n\nRelevant Snippet:\n\u2026 to traditional detectors for which a tradeoff between large \u2026 as function of the peaking time of a triangular pulse shaping. \u2026 spectroscopic performance of a matrix of silicon drift diodes,\u201d \u2026\n\n\nUnobtainable Papers:\nPeter D. Olcott and Craig S. Levin. Pulse width modulation: a novel readout scheme for high energy photon detection. 2008 IEEE Nuclear Science Symposium Conference Record, pages 4530-4535, Oct 2008. URL: https://doi.org/10.1109/nssmic.2008.4774297, doi:10.1109/nssmic.2008.4774297.\nFlorian Rettenmeier and Linus Maurer. Utilization of adaptive flattop time with large area silicon drift detectors. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 998:165192, May 2021. URL: https://doi.org/10.1016/j.nima.2021.165192, doi:10.1016/j.nima.2021.165192.\nW. Metzger, J. Engdahl, W. Rossner, O. Boslau, and J. Kemmer. Large-area silicon drift detectors for new applications in nuclear medicine imaging. IEEE Transactions on Nuclear Science, 51:1631-1635, Aug 2004. URL: https://doi.org/10.1109/nssmic.2003.1351952, doi:10.1109/nssmic.2003.1351952.\nR. B. Mott and J. J. Friel. Improving eds performance with digital pulse processing. ArXiv, pages 127-157, Jan 1995. URL: https://doi.org/10.1007/978-1-4615-1825-9\\_9, doi:10.1007/978-1-4615-1825-9\\_9.\nNicholas W.M. Ritchie, Dale E. Newbury, and Jeffrey M. Davis. Eds measurements of x-ray intensity at wds precision and accuracy using a silicon drift detector. Microscopy and Microanalysis, 18:892-904, Jul 2012. URL: https://doi.org/10.1017/s1431927612001109, doi:10.1017/s1431927612001109.\nGrazia Laricchiuta, Wilfried Vandervorst, Ivan Zyulkov, Silvia Armini, and Johan Meersschaut. High sensitivity rutherford backscattering spectrometry using multidetector digital pulse processing. Journal of Vacuum Science and Technology, Feb 2018. URL: https://doi.org/10.1116/1.5016033, doi:10.1116/1.5016033.\nJinghui Wang, Linchuan Chen, Mats Persson, Paurakh L. Rajbhandary, Praneeth Kandlakunta, Gabriella Carini, and Rebecca Fahrig. Pulse pileup analysis for a double-sided silicon strip detector using variable pulse shapes. Jun 2019. URL: https://doi.org/10.1109/tns.2019.2917144, doi:10.1109/tns.2019.2917144.\nFlorian Rettenmeier and Linus Maurer. Design of optimum filters for signal processing with silicon drift detectors. X-Ray Spectrometry, 50:501-513, Feb 2021. URL: https://doi.org/10.1002/xrs.3227, doi:10.1002/xrs.3227.\nG. Gramegna, P. O'Connor, P. Rehak, and S. Hart. Low-noise cmos preamplifier-shaper for silicon drift detectors. Jun 1997. URL: https://doi.org/10.1109/23.603676, doi:10.1109/23.603676.\nL. Bombelli, R. Quaglia, C. Fiorini, A. Tocchio, R. Alberti, and T. Frizzi. A multichannel integrated readout circuit for high throughput x-ray spectroscopy with silicon drift detectors. IEEE Transactions on Nuclear Science, 60:430-436, Oct 2013. URL: https://doi.org/10.1109/nssmic.2011.6154300, doi:10.1109/nssmic.2011.6154300.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=16 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Low voltage imaging and X-ray microanalysis in the SEM: challenges and opportunities\nValid Text Names:\n'wuhrer2016lowvoltageimaging pages 1-4', 'wuhrer2016lowvoltageimaging pages 4-7', 'wuhrer2016lowvoltageimaging pages 7-10', 'wuhrer2016lowvoltageimaging pages 10-12', 'wuhrer2016lowvoltageimaging pages 12-14', 'wuhrer2016lowvoltageimaging pages 14-15'\n\nBibTex:\n@article{wuhrer2016lowvoltageimaging,\n    author = \"Wuhrer, Richard and Moran, K.\",\n    title = \"Low voltage imaging and X-ray microanalysis in the SEM: challenges and opportunities\",\n    year = \"2016\",\n    journal = \"IOP Conference Series: Materials Science and Engineering\",\n    volume = \"109\",\n    pages = \"012019\",\n    month = \"Feb\",\n    doi = \"10.1088/1757-899x/109/1/012019\",\n    url = \"https://doi.org/10.1088/1757-899x/109/1/012019\",\n    publisher = \"IOP Publishing\",\n    issn = \"1757-8981\"\n}\n\n\nRelevant Snippet:\n\u2026 Operating the SEM at lower accelerating voltage allows for \u2026 scale lateral X-ray spatial resolution and nanoscale X-ray depth \u2026 of scanning electron microscope (SEM), X-ray microanalysis, \u2026\n\n\nUnobtainable Papers:\nM. David Frey. Low kv scanning electron microscopy. ArXiv, pages 101-119, Jan 2007. URL: https://doi.org/10.1007/978-0-387-39620-0\\_4, doi:10.1007/978-0-387-39620-0\\_4.\nDale E Newbury. Diagnostics for assessing spectral quality for x-ray microanalysis in low voltage and variable pressure scanning electron microscopy. Microscopy and Microanalysis, 7:702-703, Aug 2001. URL: https://doi.org/10.1017/s1431927600029585, doi:10.1017/s1431927600029585.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, Charles E. Lyman, Eric Lifshin, Linda Sawyer, and Joseph R. Michael. Special topics in scanning electron microscopy. ArXiv, pages 195-270, Jan 2003. URL: https://doi.org/10.1007/978-1-4615-0215-9\\_5, doi:10.1007/978-1-4615-0215-9\\_5.\nDale E. Newbury, David C. Joy, Patrick Echlin, Charles E. Fiori, and Joseph I. Goldstein. Advanced scanning electron microscopy and x-ray microanalysis. In Springer US. Mar 2013. URL: https://doi.org/10.1007/978-1-4757-9027-6, doi:10.1007/978-1-4757-9027-6.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, A. D. Romig, Charles E. Lyman, Charles Fiori, and Eric Lifshin. Coating and conductivity techniques for sem and microanalysis. ArXiv, pages 671-740, Jan 1992. URL: https://doi.org/10.1007/978-1-4613-0491-3\\_13, doi:10.1007/978-1-4613-0491-3\\_13.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, Charles Fiori, and Eric Lifshin. Coating techniques for sem and microanalysis. ArXiv, pages 461-494, Jan 1981. URL: https://doi.org/10.1007/978-1-4613-3273-2\\_10, doi:10.1007/978-1-4613-3273-2\\_10.\nEdward D. Boyes. Analytical potential of eds at low voltages. Microchimica Acta, 138:225-234, May 2002. URL: https://doi.org/10.1007/s006040200026, doi:10.1007/s006040200026.\nE.D. Boyes. On low voltage scanning electron microscopy and chemical microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 6 4:307-316, Jul 2000. URL: https://doi.org/10.1017/s1431927602000545, doi:10.1017/s1431927602000545.\nD. B. Williams and J. I. Goldstein. Quantitative x-ray microanalysis in the analytical electron microscope. ArXiv, pages 371-398, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_18, doi:10.1007/978-1-4899-2617-3\\_18.\nR.F. Egerton. Choice of operating voltage for a transmission electron microscope. Ultramicroscopy, 145:85-93, Oct 2014. URL: https://doi.org/10.1016/j.ultramic.2013.10.019, doi:10.1016/j.ultramic.2013.10.019.\nJ. I. Goldstein. Principles of thin film x-ray microanalysis. ArXiv, pages 83-120, Jan 1979. URL: https://doi.org/10.1007/978-1-4757-5581-7\\_3, doi:10.1007/978-1-4757-5581-7\\_3.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=20 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0408 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_012wLpkY7s5q8ZTdPqRt9A1b",
+                "info": {
+                  "start_ts": 2649.093164063,
+                  "end_ts": 2679.977535593
+                }
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+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\nValid Text Names:\n'goldstein2018quantitativeanalysisthe pages 1-4', 'goldstein2018quantitativeanalysisthe pages 4-6', 'goldstein2018quantitativeanalysisthe pages 6-8', 'goldstein2018quantitativeanalysisthe pages 8-9', 'goldstein2018quantitativeanalysisthe pages 9-11', 'goldstein2018quantitativeanalysisthe pages 11-12', 'goldstein2018quantitativeanalysisthe pages 12-14', 'goldstein2018quantitativeanalysisthe pages 14-16', 'goldstein2018quantitativeanalysisthe pages 16-18', 'goldstein2018quantitativeanalysisthe pages 18-18', 'goldstein2018quantitativeanalysisthe pages 18-22', 'goldstein2018quantitativeanalysisthe pages 22-23', 'goldstein2018quantitativeanalysisthe pages 23-24', 'goldstein2018quantitativeanalysisthe pages 24-26', 'goldstein2018quantitativeanalysisthe pages 26-28', 'goldstein2018quantitativeanalysisthe pages 28-29', 'goldstein2018quantitativeanalysisthe pages 29-30', 'goldstein2018quantitativeanalysisthe pages 30-31', 'goldstein2018quantitativeanalysisthe pages 31-31'\n\nBibTex:\n@article{goldstein2018quantitativeanalysisthe,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"309-339\",\n    doi = \"10.1007/978-1-4939-6676-9\\_20\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_20\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nThis module discusses the procedure used to perform a rigorous quantitative elemental microanalysis by SEM/EDS following the k-ratio/matrix correction protocol using the NIST DTSA-II software engine for bulk specimens. Bulk specimens have dimensions that are sufficiently large to contain the full range of the direct electron-excited X-ray production (typically 0.5\u201310 \u03bcm) as well as the range of secondary X-ray fluorescence induced by the propagation of the characteristic and continuum X-rays (typically 10\u2013100 \u03bcm).\n\nRelevant Snippet:\n\u2026 following the k-ratio/matrix correction protocol using the NIST \u2026 , eventually falling to zero (\u201cparalyzable dead-time\u201d). A useful \u2026 of coincidence peaks above a deadtime of 10 % from highly \u2026\n\n\n---\n\n## 2. A New Method for Dead Time Calibration and a New Expression for Correction of WDS Intensities for Microanalysis.\nValid Text Names:\n'donovan2023anewmethod pages 1-2', 'donovan2023anewmethod pages 1-1', 'donovan2023anewmethod pages 2-3', 'donovan2023anewmethod pages 3-3', 'donovan2023anewmethod pages 3-4', 'donovan2023anewmethod pages 4-5', 'donovan2023anewmethod pages 5-6', 'donovan2023anewmethod pages 6-7', 'donovan2023anewmethod pages 7-8', 'donovan2023anewmethod pages 8-8', 'donovan2023anewmethod pages 8-9', 'donovan2023anewmethod pages 9-10', 'donovan2023anewmethod pages 10-11', 'donovan2023anewmethod pages 11-12', 'donovan2023anewmethod pages 11-11', 'donovan2023anewmethod pages 12-13', 'donovan2023anewmethod pages 13-14', 'donovan2023anewmethod pages 14-14', 'donovan2023anewmethod pages 14-15', 'donovan2023anewmethod pages 15-15'\n\nBibTex:\n@article{donovan2023anewmethod,\n    author = \"Donovan, John J and Moy, Aur\u00e9lien and von der Handt, Anette and Gainsforth, Zack and Maner, James L and Nachlas, William and Fournelle, John\",\n    title = \"A New Method for Dead Time Calibration and a New Expression for Correction of WDS Intensities for Microanalysis.\",\n    year = \"2023\",\n    journal = \"Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada\",\n    volume = \"29 3\",\n    pages = \"1096-1110\",\n    month = \"May\",\n    doi = \"10.1093/micmic/ozad050\",\n    url = \"https://doi.org/10.1093/micmic/ozad050\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"3\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nObserved photon count rates must be corrected for detector dead time effects for accurate quantification, especially at high count rates. We present the \"constant k-ratio\" method, a new approach for calibrating dead time for wavelength dispersive spectrometers by measuring k-ratios as a function of beam current. The method is based on the observation that for a given emission line at a specific take-off angle and electron beam energy, the intensity ratio from two materials containing the element should remain constant as a function of beam current, if the dead time calibration is accurate. The method has the advantage that it does not rely on the linearity of the beam current picoammeter, yet also allows the analyst to evaluate the picoammeter linearity, another critical parameter in EPMA calibration. By simultaneously comparing k-ratios for all spectrometers, one can also ascertain k-ratio consensus, essential for inter-laboratory comparisons. We also introduce improved dead time expressions and provide best practices on how to perform these instrument calibrations using this new \"constant k-ratio\" method. These improvements enable quantitative analysis of major and minor elements with high accuracy at high beam currents, simultaneously with trace elements with high sensitivity, for point analyses and X-ray mapping.\n\nRelevant Snippet:\n\u2026 for energy dispersive spectrometry (EDS) systems, which \u2026 sub-optimal for determining the exact dead time constants with \u2026 the detector and electronics, which as we will see breaks down \u2026\n\n\n---\n\n## 3. Optimizing SEM-EDX for Fast, High-Quality and Non-Destructive Elemental Analysis of Glass\nValid Text Names:\n'guyett2024optimizingsemedxfor pages 1-2', 'guyett2024optimizingsemedxfor pages 2-3', 'guyett2024optimizingsemedxfor pages 3-4', 'guyett2024optimizingsemedxfor pages 4-6', 'guyett2024optimizingsemedxfor pages 4-4', 'guyett2024optimizingsemedxfor pages 6-7', 'guyett2024optimizingsemedxfor pages 6-6', 'guyett2024optimizingsemedxfor pages 7-8', 'guyett2024optimizingsemedxfor pages 8-9', 'guyett2024optimizingsemedxfor pages 9-10', 'guyett2024optimizingsemedxfor pages 10-12', 'guyett2024optimizingsemedxfor pages 12-13', 'guyett2024optimizingsemedxfor pages 13-14', 'guyett2024optimizingsemedxfor pages 14-15', 'guyett2024optimizingsemedxfor pages 15-15'\n\nBibTex:\n@article{guyett2024optimizingsemedxfor,\n    author = \"Guyett, Paul C. and Chew, David and Azevedo, Vitor and Blennerhassett, Lucy C. and Rosca, Carolina and Tomlinson, Emma\",\n    title = \"Optimizing SEM-EDX for Fast, High-Quality and Non-Destructive Elemental Analysis of Glass\",\n    year = \"2024\",\n    journal = \"Journal of Analytical Atomic Spectrometry\",\n    volume = \"39\",\n    pages = \"2565-2579\",\n    month = \"Jan\",\n    doi = \"10.1039/d4ja00212a\",\n    url = \"https://doi.org/10.1039/d4ja00212a\",\n    publisher = \"Royal Society of Chemistry (RSC)\",\n    issue = \"10\",\n    issn = \"0267-9477\"\n}\n\n\nAbstract:\nAdvancements in scanning electron microscopy and energy dispersive x-ray analysis (SEM-EDX) technologies have reached the point where rapid, fully quantitative, non-destructive and high-resolution acquisition of effectively all major element chemical...\n\nRelevant Snippet:\n\u2026 investigated with electron probe micro-analysis (EPMA). \u2026 resolution and detection limit between SEM-EDX and EPMA. \u2026 per second, and has a dead time of c. 15%, each analysis took \u2026\n\n\nUnobtainable Papers:\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, A. D. Romig, Charles E. Lyman, Charles Fiori, and Eric Lifshin. Compositional Imaging, pages 525-545. Springer US, Jan 1992. URL: https://doi.org/10.1007/978-1-4613-0491-3\\_10, doi:10.1007/978-1-4613-0491-3\\_10.\nCharles Lyman. 2023 microscopy today innovation awards. Microscopy Today, 31:12-16, Sep 2023. URL: https://doi.org/10.1093/mictod/qaad069, doi:10.1093/mictod/qaad069.\nDivyadeep Harbola and George Mathew. Mapex: a tool for x-ray map analysis. Applied Computing and Geosciences, 28:100300, Dec 2025. URL: https://doi.org/10.1016/j.acags.2025.100300, doi:10.1016/j.acags.2025.100300.\nYueyun Chen and Matthew Mecklenburg. Corrected paralyzable detector model for post-acquisition pile-up correction in energy dispersive x-ray spectroscopy. Jul 2026. URL: https://doi.org/10.1093/mam/ozag053.176, doi:10.1093/mam/ozag053.176.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, Charles E. Lyman, Eric Lifshin, Linda Sawyer, and Joseph R. Michael. Special topics in electron beam x-ray microanalysis. ArXiv, pages 453-536, Jan 2003. URL: https://doi.org/10.1007/978-1-4615-0215-9\\_10, doi:10.1007/978-1-4615-0215-9\\_10.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=20 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0408 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_01HJKVHJA7DE6q3m7Yy2WBFB",
+                "info": {
+                  "start_ts": 2649.093340995,
+                  "end_ts": 2679.209444739
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Good, I have many relevant papers now. Let me gather evidence from these papers and continue searching for remaining topics:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01N5Kh9Z7F25JaJsXarBfAD4",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"question\": \"What is the physics behind overvoltage ratio U0=2-3 recommendation? How does Bethe ionization cross-section formula relate to optimal accelerating voltage? How does the Kanaya-Okayama electron range and phi(rho-z) depth distribution compete with ionization efficiency?\"}",
+                      "name": "gather_evidence"
+                    }
+                  },
+                  {
+                    "id": "toolu_018zPp22Aox3aKeNQkUGzTLj",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Poisson statistics counting precision relative standard deviation X-ray microanalysis 10000 counts\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_01JFSkowyEXcmvsUK26aPtGC",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"ISO 22309 ASTM E1508 SEM EDS microanalysis standard parameters round-robin interlaboratory\"}",
+                      "name": "paper_search"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "No relevant evidence found for your question.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=20 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0763 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
+                "tool_call_id": "toolu_01N5Kh9Z7F25JaJsXarBfAD4",
+                "info": {
+                  "start_ts": 2695.535909684,
+                  "end_ts": 2700.316676899
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Saving the photons: mapping X\u2010rays by position\u2010tagged spectrometry\nValid Text Names:\n'mott1999savingthephotons pages 1-2', 'mott1999savingthephotons pages 2-4', 'mott1999savingthephotons pages 4-5', 'mott1999savingthephotons pages 5-6', 'mott1999savingthephotons pages 6-10', 'mott1999savingthephotons pages 10-12', 'mott1999savingthephotons pages 12-13'\n\nBibTex:\n@article{mott1999savingthephotons,\n    author = \"MOTT, R. B. and FRIEL, J. J.\",\n    title = \"Saving the photons: mapping X\u2010rays by position\u2010tagged spectrometry\",\n    year = \"1999\",\n    journal = \"Journal of Microscopy\",\n    volume = \"193\",\n    month = \"Jan\",\n    doi = \"10.1046/j.1365-2818.1999.00437.x\",\n    url = \"https://doi.org/10.1046/j.1365-2818.1999.00437.x\",\n    pages = \"2-14\",\n    publisher = \"Wiley\",\n    issue = \"1\",\n    issn = \"0022-2720\"\n}\n\n\nRelevant Snippet:\n\u2026 relative to traditional X-ray mapping, photons are counted in a \u2026 3% relative standard deviation for only those elements of at \u2026 with the average count rate according to Poisson statistics. \u2026\n\n\nUnobtainable Papers:\nEric Lifshin and Raynald Gauvin. Minimizing errors in electron microprobe analysis. Mar 2001. URL: https://doi.org/10.1007/s100050010084, doi:10.1007/s100050010084.\nShinya Yamada, Magnus Axelsson, Yoshitaka Ishisaki, Saori Konami, Nozomi Takemura, Richard L Kelley, Caroline A Kilbourne, Maurice A Leutenegger, F Scott Porter, Megan E Eckart, and Andrew Szymkowiak. Poisson vs. gaussian statistics for sparse x-ray data: application to the soft x-ray spectrometer. Publications of the Astronomical Society of Japan, Aug 2019. URL: https://doi.org/10.1093/pasj/psz053, doi:10.1093/pasj/psz053.\nHenry Shuman, Avril V. Somlyo, and Andrew P. Somlyo. Quantitative electron probe microanalysis of biological thin sections: methods and validity. Ultramicroscopy, 1 4:317-39, Jan 1976. URL: https://doi.org/10.1016/0304-3991(76)90049-8, doi:10.1016/0304-3991(76)90049-8.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, Charles E. Lyman, Eric Lifshin, Linda Sawyer, and Joseph R. Michael. Quantitative X-Ray Analysis: The Basics, pages 391-451. Springer US, Jan 2003. URL: https://doi.org/10.1007/978-1-4615-0215-9\\_9, doi:10.1007/978-1-4615-0215-9\\_9.\nThomas O. Ziebold. Precision and sensitivity in electron microprobe analysis. Analytical Chemistry, 39:858-861, Jul 1967. URL: https://doi.org/10.1021/ac60252a028, doi:10.1021/ac60252a028.\nJ. Pyle, F. Spear, D. Wark, C. Daniel, and L. Storm. Contributions to precision and accuracy of monazite microprobe ages. American Mineralogist, 90:547-577, Apr 2005. URL: https://doi.org/10.2138/am.2005.1340, doi:10.2138/am.2005.1340.\nR. C. Stanley. Counting statistics in x-ray spectroscopy. British Journal of Applied Physics, 12:503-506, Sep 1961. URL: https://doi.org/10.1088/0508-3443/12/9/314, doi:10.1088/0508-3443/12/9/314.\nJ. M. Pyle, F. S. Spear, and D. A. Wark. Electron microprobe analysis of ree in apatite, monazite and xenotime: protocols and pitfalls. Reviews in Mineralogy & Geochemistry, 48:337-362, Jan 2002. URL: https://doi.org/10.2138/rmg.2002.48.8, doi:10.2138/rmg.2002.48.8.\nP. J. Statham. Quantifying benefits of resolution and count rate in edx microanalysis. ArXiv, pages 101-126, Jan 1995. URL: https://doi.org/10.1007/978-1-4615-1825-9\\_8, doi:10.1007/978-1-4615-1825-9\\_8.\nMark A. Rodriguez, Paul G. Kotula, James J. M. Griego, Jason E. Heath, Stephen J. Bauer, and Daniel E. Wesolowski. Multivariate statistical analysis of micro-x-ray fluorescence spectral images. Powder Diffraction, 27:108-113, Jun 2012. URL: https://doi.org/10.1017/s0885715612000243, doi:10.1017/s0885715612000243.\nA.V. Somlyo, H. Shuman, and A.P. Somlyo. Electron probe x-ray microanalysis of ca2+, mg2+, and other ions in rapidly frozen cells. Methods in enzymology, 172:203-29, Jan 1989. URL: https://doi.org/10.1016/s0076-6879(89)72016-4, doi:10.1016/s0076-6879(89)72016-4.\nDC Bell and AJ Garratt-Reed. Energy dispersive x-ray analysis in the electron microscope. ArXiv, Jul 2003. URL: https://doi.org/10.4324/9780203483428, doi:10.4324/9780203483428.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=21 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0763 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_018zPp22Aox3aKeNQkUGzTLj",
+                "info": {
+                  "start_ts": 2695.580510598,
+                  "end_ts": 2725.784912099
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nS\u00e9bastien Charles, Thierry Dodier, Monika Kaindl, Alain Kast\u00e9ropoulos, Alwin Knijnenberg, Marcus Larsson, Sandrine Lauper, Nadine Merat, Ludwig Niewoehner, Thomas Scholz, and Laurence Simon. Conduction of a round-robin test on a real sample for the identification of gunshot residues by sem/edx. Apr 2020. URL: https://doi.org/10.1016/j.forsciint.2020.110183, doi:10.1016/j.forsciint.2020.110183.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=20 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0763 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_01JFSkowyEXcmvsUK26aPtGC",
+                "info": {
+                  "start_ts": 2695.58127313,
+                  "end_ts": 2714.911551988
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Let me try to read the key texts directly since evidence gathering isn't matching. The Goldstein textbook chapters should have the core information:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01Ux3jYFNfYmU8LNiYAmAgM9",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"text_name_list\": [\"goldstein2018energydispersivexray pages 11-14\", \"goldstein2018energydispersivexray pages 14-15\", \"goldstein2018energydispersivexray pages 15-16\", \"goldstein2018energydispersivexray pages 16-18\", \"goldstein2018energydispersivexray pages 18-20\", \"goldstein2018energydispersivexray pages 20-22\"]}",
+                      "name": "read_text"
+                    }
+                  },
+                  {
+                    "id": "toolu_015vVm7ny2Vv7Hq6JqXFegiY",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"text_name_list\": [\"goldstein2018quantitativeanalysisthe pages 1-4\", \"goldstein2018quantitativeanalysisthe pages 4-6\", \"goldstein2018quantitativeanalysisthe pages 6-8\", \"goldstein2018quantitativeanalysisthe pages 8-9\", \"goldstein2018quantitativeanalysisthe pages 9-11\"]}",
+                      "name": "read_text"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "## 1. goldstein2018energydispersivexray pages 18-20 (Context ID: pqac-00000000)\n\n   current. Measure and record the probe current using the\n                                                                    Faraday cup and the picoammeter.\n                                                                                    4. Collect a 60 live-time second spectrum from the copper\n                                                                        sample.\n                                                                                    5. Increase the probe current through a sequence of\n      . .\u200a\u200a\u200aFig. 16.21\u2003 The spectrum image was collected on a 128 by 128          approximately 10\u201320 steps from the initial probe current\n             pixel grid representing 4\u2009\u00d7 4 mm. After data rotation to view the x-y         to approximately 2 times the optimal probe current.\n             plane, the first energy slice, 1 out of 1024, is shown. It appears black         Collect a 60 live-time second spectrum at each probe\n           because it contains no counts                                       current and measure and record the probe current using\n                                                                         the Faraday cup. A plot of such a measurement sequence\n                                                                                                  is shown in .\u2003 Fig. 16.23 (upper).\n                                                                                    6. Integrate the total number of counts in the range of\n                                                                      channels representing the Cu K-L2,3 characteristic peak.\n16                                                              (You don\u2019t need to background correct the integral.) Plot\n                                                                         the measured intensity divided by the probe current\n                                                                            against the measured probe current. The result should\n                                                                 be a horizontal line, as shown in .\u2003 Fig. 16.23 (lower).\n                                                                                       1.  If the line is not horizontal, the problem may be in the\n                                                                              detector or in the probe current measurement.\n                                                                                       2. The probe current measurement could be non-linear\n                                                                meaning the plot of the measured probe current to\n                                                                              true probe current is not a straight line.\n                                                                                       3.  Alternatively, the probe current may have a zero\n                                                                                              offset. The zero offset can be measured by blanking\n                                                                            the beam and recording the measured current at zero\n      . .\u200a\u200a\u200aFig. 16.22\u2003  Extracting the Cu L-family lines from the spectrum              true current. Subsequent probe current measurement\n            planes 89 to 97                                                can be offset by this value.\n\n         probe current, due to the loss of useful electrons during the\n          dead-time.                                                   16.3.6\u2002 Energy Calibration Linearity\n                   It is very important for accurate quantitative analysis that\n          the measured X-ray intensity is linear with respect to the   Consistent energy  calibration  is  critically important  for\n            effective probe dose. Twice the effective probe dose should   reproducible quantitative analysis. Pick a nominal channel\n         produce twice the measured  intensity. Not only  is  this  width (5-eV/channel will work fine in almost all cases) and                                                                                                        227                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n. .\u200a\u200a\u200aFig. 16.23\u2003 The number of\nX-rays recorded in the spectrum             3,000,000\nshould scale linearly with the                                      f(x) = 35876.1202787172x\ndose (the product of live-time                          R2 = 0.9999923818\nand probe current)                         2,500,000\n\n                                         2,000,000\n\n\n                                         1,500,000                                                                                        Counts                                                                   Det 2\n                                         1,000,000                                                                   Linear (Det 2)\n\n\n                                         500,000\n\n\n                                           0\n                                            0    10   20   30   40   50   60   70   80   90\n                                                              Probe dose (nA.s)\n\n\n                                      36,050\n\n                                      36,000\n                                      35,950\n\n                                      35,900\n\n                                      35,850                                                                                      (nA.s)\n              / 35,800\n                                      35,750                                                                Det 2                                                                                      Counts\n                                      35,700\n\n                                      35,650\n                                      35,600\n\n                                      35,550\n                                         0        0.2       0.4        0.6       0.8       1        1.2       1.4\n                                                                 Probe current (nA)\n\n\n\nuse this value for all your data acquisition. Before each day\u2019s   energy. Two points are sufficient to unambiguously calibrate\nmeasurements ensure that the detector is calibrated consis-   a linear function. The calibration (peak position) and resolu-\ntently by following the same protocol to check and, if neces-   tion (peak shape) should be constant with input count rate\nsary, recalibrate your detector.                                 (or dead-time), as shown in .\u2003 Fig. 16.24.\n  On a modern pulse processor, calibration is usually per-     To a very high degree, modern EDS detectors are linear.\nformed using the EDS vendor\u2019s software. The software will  However if you look carefully in the mid-range of energies,\nprompt you to collect a spectrum from an established mate-  you many notice the KLM markers may be misaligned by a\nrial. The software will examine the spectrum and extract the   channel or two. This is evidence that your detector is not per-\npositions of various characteristic X-ray features. The soft-   fectly linear but this need not represent a true performance\nware will then perform an internal adjustment to center these   problem.\nfeatures in the correct channels. Most modern pulse proces-      Since energy calibration is so critical but is also one of\nsors perform a continuous zero offset calibration using a  many parameters that should be measured as part of a com-\n\u201czero strobe pulse\u201d the pulse processor adds to the signal   plete EDS Quality Control (QC) program, the validation will\nstream for diagnostic purposes. Thus the only parameter  be discussed in a later section.\nthey usually adjust when performing a calibration is an elec-\ntronic gain. Usually, this involves identifying a single high\nenergy characteristic line (like the Mn K-L2,3 or the Cu K-L2,3)   16.3.7  Other Items\nand adjusting the gain until this feature is centered on the\nappropriate channel. The calibration is thus a two-point cali-   zz  Light Transparency and IR Cameras\nbration\u2014either a low energy characteristic line or the zero  Most (but not all) modern EDS detectors have a vacuum\nstrobe at low energy and a second characteristic line at high   tight window that is opaque to infrared and visible light.          228    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.24\u2003 The position and\n           widths of the characteristic peaks\n           should not vary with probe cur-\n             rent                               15 000\n\n                                                                                                                 Counts 10 000\n\n                                             5 000\n\n\n\n                                                0\n                  \n\n## 2. goldstein2018energydispersivexray pages 16-18 (Context ID: pqac-00000001)\n\n                                                                   \u201cImport \u2192 Raw\u201d tools to create a \u201cstack\u201d as shown in                   Detector                                                       .\u2003 Fig. 16.18.\n                                                                                        3. As imported, the orientation of the stack will depend\n                                                               upon how the data in the RAW file is organized.\n                                                                              Regardless of the original orientation, you will need to\n                                                                                 pivot the data a couple times using the \u201cImage \u2192\n                                        0.0                                                    Stack \u2192 Reslice\u201d tool. First, to identify the range of\n                                                                           channels that represent the Cu L-family and Cu K-L2,3\n                                                                                             intensities. Second, to align the spectrum data with           4\n               mm                                              the Z dimension so that the \u201cImage \u2192 Stack \u2192\n                                                                                Z-project\u201d tool can be used to create plots representing\n                                                                              the intensities in the Cu L-family and Cu K-L2,3\n                             4mm                       channels.\n                                                                                        4. The initial view of the imported spectrum will\n      . .\u200a\u200a\u200aFig. 16.16\u2003 A 3D rendering of the intensity in the Cu K line over a            usually show the data as shown in .\u2003 Fig. 16.19. In16\n           4 mm by 4 mm mapped area. Created using ImageJ-Fiji                          this view it is possible to identify the range of\n\n      . .\u200a\u200a\u200aFig. 16.17\u2003 A plot of two diag\u00ad\n            onal traverses extracted from the          300\n         3D rendering. The blue dots are                                                                                    Perp\n            perpendicular to the detector axis                                                                                                        Parallel\n                                             250          and red are parallel. Created using\n             ImageJ-Fiji\n                                             200\n\n\n                                             150                                                                                                                                                                        Intensity\n                                             100\n\n\n                                              50\n\n\n                                               0\n                                                 0           1           2           3           4           5           6\n\n                                                  mm                                                                                                       225                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n      channels to sum together for the Cu L-family and Cu   16.3.5  Count Rate Linearity\n       K-L2,3 lines. The Cu K-L2,3 lines are often quite dim.\n    5.  Using the \u201cImage \u2192 Stack \u2192 Reslice\u201d tool (see       One of the most important circuits in an X-ray pulse proces-\n       .\u2003 Fig. 16.20) rotate the stack until it looks like          sor accounts for the time during which the pulse processor is\n       .\u2003 Fig. 16.21                                       busy processing X-ray events. When the pulse processor is\n    6. Use the \u201cImage \u2192 Stack \u2192 Z-project\u201d twice            processing an X-ray, it is unavailable to process new incoming\n       (.\u2003 Fig. 16.22) to extract the range of channels           X-rays. This time is called \u201cdead-time.\u201d In contrast, the time\n       identified in .\u2003 Fig. 16.19 as associated with the Cu     during which the processor is not busy and is available is called\n       L-family and Cu K-L2,3 lines.                              \u201clive-time.\u201d The sum of \u201clive-time\u201d and \u201cdead-time\u201d is called\n    7. Convert the gray-scale image to a thermal scale using   \u201creal-time\u201d \u2013 the time you would measure using a wall clock.\n      \u201cImage \u2192 Lookup Tables \u2192 Thermal.\u201d                   For calculating the effective probe dose, live-time is the\n    8. Convert the image to a plot using \u201cAnalyze \u2192            critical parameter. The effective probe dose consists of those\n       Surface Plot\u201d                                           electrons which could produce measurable X-rays. So the\n    9.  Extract traverses from the image using the straight      effective probe dose equals the live-time times the probe cur-\n        line tool to define the traverse and then the \u201cAnalyze    rent. The effective probe dose is always less than the real\n   \u2192 Plot Profile\u201d tool to extract and plot the data.       probe dose, which is the product of the real time and the\n\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.18\u2003  Importing a RAW formatted spectrum image into\nImageJ-Fiji                                . .\u200a\u200aFig. 16.20\u2003  \u201cReslice\u201d tool used to rotate the stack\n\n\n\n\n       Cu L-family                                                               Cu K-L2,3\n\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.19\u2003 The spectrum image perspective as imported into ImageJ-Fiji. The bright strip is the Cu L-family while the much fainter band is\nCu K-L2,3           226    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                                                                  important because it is often hard to replicate the identical\n                                                                probe current but it is also important because different mate-\n                                                                                       rials measured with the same probe current will produce dif-\n                                                                            ferent dead times.\n                                                                    There really is no excuse for a modern X-ray detector not\n                                                                         to be linear. However, it is worth checking because the test\n                                                               can expose other potential problems like a non-linear or off-\n                                                                                set probe current meter.\n\n                                                                                           zz  Check 5: Count Rate Linearity with Effective Probe\n                                                                    Current\n                                                                  Equipment:\n                                   55 Faraday cup\n                                   55 Picoammeter\n                                   55 Flat, polished copper sample\n                                                                       Procedure:\n                                                                                       1. Mount the Faraday cup and the polished copper\n                                                                     sample on the stage at the same nominal working\n                                                                                   distance.\n                                                                                       2. Image the sample at the optimal working distance\n                                                               and a beam energy selected in the 15\u201325 keV\n                                                                            range.\n                                                                                    3.  Start a factor of 10 or more below the optimal probe\n                                                                              current. Measure and record the probe current using the\n                                                                    Faraday cup and the picoammeter.\n                                                                                    4. Collect a 60 live-time second spectrum from the copper\n                                                                        sample.\n                                                                                    5. Increase the probe current through a sequence of\n      . .\u200a\u200a\u200aFig. 16.21\u2003 The spectrum image was collected on a 128 by 128          approximately 10\u201320 steps from the initial probe current\n             pixel grid representing 4\u2009\u00d7 4 mm. After data rotation to view the x-y         to\n\n## 3. goldstein2018energydispersivexray pages 14-15 (Context ID: pqac-00000002)\n\n\n                              Y                                    distance\n                                                                                      \u03c8:\n                                                                                                    Elevation angle                                                         Actual\n                                  Z                     working                                                   Sample                                                                         distance\n\n\n\n\n                                                                                                 Sample tilt          222    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                                                                 per unit time. By spectral resolution we mean the width of\n                                                                   a characteristic peak, usually taken to be the Mn K-L2,3\n                                                             (K\u03b1) peak.\n                                                                  Higher throughput is desirable because it allows you to\n                                                                   use higher probe currents to produce more X-rays and pro-\n                                                              duce measured spectra with a larger number of measured\n                                                                         X-rays. Higher resolution is desirable because  it becomes\n                                                                             easier to distinguish characteristic peaks of similar energy.\n                                                             Both are virtues but one is achieved at the expense of the\n                                                                             other.\n                                                              The task of selecting a process time is the task of balanc-\n                                                                      ing good throughput with adequate resolution. At the best\n                                                                         resolution settings, throughput  is seriously compromised\n                                                           and as a result the precision of quantitative analysis is also\n                                                              compromised. At the highest throughput settings, resolution\n      . .\u200a\u200a\u200aFig. 16.14\u2003  Using a cell phone inclinometer to measure the eleva-                                                                                              is compromised and it becomes much more difficult to dis-             tion angle\n                                                                        tinguish interfering peaks.\n                                                                              Fortunately, resolution degrades relatively slowly while\n           correction. The elevation angle (usually sloppily called the  throughput increases quickly. Moderate pulse process times\n           \u201ctake-off angle\u201d) is often a configuration option that may be   tend to degrade the ultimate resolution by a few percent,\n           available to you to modify or may require a service engineer.   while increasing throughput by much larger factors. Every\n          Usually you can check the elevation angle by opening a spec-  vendor is different but typically a moderate pulse process\n         trum data file in a text editor. Most spectrum files are ASCII   time will produce both adequate resolution and excellent\n            text files and the vendors write a line containing the elevation   throughput.\n          or nominal take-off angle.                                 While some modern SDD are capable of ultimate resolu-\n           Compare the value produced by the software with the   tions of 122\u2013128 eV, compromising the resolution to 130\u2013\n           physical position of your detector relative to the beam axis.  135 eV  will produce an excellent compromise between\n          Sometimes, the correct instrument specific value of the take-\u00ad  resolution and throughput. Even a resolution of 140\u2013150 eV\n            off angle will be handwritten in the EDS vendor\u2019s documenta-   at high throughputs can produce  excellent  quantitative\n            tion. Other times, you can extract the angle from instrument   results because the precision of spectrum fitting is more\n            specific schematic diagrams from the SEM or EDS vendors.  determined by the number of measured X-rays than the\n           Regardless, it is a good idea to verify the elevation angle using   spectral resolution.\n          a protractor or a smart phone. Many smart phones contain\n          inclinometers which are accurate to within a degree and \u201cbub-                                                                                           zz  Check 2: Selecting a Process Time\n           ble level apps\u201d are available to turn the phone into a digital                                   55 Ensure that your EDS detector electronics are set to a           inclinometer. First, test the accuracy of the cell phone incli-                                                                    moderate process time that produces a good         nometer using a 30-60-90 triangle or similar reference shape.16                                                                    throughput with a resolution within 5 eV of the best         Then use the cell phone to measure the angle of the snout rela-                                                                                   resolution. Record this parameter in your electronic            tive to the angle of the column and calculate the elevation                                                                    notebook for future reference.           angle. .\u2003 Figure 16.14 shows that a cell phone measures the                                   55 Do not use an \u201cadaptive process time\u201d for           elevation angle of this detector to within half a degree (90\u00b0\u2013                                                                           standards-based quantitative analysis. Adaptive           54.5\u00b0 = 35.5\u00b0 ~ 35\u00b0 nominal value). Achieving similar accu-                                                                             process times allow the resolution to change with          racy with a protractor and a bubble level is difficult.                                                                       throughput making spectrum fitting challenging and\n                                                                                            less accurate.\n          16.3.2  Process Time\n                                                           The optimization of throughput is also confounded by an\n         The \u201cprocess time\u201d (also called the \u201cthroughput setting,\u201d   another practical limitation\u2014coincident X-rays or pulse-\u00ad\n          the \u201cdetector time constant,\u201d the \u201cresolution setting\u201d or  pileup\u2014and will be addressed in a later section.\n          other names) determines how much time the detector elec-\n           tronics dedicates to processing each incoming X-ray. A\n          longer  \u201cprocess  time\u201d  tends  to produce  lower X-ray   16.3.3  Optimal Working Distance\n         throughput but higher spectral resolution. Shorter \u201cpro-\n           cess times\u201d tend to produce higher X-ray throughput but   Nominally, the optimal working distance should be specified\n          lower spectral resolution. By throughput, we mean the   in instrument schematics. However,  it is worth checking\n       maximum number of X-rays that the detector can measure   because it may vary slightly or there may be a mistake in                                                                                                       223                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\ndesign or manufacturing. From the detector geometry sec-   detector element there is usually a window and an electron\ntion, we know that the optimal working distance is the dis-   trap. Most windows are ultrathin layers of polymer or sili-\ntance at which the axis along the detector snout intersects  con nitride mounted on a grid for mechanical strength.\nwith the electron beam axis (see .\u2003 Fig. 16.13). This working  Examples of two support grids are given in .\u2003 Fig. 16.15.\ndistance should also produce the largest flux of X-rays and be  While the grid may have an open area fraction of 75\u201380\u2009%,\nthe distance which is least sensitive to slight errors in vertical   the  silicon or carbon  grid  bars  are  often very  thick\npositioning.                                                  (0.38 mm) to enhance mechanical rigidity under the strain\n                                     \n\n## 4. goldstein2018energydispersivexray pages 11-14 (Context ID: pqac-00000003)\n\n                  the crystal mounted at the end of the snout and the face of\n 6. Use your vendor\u2019s software (or NIST DTSA-II) to         the active detector element perpendicular to the principle\n     integrate the background-corrected intensity in the Al     axis of the snout. The principal axis of the snout is oriented in\n   K peak (E\u2009=\u20091.486 keV).                                 the instrument such that it intersects with the electron beam\n 7. Use your vendor\u2019s software (or NIST DTSA-II) to look     axis at the \u201coptimal working distance.\u201d This geometry is illus-\n     for and integrate the background-corrected intensity in    trated in .\u2003 Fig. 16.11.\n    the Al K\u2009+\u2009Al K coincidence peak (E\u2009=\u20092.972 keV).           Often the detector is mounted on the flange on a sliding\n 8. Determine the ratio of the integrated intensity I(Al      mechanism that allows the position of the detector to trans-\n    K\u2009+\u2009Al K)/I(Al K). We desire this ratio to be smaller         late (move in and out) along the axis of the snout. The eleva-\n    than 0.01 (1\u2009%). In some trace analysis situations, it may   tion angle is nominally held fixed during the translation but\n     desirable to have this ratio less than 0.001 (0.1\u2009%).         the distance from the detector crystal changes and along with\n     Setting this limit too low will limit throughput but            it the solid angle (\u03a9) subtended by the detector. The solid          220    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.11\u2003 The elevation\n            angle is a fixed property of the\n                                                                        C            instrument/detector                                                                                         L\n\n\n\n                                                                                                Objective\n                                                                                                        lens\n\n                                                                                                         snout\n                                                                                                                     detector\n                                                Axes     X                               EDS\n\n                                       Y\n\n                                                                           Optimal\n                                           Z                        working           \u03c8:\n                                                                                  distance                Elevation angle\n\n                                                           Sample\n\n\n\n\n\n      . .\u200a\u200a\u200aFig. 16.12\u2003 The solid angle is a\n            function of sample-to-detector\n            distance and the active detector                                                           CL\n            area\n\n\n\n                                                                                                  Objective\n                                                                                                          lens\n\n16\n\n\n\n\n                                                                                                         Detector\n                                                           W      crystal\n\n\n\n                                                            Sample                                                                                                     Sample-to\n                                                                                                                 -detector\n                                                                                                               distance\n\n\n\n\n\n          angle is illustrated in the .\u2003 Fig. 16.12. Moving the detector        It is important to be able to maintain a reproducible solid\n         away from the sample is designed to decrease the solid angle   angle through consistent repositioning of the detector. Some\n          but does not change the elevation angle or the optimal work-   slide mechanisms are motorized. Motorized mechanisms\n          ing distance.                                             should  define an  \u201cinserted\u201d  position and a  \u201cretracted\u201d                                                                                                          221                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\nposition, which you should test to ensure that the positioning       4.  Test the reproducibility of the insertion point by\nis reproducible between insertions. Manual mechanisms usu-          extracting and inserting the detector and collecting a\nally provide a threaded screw with a manual crank to pull the           series of spectra. If the characteristic peak intensities\ndetector in and out. The threaded screw will usually have a          are reproducible (to much better than a fraction of a\npair of interlocking nuts which can be positioned to define a          percent) between insertions, the precision is adequate.\nconsistent insertion position. The procedure in the sidebar\nbelow will allow you to set and maintain a constant solid  The take-off angle is the angle at which X-rays exit a flat sam-\nangle and thus also a consistent detector collection efficiency.   ple in the direction of the detector. For a flat sample mounted\n                                                          perpendicular to the electron beam at the optimal working\n                                                                 distance, the take-off angle equals the elevation angle. If the\nzz  Sidebar: Setting a Constant Detector-to-Sample        sample is tilted or the sample surface is at a slightly different\n   Distance to Maintain Solid Angle                     working distance, then the take-off angle can be computed\n    1.  Locate the pair of lock nuts on the screw mechanism.  from the sample tilt, the working distance and the sample-to-\n     Move the lock nuts to the inner most position on the   detector distance. This is shown in .\u2003 Fig. 16.13. Often you\n       treaded rod.                                                will hear the terms elevation angle and take-off angle used\n    2.  Insert the detector as close to the sample as possible.    interchangeably. It is more precise however to think of the\n      Ensure that the detector does not touch the interior     elevation angle as being a fixed property of the instrument/\n       of the microscope. The detector snout must be          detector geometry and the take-off angle being dependent\n        electrically isolated (no conductive path) from the     upon instrument-specimen configuration.\n       interior of the chamber to eliminate noise caused by\n        electrical ground loops.                                        zz  Check 1: Verify the Elevation Angle\n    3.  Twist the upper lock nut to limit the motion of the        It is critical that your quantitative analysis software has the\n       detector towards the sample. Tighten the lower nut     correct elevation/take-off angle. Matrix correction \u00adalgorithms\n       to lock the upper nut into position.                   use the take-off angle to calculate the correct absorption\n\n. .\u200a\u200a\u200aFig. 16.13\u2003 The take-off angle\nis a function of the elevation angle,\nthe sample tilt and the actual                                               C                                                                                  L\nworking distance\n\n\n\n                                                                                        Objective\n                                                                                               lens\n\n\n                                                                                                 snout\n                                                                                                           detector                                                     Optimal                       EDS\n                                      Axes      X           working\n                              Y                                    distance\n                                                                                      \u03c8:\n                                                                                                    Elevation angle                                                         Actual\n                                  Z                     working                                                   Sample                                                                         distance\n\n\n\n\n                                                                                                 Sample tilt          222    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and\n\n## 5. goldstein2018energydispersivexray pages 15-16 (Context ID: pqac-00000004)\n\nat the optimal working distance is the dis-   trap. Most windows are ultrathin layers of polymer or sili-\ntance at which the axis along the detector snout intersects  con nitride mounted on a grid for mechanical strength.\nwith the electron beam axis (see .\u2003 Fig. 16.13). This working  Examples of two support grids are given in .\u2003 Fig. 16.15.\ndistance should also produce the largest flux of X-rays and be  While the grid may have an open area fraction of 75\u201380\u2009%,\nthe distance which is least sensitive to slight errors in vertical   the  silicon or carbon  grid  bars  are  often very  thick\npositioning.                                                  (0.38 mm) to enhance mechanical rigidity under the strain\n                                                               of up to one atmosphere of differential pressure. Off-axis\nzz  Check 3: Measuring the Optimal Working Distance       the grid bars can occlude the direct transmission of X-rays\n    1.  Select a sample like a piece of copper and mount it     from the sample to the detector element. Furthermore, the\n       perpendicular to the electron beam axis.             magnetic electron trap can also occlude X-rays from off-\n    2.  Select a beam energy of 15\u201325 keV and a moderate      axis. As a result, an EDS detector is more sensitive to X-rays\n      probe current to produce\u2009~\u200920% dead time.           produced on the snout axis than slightly off the axis. The\n    3. Move the stage\u2019s vertical axis to place the sample        result is a position dependent efficiency which peaks on\n       close to the objective lens pole piece. Be careful not     axis and decreases as the source of the X-rays is further\n       to run the sample into a detector.                  from axis.\n    4. Focus the image and record the working distance      A wide field-of-view X-ray spectrum image can demon-\n       reported by your SEM\u2019s software.                         strate the position sensitivity and can be used to ensure that\n    5.  Collect a 60 live-time second spectrum.                the detector snout and detector active element are oriented\n    6. Move the stage away from the objective lens pole        correctly.\n       piece in 1-mm steps.\n    7.  Repeat steps 4\u20136, taking the working distance             zz  Check 4: Collect a Wide Field X-ray Spectrum Image\n      through the nominal optimal working distance.              1. Mount a flat, polished piece of Cu in your SEM.\n    8.  Process the spectra. Extract the total number of              2. Image the Cu at the optimal working distance and at\n      counts in the energy range from about 100 eV to the         20\u201325 keV to excite both the K and L lines.\n     beam energy and plot this number against the                3. Find out how wide a field-of-view your SEM can\n      working distance.                                      image at the optimal working distance. The example\n    9. Determine the working distance which produces the           in .\u2003 Fig. 16.16 uses a 4-mm field-of-view.\n        largest number of counts. Since this working distance       4.  Collect a high count X-ray spectrum image from the\n       represents an inflection point, the slope will be              Cu. Acquiring at a moderate-to-high probe current\n     minimum and thus the sensitivity with respect to               for an hour or more at 256 \u00d7\u2009256-pixel image\n      working distance will also be minimized.                   dimensions should produce sufficiently high\n                                                                      signal-to-noise data.\n                                                                           5.  Process the data to extract and plot the raw\n16.3.4  Detector Orientation                                   intensities at each pixel in each of the Cu K-L2,3 and\n                                                Cu L-family lines.\nIn the previous section, we assumed that the principal axis of           1.  It is important to extract the raw intensities and\nthe detector snout is oriented to intersect with the electron            not the normalized intensities since we are\nbeam axis. In other words, the detector points towards the            looking for variation in the raw intensity as a\nsample. It is usually the EDS vendor\u2019s responsibility to ensure            function of position.\nthat the mounting flange has been designed to correctly ori-           2. The open source software ImageJ-Fiji (ImageJ\nent and position the detector. The next check will verify this.             plus additional tools) can be used to process\n   The active face of an EDS detector is a planar area that is           spectrum image data if it can be converted to a\nmounted perpendicular to the snout axis. In front of the       RAW format.\n\n\n\n                                AP3          AP5\n Thickness (\u00b5m)                      380           265\n Rib width (\u00b5m)                       59            45\n Opening width (\u00b5m)                  190           190             Thickness\n\n Open area %                    76%         78%\n                                                                                    Rib                     Opening\n Acceptance angle                     53\u00b0             72\u00b0                       width                    width\n\n. .\u200a\u200a\u200aFig. 16.15\u2003 Window support grid dimensions for two common window types (Source: MOXTEK)           224    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                6.  Plot the data to demonstrate the variation of the                nished intensities leading to low analytical totals\n                   intensity as a function of position. .\u2003 Figure 16.16              and sub-optimal quantitative results.\n               shows the map from a well-oriented detector plotted            3.  Typically, the Cu L-family peak is more sensi\u00adtive\n                using a thermal color scheme in which red                   due to absorption by the vacuum window support\n                 represents the highest intensity and blue represents                 grid\u2019s Si ribs. .\u2003 Figure 16.15 (source: Moxtek)\n                 zero intensity. .\u2003 Figure 16.17 shows traverses                 shows the design of two recent Moxtek support\n                 extracted from the .\u2003 Fig. 16.16 data on diagonals                  grids. The vertical sensitivity is usually minimized\n                 representing parallel to the detector axis and                  by orienting the grid ribs vertically.\n                perpendicular to the detector axis. Verify that the\n              most intense region in the intensity plots is in the\n                 center of the image area.                                       zz  Sidebar: Processing a \u201cRAW\u201d Spectrum Image with\n                7. Note the extent of the region of uniform efficiency.         ImageJ-Fiji\n                 Variation from ideal uniform sensitivity has                  1. Convert the X-ray spectrum image data into a RAW\n                consequences.                                                                    file. A RAW file is large binary representation of the\n                    1. Low magnification X-ray spectrum images will            data in the spectrum image. Each pixel in the\n                       suffer from reduced intensity towards the edges.          spectrum image consists of a spectrum encode in an\n                    2. Point mode X-ray spectrum acquisitions collected          integer binary format. The pixels are organized in a\n                        off the optical axis will also suffer from dimi\u00ad             continuous array row-by-\u00adrow. The size of the file is\n                                                                                      typically equal to (channel depth)\u2009\u00d7\u2009(row\n                                                                         dimension)\u2009\u00d7\u2009(column dimensions)\u2009\u00d7\u2009(2 or 4 bytes\n                                                                         per integer value).\n                                   255.0                                                                                        2. Import the RAW data file into ImageJ using the\n                                                                      \u201cImport \u2192 Raw\u201d tools to create a \u201cstack\u201d as shown in                   Detector                                                       .\u2003 Fig. 16.18.\n                                                                                        3. As imported, the orientation of the stack will depend\n                                                               upon how the data in the RAW file is organized.\n                                                                              Regardless of the original orientation, you will need to\n                                                                                 pivot the data a couple times using the \u201cImage \u2192\n             \n\n## 6. goldstein2018energydispersivexray pages 20-22 (Context ID: pqac-00000005)\n\n line or the zero  Most (but not all) modern EDS detectors have a vacuum\nstrobe at low energy and a second characteristic line at high   tight window that is opaque to infrared and visible light.          228    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.24\u2003 The position and\n           widths of the characteristic peaks\n           should not vary with probe cur-\n             rent                               15 000\n\n                                                                                                                 Counts 10 000\n\n                                             5 000\n\n\n\n                                                0\n                                                               7.7        7.9        8.1        8.3        8.5        8.7        8.9        9.1\n                                                                                     Energy (keV)\n\n\n\n                                            150 000\n\n\n\n                                            100 000                                                                                                                 Counts\n\n\n                                             50 000\n\n\n\n                                                 0\n                                                          0.68                0.78                0.88               0.98                1.08\n                                                                                      Energy (keV)\n\n\n           Usually, the window is coated with a thin layer of aluminum   16.3.8  Setting Up a Quality Control Program\n           (or other metal) to keep light in the chamber from creating a\n          spurious signal on the EDS detector.                 An ongoing QC program is a valuable way to demonstrate\n              Regardless, it is worthwhile to test whether your detector   that your data and results can be trusted\u2014\u2014yesterday, today,\n              is sensitive to light. You may be surprised by a pinhole light  and tomorrow. If a client ever questions some data, it is useful\n           leak or a window without an adequate opaque layer.           to be able to go back to the day that data was collected and16                                                         show that your instrument and detector were performing\n             zz  Check 6: Check for SEM Light Sources                     adequately. A well-designed QC program need not take\n         The windows on some EDS detectors are not opaque to light  much time. A single spectrum from a consistent sample col-\n         and light in the chamber will produce noise counts particu-   lected under consistent conditions is sufficient to identify\n            larly in low channels.                                  most common failure modes and to document the long-term\n            1.  Enumerate the potential sources of light inside your      performance of your detector. A well-designed QC program\n           SEM. Sources to consider:                                          is likely to save time by eliminating the possibility of collect-\n                1. An IR camera                                        ing data when the detector is miscalibrated or otherwise\n                2.  Stage position sensors                               misbehaving.\n                3. The tungsten filament (essentially a light bulb)\n                4. Chamber windows                                              zz  Check 7: Implement a Quick QC Program\n                5. Cathodoluminescence from samples like zinc                1.  Maintain a sample consisting of a Faraday cup and a\n                  selenide or benitoite.                                         piece of Cu or Mn. Make use of this sample each day\n            2.  Collect a series of spectra and examine these spectra for        on which you intend on collecting quantitative EDS\n              anomalies.                                                     data to ensure that the detector is calibrated.\n                1. When possible collect the spectra without an electron       2.  Image the sample at a consistent working distance\n             beam so there should be no source of X-rays.                  (the \u201coptimal working distance\u201d), a consistent beam\n                2.  Collect a spectrum with the light source turned off            energy, and a consistent probe current.\n              and a spectrum with the source on. There should be         3.  Collect a spectrum from a sample for a consistent\n              no difference.                                                    live-time.                                                                                                       229                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n    4.  Process the spectrum to extract the raw intensities in           ideal because it is readily available, stable and has\n       the K-L2,3 and L-family lines, the resolution, the actual        both K-L2,3 (~8.04 keV) and L-family (~930 eV)\n       zero offset and gain, and the total number of counts.             lines.\n      Record and plot these values on a control chart.      55 The beam energy should be sufficient to adequately\n                                                                         excite (overvoltage\u2009>\u20092) all the lines of interest in the\nUsing the QC Tools Within DTSA-II                        sample.\nWhile it is possible to implement a QC program by combining   55 The nominal working distance should be the\nan EDS  vendor\u2019s  software  with  careful  record-keeping,          detector\u2019s optimal working distance. The sample\nDTSA-II provides tools specifically designed to implement a        should be brought into focus (using the stage Z-axis if\nbasic EDS detector QC program. The tools import spectra,         necessary) at this working distance before collecting a\nmake some basic sanity checks, process the spectrum to extract        spectrum.\nQC metrics, archive the metrics and report the metrics.      55 The nominal probe current is the probe current at\n                                                         which the spectra will be collected (to within a few\nCreating a QC Project                                          percent). Usually, the \u201cuse probe current\n5 5 A QC project is an archive of spectra collected from a           normalization\u201d will be selected so that all intensities\n    specified sample under similar conditions on a specified         are scaled relative to the probe current measured with\n   detector/instrument. The spectra are fitted with a               a in-lens cup or a Faraday cup.\n   modeled spectrum and the resulting quantities      55 After creating the project, you will need to go\n   recorded to track these values over the lifetime of the        through the QC tool additional times to add measured\n    detector.                                                      spectra.\n5 5 Creating a QC Project involves specifying a detector\n   and the conditions which are to be held consistent\n    (.\u2003 Fig. 16.25). If you use a single detector with different     zz  Adding Spectra to a QC Project\n   process times, either select a constant process time or,    55 To add spectra to a QC project, you first need to\n    better yet, create individual projects for each process              specify which project you will be adding the spectra.\n   time.                                              Once you select the project, the \u201cmaterial,\u201d \u201cbeam\n  5 5 The material may be simple or complex but                    energy,\u201d \u201cnominal working distance,\u201d and \u201cnominal\n      should be robust, durable and provide characteristic         probe current\u201d boxes will fill with the associated\n       lines over a large range of energies. Copper is                information (see .\u2003 Fig. 16.26).\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.25\u2003 The panel in\nDTSA-II for creating QC projects.\nThis panel is accessed through\nthe \u201cTools \u2192 QC Alien\u201d menu item          230    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.26\u2003  Panel for selection\n             of detector and material para\u00ad\n           meters\n\n\n\n\n\n      55 Once the project has been selected, you will need to      You will specify the detector and QC project along with\n                  specify a spectrum to add to the project. Needless to    the fit values that you wish to report. The report will be gen-\n                    say, the spectrum should have been collected on the    erated into a new HTML document and the result displayed\n                  correct detector under the conditions specified (see     in your system\u2019s default web browser. The report will look\n                  .\u2003 Fig. 16.27).                                               like .\u2003 Fig. 16.30, with h\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=21 | Relevant Papers=1 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0763 | Disease-Target Evidence=0",
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+                "content": "## 1. goldstein2018quantitativeanalysisthe pages 8-9 (Context ID: pqac-00000006)\n\nAnalysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n         20.3 Examples of the k-ratio/Matrix              the error budget. In this analysis and the analyses reported\n             Correction Protocol with DTSA II            below, the relative deviation from the expected value (RDEV)\n           (Newbury and Ritchie 2015b)                    (also referred to as \u201crelative error\u201d) is calculated with the\n                                                                       \u201cexpected\u201d value taken as the stoichiometric formula value or\n          20.3.1  Analysis of Major Constituents            the value obtained from an \u201cabsolute\u201d analytical method, just\n                 (C\u2009>\u20090.1 Mass Fraction) with                 as in gravimetric analysis:\n               Well-\u00adResolved Peaks                                                                                         \uf8ee ( Analyzed value \u2212 expected value ) \uf8f9\n                                                  RDEV = \uf8ef                                 \uf8fa \u00d7 100%    (20.3)\n         The EDS spectra of the minerals pyrite (FeS2) and troilite               \uf8f0         expected value         \uf8fb\n          (FeS) measured at E0\u2009=\u200920 keV with a dead-time of\u2009~\u200910\u2009% are\n        shown in .\u2003 Fig. 20.4 and feature well separated peaks for the  Optimizing Analysis Strategy\n         Fe K- and L- families and the S K-family. These spectra were                                                           The DTSA II analysis report includes for each analyzed ele-\n          analyzed with Fe and CuS serving both as peak-fitting refer-                                                         ment the ZAF factors and the estimated uncertainties in\n          ences and as standards. CuS is chosen for the S reference and                                                                        these factors as well as uncertainties due to the counting sta-\n          standard rather than elemental S since CuS is stable under                                                                                          tistics associated with the measurements of the unknown and\n           electron bombardment while elemental S is not stable. The                                                                           of the standard (Ritchie and Newbury 2012). Careful exami-\n         spectrum for FeS and the residual spectrum after peak-fitting                                                                     nation of these factors can be used to refine the analytical\n           are also shown in .\u2003 Fig. 20.4. The results for seven replicate                                                                           strategy to optimize the measurement. Reducing the uncer-\n           analyses are listed in .\u2003 Table 20.1 (FeS) and .\u2003 Table 20.2 (FeS2)   tainty due to the counting statistics requires increasing the\n          along with the ZAF correction factors and the \u00adcomponents of                                                                        dose. The absorption factor A is strongly influenced by the\n\n\n\n             a  180 000                                                                                                                                                FeS_20kV10n9%DT_50s\n                                                                                                                                                FeS_20kV10n9%DT_50s\n                160 000\n                                                                                     E0 = 20 KeV\n                140 000                                                                           FeS\n                120 000                                                      FeS2\n                                   Counts 10080 000000\n\n                 60 000\n\n                 40 000\n\n                 20 000\n\n                      0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                  Photon energy (keV)\n\n           b\n                 14 000                                                                                                            FeS_20kV10n9%DT_50s\n                                                                                                                                                 Residual_FeS_20kV10n9%DT_50s\n\n                 12 000\n                                                                           E0 = 20 KeV\n                 10 000                                          FeS\n                                                                                   Fitting residual\n                                   Counts   8 00020              6 000\n\n                  4 000\n\n                  2 000\n\n                      0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                  Photon energy (keV)\n\n\n      . .\u200a\u200a\u200aFig. 20.4\u2003  a SDD-EDS spectra of Pyrite (FeS2) (blue) and meteoritic Troilite (FeS (red) at E0\u2009=\u200920 keV. b NIST DTSA-II analysis of FeS using Fe and\n          CuS as peak-fitting references and as standards. The original spectrum (red) and the residual spectrum after peak-fitting (blue) are shown                                                                                                               317                                      20\n20.3 \u00b7 Examples of the k-ratio/Matrix Correction Protocol with DTSA II\n\n\n\n  . .\u200a\u200a\u200aTable 20.1\u2003  Analysis of FeS (meteoritic troilite) at E0\u2009=\u200920 keV     . .\u200a\u200a\u200aTable 20.3\u2003  Analysis of FeS at E0\u2009=\u200910 keV with CuS and Fe as\n    with CuS and Fe as fitting references and standards Integrated              fitting references and standards Integrated spectrum count,\n    spectrum count, 0.1\u201320 keV\u2009=\u20097,048,000; uncertainties expressed         0.1\u201310 keV\u2009=\u20095,630,000; uncertainties expressed in mass\n    in mass fraction. Analysis performed with Fe K-L2,3 and S K-L2,3              fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.5052        0.4948              Cav (atom frac)                     0.503           0.497\n\n    Z-correction                        0.977          0.95               Z-correction                       0.973           0.937\n\n    A-correction                        1.118          0.983              A-correction                      1.041           0.997\n\n    F-correction                        1.003         1                  F-correction                       1.001          1\n\n   \u03c3 (7 replicates)                     0.00075       0.00075         \u03c3 (7 replicates)                    0.00056         0.00056\n     \u03c3Rel (%)                             0.15\u2009%         0.15\u2009%                \u03c3Rel (%)                            0.11\u2009%           0.11\u2009%\n   RDEV (%)                           1.00\u2009%       \u22121.00\u2009%          RDEV (%)                          0.59\u2009%        \u22120.59\u2009%\n\n   C (mass frac, single analysis)         0.3699        0.6305          C (mass frac, single analysis)        0.3627          0.6257\n\n    Counting error, std                 0.00020       0.0003           Counting error, std                0.0002          0.0008\n\n    Counting error, unk                 0.00020       0.0007           Counting error, unk                0.0003          0.0018\n\n    A-factor error                       0.0017        0.0002             A-factor error                     0.0006          4.10E-05\n\n    Z-factor error                       2.20\u00d7105      4.10\u00d710\u20136           Z-factor error                      2.20\u00d710\u20135       1.30\u00d710\u20136\n\n   Combined errors                   0.0017        0.0008          Combined errors                  0.0007          0.0019\n\n\n\n  . .\u200a\u200a\u200aTable 20.2\u2003  Analysis of FeS2 (pyrite) at E0\u2009=\u200920 keV with CuS      . .\u200a\u200a\u200aTable 20.4\u2003  Analysis of FeS2 at E0\u2009=\u200910 keV with CuS and Fe as\n   and Fe as fitting references and standards Integrated spectrum             fitting references and standards Integrated spectrum count,\n    count, 0.1.\u201320 keV\u2009=\u20097,765,000; uncertainties expressed in mass          0.1\u201310 keV\u2009=\u20096,253,000); uncertainties expressed in mass\n     fraction. Analysis performed with Fe K-L2,3 and S K-L2,3                       fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.6726        0.3274              Cav (atom frac)                     0.671           0.329\n\n    Z-correction                        0.957          0.928              Z-correctio\n\n## 2. goldstein2018quantitativeanalysisthe pages 4-6 (Context ID: pqac-00000007)\n\n 20 000\n\n\n\n                     0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                 Photon energy (keV)\n\n                100 000\n                                                                                                                                         Mn_20kv10nA110kHz10DT\n\n\n                 80 000\n\n                                                                                            5 eV bin width\n                 60 000\n                                   Counts\n                                                                  FWHM = 126 eV                 40 000\n\n\n\n                 20 000\n\n\n\n                     0\n                         5.60      5.65      5.70      5.75      5.80      5.85      5.90      5.95      6.00      6.05      6.10      6.15      6.20\n                                                                 Photon energy (keV)\n\n\n      . .\u200a\u200a\u200aFig. 20.1\u2003 SDD-EDS spectrum of Mn (E0\u2009=\u200920 keV)\n\n          energy, E0. The energy span is given by the channel width   photoelectron to determine the photon energy, and incre-\n          multiplied by the number of channels. With a 5-eV chan-  menting the appropriate energy bin in the EDS histogram\n          nel width, a choice of 4096 channels will provide access to  by one count. The EDS time constant (also known as the\n         photon energies as high as 20.48 keV. For beam energy   shaping time, the processing time, the maximum through-\n         above 20 keV, the number of channels should be increased   put, or other terms in different vendor EDS systems) effec-\n           to retain the 5-eV channel width, or alternatively the chan-   tively  determines  the amount  of  time  spent on  the\n          nel width can be increased to 10 eV, but with the conse-  measurement cycle. A short time constant enables more\n20      quence that fewer channels will describe each characteristic  photons to be processed per unit of real (clock) time, but\n          peak.                                                      the trade-off of faster processing  is poorer accuracy in\n                                                                      assigning the photon energy. While the characteristic X-ray\n      EDS Time Constant (Resolution                   peak has a sharply defined energy, with a natural peak width\n       and Throughput)                                         of a few eV or less, the EDS measurement process inevitably\n         The EDS is only capable of processing one photon at a time.   substantially broadens the measured peak. For example,\n         The basic measurement cycle is the photoelectric absorp-  Mn K-L2,3 has a natural width of approximately 7 eV (deter-\n           tion of the photon in the detector active volume, measure-  mined as the FWHM) but as displayed in the EDS histo-\n        ment  of  the  charge  deposited  by  scattering  of  the  gram, the Mn K-L2,3 peak is broadened to 122\u2013150 eV                                                                                                               313                                      20\n20.2 \u00b7 Instrumentation Requirements\n\n\nFWHM or more, depending on the choice of time constant.   reproducible choice must be made for r since this value has\nFor the particular silicon drift detector (SDD)-EDS and  such a strong impact on \u03a9 and thus on the number of pho-\ntime constant shown in .\u2003 Fig. 20.1, the broadened EDS   tons detected per unit of dose.\npeak has a FWHM\u2009=\u2009126 eV. The peak width increases (i.e.,\nresolution becomes poorer) as the time constant decreases.\nThe shortest time constant, which gives the highest through-   20.2.2  Choosing the Beam Energy, E0\nput but the broadest peaks (poorest resolution), is typically\nchosen for analysis situations where it is important to max-  The choice of beam energy depends on the particular\nimize the total number of X-ray counts per unit of clock   aspects of the analysis that the analyst wishes to optimize.\n(real) time, such as elemental X-ray mapping. For quantita-  As a starting point, a useful general analysis strategy is to\ntive analysis, better peak resolution is desirable, and thus a  optimize the excitation of photon energies up to 12 keV\nlonger time constant should be chosen. Whichever time  by choosing an incident beam energy of 20 keV, which\nconstant strategy is selected, it is important for standards-   provides sufficient overvoltage (E0/Ec\u2009>\u20091.5) for K-shell\nbased quantitative analysis that this same time constant be   (to Br) and L-shell (elements to Bi) for reasonable excita-\nused for all measurements of unknowns and standards,   tion. The characteristic peaks of X-ray families that occur\nespecially if archived standards are used.                     in the photon energy range from 4 keV to 12 keV are gen-\n                                                                 erally sufficiently separated in energy to be resolved by\nEDS Calibration                                 EDS. When  it is important to measure those elements\nAssigning the proper energy bin for a photon measure-  whose characteristic peaks occur below 4 keV, and espe-\nment depends on the EDS being calibrated. The vendor for   cially for the low atomic number elements Be, B, C, N, O\na particular EDS system will have a recommended calibra-  and F, for which the characteristic peaks occur below\ntion procedure that should be followed on a regular basis  1 keV and suffer high absorption, then analysis with\nas part of establishing a quality measurement environ-  lower beam energy, 10 keV or lower, will be necessary to\nment, with full documentation of the measurements to  optimize the results.\nestablish the on-\u00adgoing calibration record. A typical cali-\nbration strategy is to choose a material such as Cu that\nprovides (with E0\u2009\u2265\u200915 keV) strongly excited peaks in the   20.2.3  Measuring the Beam Current\nlow photon energy range (Cu L3M5\u2009=\u20090.93 keV) and the\nhigh  photon  energy  range  (Cu  K-L2,3\u2009=\u20098.04  keV).  The SEM should be equipped for beam current measure-\nAlternatively, some EDS systems that provide a \u201czero  ment, ideally with an in-column Faraday cup which can be\nenergy reference\u201d signal will use this value with a single   selected periodically during the analysis procedure to\nhigh photon energy peak such as Cu K-L2,3 or Mn K-L2,3 to  determine the beam current. As an alternative, a picoam-\nperform calibration. A good quality assurance practice is  meter can be installed between the electrically isolated\nto begin each measurement campaign by measuring a  specimen stage and the electrical ground to measure the\nspectrum of Cu (or another element, e.g., Mn, Ni, etc., or a  absorbed (specimen) current that must flow to ground to\ncompound, e.g., CuS, FeS2, etc.) under the user-defined   avoid specimen charging. The specimen current is the dif-\nconditions. This Cu spectrum can be compared to the Cu   ference between the beam current and the loss of charge\nspectrum that is stored in the archive of standards to con-  due to BSE and SE emission, both of which vary with com-\nfirm that the current measurement conditions are identi-   position. To measure the true beam current, BSE and SE\ncal to those used to create the archive. This starting Cu  emission must be recaptured, which is accomplished by\nspectrum should always be saved as part of the quality   placing the beam within a Faraday cup, which is con-\nassurance plan.                                            structed as a blind hole in a conducting material (e.g.,\n                                                      metal or carbon) covered with a small entrance aperture\nEDS Solid Angle                                                   (e.g., an electron microscope aperture of 50 \u03bcm diameter\nThe solid angle of collection, \u03a9, is given by                  or less). This Faraday cup is then placed at a suitable loca-\n                                                            tion on the electrically isolated specimen stage. By locat-\n   \u2126= A / r 2                                           (20.1)   ing the beam in the center of the Faraday cup aperture\n                                                        opening, the primary beam electrons as well as all BSEs\nwhere A is the active area of the detector and r is the distance  and SEs generated at the inner surfaces are collected with\nfrom the X-ray source on the specimen to the detector. Some   very little loss through the small aperture, so that the cur-\nEDS  systems  are mounted on  a  retractable arm  that   rent flowing to the electrical ground is the total incident\nenables the analyst to choose the value of r. A consistent and  beam current.           314    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n          \n\n## 3. goldstein2018quantitativeanalysisthe pages 9-11 (Context ID: pqac-00000008)\n\ne as\n   and Fe as fitting references and standards Integrated spectrum             fitting references and standards Integrated spectrum count,\n    count, 0.1.\u201320 keV\u2009=\u20097,765,000; uncertainties expressed in mass          0.1\u201310 keV\u2009=\u20096,253,000); uncertainties expressed in mass\n     fraction. Analysis performed with Fe K-L2,3 and S K-L2,3                       fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.6726        0.3274              Cav (atom frac)                     0.671           0.329\n\n    Z-correction                        0.957          0.928              Z-correction                       0.95             0.91\n\n    A-correction                        1.181          0.975              A-correction                      1.061           0.995\n\n    F-correction                        1.003         1                  F-correction                       1.001          1\n\n   \u03c3 (7 replicates)                     0.000314      0.000314        \u03c3 (7 replicates)                    0.0007          0.0007\n     \u03c3Rel (%)                             0.05\u2009%         0.10\u2009%                \u03c3Rel (%)                            0.11\u2009%           0.21\u2009%\n   RDEV (%)                           0.88\u2009%       \u22121.80\u2009%          RDEV (%)                          0.65\u2009%        \u22121.30\u2009%\n\n   C (mass frac, single analysis)         0.5485        0.4657          C (mass frac, single analysis)        0.537           0.4618\n\n    Counting error, std                  0.0003        0.0002           Counting error, std                0.0003          0.0006\n\n    Counting error, unk                 0.0003        0.0006           Counting error, unk                0.0003          0.0016\n\n    A-factor error                       0.0023        0.0002             A-factor error                     0.0008          4.30E-05\n\n    Z-factor error                       3.30\u00d710\u20135      2.90\u00d710\u20136          Z-factor error                      3.20\u00d710\u20135       9.60\u00d710\u20137\n\n   Combined errors                   0.0023        0.0007          Combined errors                  0.0009          0.0017\n\n\nchoice of beam energy. If the beam energy can be decreased,  10 keV gives the results shown in .\u2003 Tables 20.3 and 20.4. The\nconsidering also the constraints imposed by having sufficient   absorption factor A from is reduced from 1.118 to 1.04 for S\novervoltage for all elements to be analyzed, the absorption   in FeS and from 1.18 to 1.06 for S in FeS2, and the relative\ncorrection factor and its uncertainty can also be reduced. For   errors are also reduced slightly, from 1 to 0.59\u2009% for S in FeS\nthe Fe-S examples, lowering the beam energy from 20 to  and from 0.88 to 0.65\u2009% for S in FeS2.           318    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n          20.3.2  Analysis of Major Constituents            separated by 36 eV, as shown in .\u2003 Fig. 20.5. Analysis of PbS\n                 (C\u2009>\u20090.1 Mass Fraction) with Severely    with DTSA II using CuS and PbSe as peak-fitting references\n             Overlapping Peaks                       and as standards yields the results in .\u2003 Table 20.5. Despite\n                                                                      the severe peak interference, the relative error based on the\n                                                                 formula stoichiometry is only \u00b11.2\u2009% for S and Pb.\n       PbS                                                                Note that an alternative analytical approach would be to\n         The throughput and the peak stability (calibration and reso-   select the beam energy such that E0\u2009\u2265\u200920 keV so that the Pb\n           lution) of SDD-EDS spectrometry enable collection of high   L-family is excited (LIII\u2009=\u200913.04 keV). With this choice of exci-\n          count, high quality spectra (>5 million counts) within mod-   tation, the Pb L3-M4,5 peak at 10.55 keV, which does not suffer\n            est measurement time, 100 s or less. High count spectra   interference, could be chosen to measure Pb. Of course, the S\n          enable measurements of minor and trace constituents with  K still must be deconvoluted from the interference from the\n          high precision. High counts and stable peak structures are  Pb M-family since there is no alternate peak to measure for S.\n             critical for successful peak intensity measurements by peak-\u00ad\n             fitting methods, which is especially important for situations  MoS2\n         where two or more peaks are so close in photon energy that  MoS2 represents an even greater analytical challenge because\n          the EDS resolution function convolves the peaks into mutual   the peaks that must be used for analysis, S K-L2 (2.307 keV)\n           interference. Despite extreme peak interference, quantitative  and Mo L3-M4,5 (2.293 keV), are separated by only 14 eV, as\n          X-ray microanalysis can be achieved with RDEV values of  shown in .\u2003 Fig. 20.6. Analysis of MoS2 with DTSA II using\n          5\u2009% relative or less (Newbury and Ritchie 2015a).          CuS and Mo as peak-fitting references and as standards yields\n           PbS (galena) represents a challenging analysis situation   the results in .\u2003 Table 20.6. Despite the severe peak interfer-\n           for EDS because of the severe interference between the S   ence, the relative error based on the formula stoichiometry is\n         K-L2 (2.307 keV) and Pb M5-N6,7 (2.343 keV), which are   only \u22120.34\u2009% for S and 0.7\u2009% for Mo.\n\n\n             a 120 000                                                                                                                    PbS_10kV20nA\n                                                                                                                                                           Residual_PbS_10kV20nA\n\n                100 000                                                                                                   E0 = 10 KeV\n                                                                                PbS\n                 80 000                                                                                Fitting residual\n\n\n                 60 000                                   Counts\n\n                 40 000\n\n\n                 20 000\n\n\n                     0\n                            1.5          1.7          1.9          2.1          2.3          2.5          2.7          2.9          3.1          3.3\n                                                                   Photon energy (keV)\n\n           b                                                                                                                             PbS_10kV20nA\n                 14 000                                                                                                                            Residual_PbS_10kV20nA\n\n                 12 000\n\n                 10 000\n\n                  8 00020                         Counts\n                  6 000\n\n                  4 000\n\n                  2 000\n\n                     0\n                            1.5          1.7          1.9          2.1          2.3          2.5          2.7          2.9          3.1          3.3\n                                                                   Photon energy (keV)\n\n\n      . .\u200a\u200a\u200aFig. 20.5\u2003  a SDD-EDS spectrum of PbS (red) and residual (blue) after DTSA II analysis using CuS and PbSe as fitting references and standards.\n         b Expanded view                                                                                                              319                                      20\n20.4 \u00b7 The Need for an Iterative Qualitative and Quantitative Analysis Strategy\n\n\n                                                                    analysis, O has been directly analyzed with the k-ratio/matrix\n  . .\u200a\u200a\u200aTable 20.5\u2003  Analysis of PbS at E0\u2009=\u200910 keV with CuS and PbSe                                                              corrections protocol and not by the method of assumed stoi-    as fitting references and standards; Integrated spectrum count,\n    0.1\u201310 keV\u2009=\u20095,482,000; uncertainties expressed in mass fraction.     chiometry. The analytical results are seen to closely match the\n    Analysis performed with Pb M5-N6,7 and S K-L2,3                  stoichiometry of the ideal mineral formula.\n\n                                  S           Pb\n                                                         20.3.5  Ba-Ti Interference: Major/Minor    Cav (atom frac)                       0.4938        0.5062                                                  Constituent Interference in K2496\n    Z-correction                          1.31          0.983            Microanalysis Glass\n    A-correction                         1.028         1.05\n\n## 4. goldstein2018quantitativeanalysisthe pages 6-8 (Context ID: pqac-00000009)\n\nin the center of the Faraday cup aperture\n                                                        opening, the primary beam electrons as well as all BSEs\nwhere A is the active area of the detector and r is the distance  and SEs generated at the inner surfaces are collected with\nfrom the X-ray source on the specimen to the detector. Some   very little loss through the small aperture, so that the cur-\nEDS  systems  are mounted on  a  retractable arm  that   rent flowing to the electrical ground is the total incident\nenables the analyst to choose the value of r. A consistent and  beam current.           314    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n          20.2.4  Choosing the Beam Current            SDD-EDS, a more conservative counting strategy is sug-\n                                                                          gested, such that the beam current is chosen so that the\n           After the analyst has chosen the EDS time constant, the   dead-\u00adtime on the most highly excited standard of interest,\n           detector solid angle (for a retractable detector), and the beam   for example, Al or Si, is less than 10\u2009%. Despite the opera-\n           energy, the beam current should be chosen so as to give a   tion of the anti-coincidence function, SDD-EDS systems\n          reasonable detector throughput, as expressed by the system   typically show evidence of coincidence peaks above a dead-\n          dead-time. .\u2003 Figure 20.2 shows the relationship between the  time of 10\u2009% from highly excited parent peaks, as illustrated\n          input count rate (ICR) of X-rays that arrive at the detector   in .\u2003 Fig. 20.3, which shows the in-growth of an extensive\n         and the output count rate (OCR) of photons that are actually   set of coincidence peaks from several parent peaks. If it is\n           stored in the measured spectrum. The OCR initially rises lin-  important to measure low intensity X-ray peaks that cor-\n           early with the ICR, but as photons arrive at a progressively  respond to minor or trace constituents that occur in spec-\n           greater rate at the detector, photon coincidence begins to   tral regions affected by coincidence peaks, then choosing\n          occur and the anti-coincidence function begins to reject   the low dead-\u00adtime to minimize coincidence will be an\n           these coincidence events, reducing the OCR. Eventually a  important issue in selecting the general analytical condi-\n       maximum OCR value is reached beyond which the OCR   tions. If there is no interest in measuring X-ray peaks of\n          decreases with increasing ICR, eventually falling to zero   possible constituents that occur in the region of coinci-\n           (\u201cparalyzable dead-time\u201d). A useful measure of the activity  dence peaks, then these regions can be ignored and a\n            state of the EDS detector is the system \u201cdead-time\u201d which is  counting strategy that involves higher dead-time operation\n          defined as                                             can be used.\n                                                          Once the analytical conditions (EDS time constant, solid\n                                               100    (20.2)   angle, beam energy, and beam current appropriate to the                Dead-time ( % ) = \uf8ee\uf8f0 (                           ICR \u2212 OCR ) / ICR \uf8f9\uf8fb\u2217\n                                                                 complete suite of standards) have been chosen, these condi-\n      A classic strategy with the low throughput Si(Li)-EDS is to   tions should be used for all standards and unknowns to\n           select a beam current on a highly excited pure element such   achieve the basic measurement consistency required for the\n           as Al or Si that produces a dead-time of 30\u2009% or less. With   k-ratio/matrix corrections protocol.\n\n\n\n      . .\u200a\u200a\u200aFig. 20.2\u2003  Output count rate\n           (OCR) vs. input count rate for an\n          SDD-EDS array of four 10-mm2                                  30 mm2 SDD at medium throughtput\n            detectors\n                                                  200,000\n                                                                                                                        Ideal response\n                                                                                                         (no deadtime)\n\n                                                  160,000\n                                                                                                                                                                                                    (counts/s)\n                                                  120,000\n                                                                              Rate\n                                                                                                  Count\n                                                    80,000\n                                                                                                                      Output\n\n                                                    40,000\n20\n\n                                                   0\n                                                     0          40,000        80,000       120,000       160,000      200,000\n                                                                                     Input Count Rate (counts/s)                                                                                                               315                                      20\n20.2 \u00b7 Instrumentation Requirements\n\n\n\n\n   a\n     3 500 000                                                                                                    K412_20kV5nAMED5eV40kHz3DT_5ks\n\n     3 000 000                                  SRM470 Glass K412\n                                                           E0 = 20 keV\n                                                  Deadtime = 3%\n     2 500 000\n\n\n     2 000 000       Counts\n     1 500 000\n\n\n     1 000 000\n\n     5 000 000\n\n\n            0\n                0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                       Photon energy (keV)\n\n  b\n                                                                                                                     K412_20kV5nAMED5eV40kHz3DT_5ks\n\n      100 000\n\n\n       80 000\n\n\n       60 000       Counts\n\n\n       40 000\n\n\n       20 000\n\n\n            0\n               0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                       Photon energy (keV)\n\n   c                                                                                                                       K412_20kV5nA40kHz_3DT\n                                                                                      Al+Al                                                                        K412_20kV50nA387kHz_29DT\n\n                                                                         SRM470 Glass K412                                                      Si+O                Si+Mg;      Si+Si                                           E0 = 20 keV\n                                                                                Deadtime = 3%\n                                                                                Deadtime = 29%         Counts\n                                                                                                                                     Mg+Ca      Si+Ca\n\n\n\n\n\n       0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0         10.0\n                                                      Photon energy (keV)\n\n\n. .\u200a\u200a\u200aFig. 20.3\u2003 SDD-EDS spectra of NIST SRM (glass K412, E0\u2009=\u200920 keV: a, b at 3\u2009% dead-time (red); c 3\u2009% (red) and 29\u2009% dead-time (blue), showing\nin-growth of coincidence peaks           316    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n         20.3 Examples of the k-ratio/Matrix              the error budget. In this analysis and the analyses reported\n             Correction Protocol with DTSA II            below, the relative deviation from the expected value (RDEV)\n           (Newbury and Ritchie 2015b)                    (also referred to as \u201crelative error\u201d) is calculated with the\n                                                                       \u201cexpected\u201d value taken as the stoichiometric formula value or\n          20.3.1  Analysis of Major Constituents            the value obtained from an \u201cabsolute\u201d analytical method, just\n                 (C\u2009>\u20090.1 Mass Fraction\n\n## 5. goldstein2018quantitativeanalysisthe pages 1-4 (Context ID: pqac-00000010)\n\n                                                                               309                              20\n\nQuantitative Analysis:\nThe SEM/EDS Elemental\nMicroanalysis k-ratio Procedure\nfor Bulk Specimens,\nStep-by-Step\n\n\n20.1   Requirements Imposed on the Specimen\n      and Standards \u2013 311\n\n20.2   Instrumentation Requirements \u2013 311\n20.2.1   Choosing the EDS Parameters \u2013 311\n20.2.2   Choosing the Beam Energy, E0 \u2013 313\n20.2.3   Measuring the Beam Current \u2013 313\n20.2.4   Choosing the Beam Current \u2013 314\n\n20.3   Examples of the k-ratio/Matrix Correction\n        Protocol with DTSA II \u2013 316\n20.3.1   Analysis of Major Constituents (C\u2009>\u20090.1 Mass Fraction)\n        with Well-\u00adResolved Peaks \u2013 316\n20.3.2   Analysis of Major Constituents (C\u2009>\u20090.1 Mass Fraction)\n        with Severely Overlapping Peaks \u2013 318\n20.3.3   Analysis of a Minor Constituent with Peak Overlap\n       From a Major Constituent \u2013 319\n20.3.4   Ba-Ti Interference in BaTiSi3O9 \u2013 319\n20.3.5   Ba-Ti Interference: Major/Minor Constituent Interference\n          in K2496 Microanalysis Glass \u2013 319\n\n20.4   The Need for an Iterative Qualitative and\n        Quantitative Analysis Strategy \u2013 319\n20.4.1   Analysis of a Complex Metal Alloy, IN100 \u2013 320\n20.4.2   Analysis of a Stainless Steel \u2013 323\n20.4.3   Progressive Discovery: Repeated Qualitative\u2013Quantitative Analysis\n        Sequences \u2013 324\n\n20.5     Is the Specimen Homogeneous? \u2013 326\n\n\n\n\n\n\u00a9 Springer Science+Business Media LLC 2018\nJ. Goldstein et al., Scanning Electron Microscopy and X-Ray Microanalysis,\nhttps://doi.org/10.1007/978-1-4939-6676-9_2020.6   Beam-Sensitive Specimens \u2013 331\n20.6.1   Alkali Element Migration \u2013 331\n20.6.2   Materials Subject to Mass Loss During Electron\n       Bombardment\u2014the Marshall-Hall Method \u2013 334\n\n       References \u2013 339                                                                                                                 311                                      20\n20.2 \u00b7 Instrumentation Requirements\n\n\nThis chapter discusses the procedure used to perform a rig-      grinding and polishing. \u201cChemical polishing\u201d should\norous quantitative elemental microanalysis by SEM/EDS     be avoided since chemical reactions may induce shal-\nfollowing the k-ratio/matrix correction protocol using the      low, near-surface compositional changes that affect\nNIST DTSA-II software engine for bulk specimens. Bulk      the very shallow region that is excited and sampled\nspecimens have dimensions that are sufficiently large to     by the electron beam. Ion beam milling can be used\ncontain the full range of the direct electron-excited X-ray      to shape and finish the specimen, but it must be\nproduction (typically 0.5\u201310 \u03bcm) as well as the range of      recognized that implantation of the primary ion and\nsecondary X-ray fluorescence induced by the propagation       differential material removal caused by differences in\nof  the  characteristic and continuum X-rays  (typically      the sputtering rates of the elements can modify the\n10\u2013100 \u03bcm).                                             composition of a shallow surface layer.\n\n20.1  Requirements Imposed                     20.2  Instrumentation Requirements\n    on the Specimen and Standards\n                                                   The basis of the k-ratio/matrix corrections protocol is mea-\nThe k-ratio/matrix correction protocol for the analysis of  surement of the X-ray spectra of the specimen and standard\nbulk specimens has two basic underlying assumptions:        (s) under identical conditions of beam energy, known elec-\n1. The composition is homogeneous throughout the entire   tron dose (the product of beam current and EDS live-time,\n   volume of the specimen in which primary characteristic   with  accurate  dead-time  correction), EDS  parameters\n   X-rays are directly excited by the incident electron beam   (detector solid angle, time constant, calibration, and window\n   and in which secondary X-ray fluorescence is induced      efficiency), target orientation (tilt angle, ideally 0\u00b0 tilt, i.e.,\n   during the propagation of the primary characteristic    beam perpendicular to the target surface), and EDS take-off\n   and continuum X-rays. A compositionally heteroge-     angle (i.e., the detector elevation angle above the flat sample\n   neous specimen which does not satisfy this requirement   surface).\n   cannot be analyzed by the conventional k-ratio/matrix\n   correction protocol. Examples of such heterogeneous\n   specimens include a horizontally layered specimen such   20.2.1  Choosing the EDS Parameters\n    as a thin film on a substrate or an inclusion with dimen-\n   sions similar to the interaction volume embedded in a     Consistency in the choice of the EDS parameters is critical\n   matrix. Such specimens must be analyzed with protocols   for establishing a robust analytical measurement environ-\n    that account for the effects of the particular specimen     ment, and this is especially important when archived stan-\n   geometry.                                           dard spectra are used.\n2. The X-ray intensities measured on the location of\n                                     EDS Spectrum Channel Energy Width    interest on the specimen and on the standard(s) differ\n   only because the compositions are different. No other  and Spectrum Energy Span\n    factors modify the measured intensities. In particular,   As shown in .\u2003 Fig. 20.1, when the energy axis is expanded\n   geometric effects that arise from physical surface         sufficiently, the EDS spectrum is seen to be a histogram of\n    defects, such as scratches, pits, and so on, can modify   energy channels of a specific width (e.g., 5 eV, 10 eV,\n   the interaction of the electron beam (electron back-     20 eV) and number (e.g., 1024, 2048, 4096). For accurate\n    scattering, beam penetration) with the specimen and     peak-\u00adfitting purposes, it is desirable to have an adequate\n   can alter the subsequent X-ray absorption path length  number of channels spanning the characteristic X-ray\n   to the detector compared to an ideal flat bulk speci-     peaks. Because the EDS resolution is a function of photon\n   men. This requirement places strict conditions on the   energy, low photon energy peaks below 1 keV are substan-\n   surface condition of the specimen and standards. A       tially narrower than higher energy peaks. A choice of 5 eV\n   highly polished, flat surface must be created following   for the channel energy width will provide a sufficient num-\n   the appropriate metallographic preparation proto-      ber of channels to adequately span all of the peaks of ana-\n   col for each particular material. The surface should       lytical  interest, including the peaks that occur below\n   be finished to a surface roughness below 100 nm       1 keV. C K-L2,3 is broadened in EDS to approximately\n   root mean square (rms) with a typical final polish      50 eV full width at half-maximum (FWHM), so a choice of\n   performed with 100-nm diamond, alumina, ceria       5-eV/channel will provide at least 10 channels to span the\n   or other polishing compound as appropriate. When     low photon energy peaks, which is important for accurate\n   the analysis involves measuring low energy photons     peak fitting. It is also desirable for the measured spectrum\n   below 1 keV (e.g., for the elements Be, B, C, N, O,        to span the full range of the excited X-ray energy, from an\n   and F), the surface finish should be better than 50 nm    effective threshold of approximately 100 eV to the Duane\u2013\n   rms. The preparation protocol should utilize physical   Hunt  limit, which corresponds to the incident beam           312    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n\n\n                100 000\n                                                                                                                                         Mn_20kv10nA110kHz10DT\n\n\n                 80 000\n                                    Mn\n                                                         E0 = 20 keV\n\n                 60 000\n                                   Counts\n                 40 000\n\n\n\n                 20 000\n\n\n\n                     0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                 Photon energy (keV)\n\n                100 000\n                                                                                                                                         Mn_20kv10nA110kHz10DT\n\n\n                 80 000\n\n                                                                                            5 eV bin width\n                 60 000\n                                   Counts\n                                                                  FWHM = 126 eV       \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010]\n\nStatus: Paper Count=21 | Relevant Papers=2 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=11 | Current Cost=$0.0763 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000011\n\nFrom text 'goldstein2018energydispersivexray pages 9-10'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\nThe excerpt describes EDS dead-time characteristics. X-rays arrive randomly, but the EDS system can only measure one photon at a time, becoming unavailable during measurement. The dead-time percentage is calculated as (ICR - OCR)/ICR \u00d7 100%, where ICR is input count rate and OCR is output count rate, shown graphically in Fig. 16.9. The anti-coincidence function excludes photons arriving during busy periods, though if the first photon measurement isn't sufficiently advanced, both photons may be excluded and lost. An automatic dead-time correction adds additional measurement time to maintain constant \"live-time\" for quantitative measurements. Dead-time increases with beam current, and the correction circuit can compensate across the full dead-time range to 80% or higher.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011]\n\nStatus: Paper Count=21 | Relevant Papers=2 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=12 | Current Cost=$0.1104 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000012\n\nFrom text 'blaj2017optimalpulseprocessing pages 2-2'.\n\nG. Blaj, C. J. Kenney, A. Dragone, G. Carini, S. Herrmann, P. Hart, A. Tomada, J. Koglin, G. Haller, S. Boutet, M. Messerschmidt, G. Williams, M. Chollet, G. Dakovski, S. Nelson, J. Pines, S. Song, and J. Thayer. Optimal pulse processing, pile-up decomposition, and applications of silicon drift detectors at lcls. IEEE Transactions on Nuclear Science, 64:2854-2868, Jun 2017. URL: https://doi.org/10.48550/arxiv.1706.01211, doi:10.48550/arxiv.1706.01211. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses the trade-off between pulse shaping time and detector performance in silicon drift detectors (SDDs). Longer pulse shaping and decay times increase pile-up probability, while shorter peaking times increase noise hyperbolically. The document indicates that without pulse shaping, rise time variations become significant and must be accounted for in fitting procedures to maintain optimal energy resolution. The authors demonstrate an approach eliminating pulse shaping altogether, where signal amplitude is obtained through fitting with the pulse function while accounting for variable rise times, achieving approximately 730 ns pulse separation without requiring pulse rejection.\n\n\n---\n\n## pqac-00000013\n\nFrom text 'blaj2017optimalpulseprocessing pages 13-14'.\n\nG. Blaj, C. J. Kenney, A. Dragone, G. Carini, S. Herrmann, P. Hart, A. Tomada, J. Koglin, G. Haller, S. Boutet, M. Messerschmidt, G. Williams, M. Chollet, G. Dakovski, S. Nelson, J. Pines, S. Song, and J. Thayer. Optimal pulse processing, pile-up decomposition, and applications of silicon drift detectors at lcls. IEEE Transactions on Nuclear Science, 64:2854-2868, Jun 2017. URL: https://doi.org/10.48550/arxiv.1706.01211, doi:10.48550/arxiv.1706.01211. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses the tradeoff between pulse processing parameters and detector performance. It describes a fundamental compromise in typical pulse processing between counting rate (achieved with short rise times) and energy resolution (requiring long rise times through pulse shaping), necessitating selection of an appropriate peaking time. However, the authors present an alternative approach using pulse waveform fitting with pulse functions rather than traditional pulse shaping. This fitting method eliminates the need for pulse shaping while achieving fast pulse onset, improved pulse separation, and the ability to handle multiple overlapping pulses. The method extracts precise amplitude and timing information by fitting each pulse waveform to a combined gradual step function and exponential decay model.\n\n\n---\n\n## pqac-00000014\n\nFrom text 'goldstein2018energydispersivexray pages 25-26'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\nThe excerpt discusses the fundamental trade-off in EDS detectors between pulse process time, energy resolution, and throughput. Longer pulse process times achieve better energy resolution but produce poor ultimate throughput. Conversely, shorter pulse process times maximize throughput but introduce coincidence events (pulse pile-up) that limit quantitative accuracy. The document indicates that optimal detector performance involves a three-way trade-off between throughput, resolution, and coincidence rate. Practically, operators define an acceptable coincidence rate and select a process time that maximizes throughput while maintaining that rate, typically sacrificing only a few eV of resolution quality. This resolution compromise is deemed acceptable since accurate quantitative analysis prioritizes throughput over optimal resolution. However, the excerpt does not specifically address the electronic noise and series noise components or their detailed relationship to determining optimal shaping time.\n\n\n---\n\n## pqac-00000015\n\nFrom text 'goldstein2018energydispersivexray pages 14-15'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\nThe excerpt explains the inverse relationship between pulse process time and detector performance in SDD-EDS systems. Longer process times produce better spectral resolution but lower X-ray throughput, while shorter process times increase throughput at the expense of resolution. The text emphasizes that resolution degrades slowly relative to throughput gains when reducing process time. Moderate process time settings typically degrade resolution by only a few percent while substantially increasing throughput. Modern SDDs achieving 122-128 eV resolution can be compromised to 130-150 eV while maintaining excellent quantitative analysis, since precision depends more on the number of measured X-rays than spectral resolution alone. The excerpt does not discuss the electronic noise or series noise components that determine optimal shaping time.\n\n\n---\n\n## pqac-00000016\n\nFrom text 'newbury2011isscanningelectron pages 2-3'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\nThe excerpt demonstrates the inverse relationship between pulse processing time constant (shaping time) and detector performance metrics in SDD-EDS systems. Shorter time constants enable higher throughput (OCR) but with a resolution trade-off. For example, a 500 ns time constant achieves resolution below 130 eV (MnK\u03b1), while reducing the time constant to 220 ns increases maximum OCR to 270 kHz but degrades resolution to 145 eV. The text illustrates that SDD-EDS detectors significantly outperform Si(Li)-EDS in throughput capability (by a factor of at least 60 for similar resolution), and this improved count rate performance enables collection of statistically robust spectra within practical measurement intervals. However, the excerpt does not explicitly discuss the underlying noise mechanisms (electronic noise vs. series noise) or the theoretical optimization process for determining optimal shaping time based on noise trade-offs.\n\n\n---\n\n## pqac-00000017\n\nFrom text 'blaj2017optimalpulseprocessing pages 1-2'.\n\nG. Blaj, C. J. Kenney, A. Dragone, G. Carini, S. Herrmann, P. Hart, A. Tomada, J. Koglin, G. Haller, S. Boutet, M. Messerschmidt, G. Williams, M. Chollet, G. Dakovski, S. Nelson, J. Pines, S. Song, and J. Thayer. Optimal pulse processing, pile-up decomposition, and applications of silicon drift detectors at lcls. IEEE Transactions on Nuclear Science, 64:2854-2868, Jun 2017. URL: https://doi.org/10.48550/arxiv.1706.01211, doi:10.48550/arxiv.1706.01211. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses silicon drift detectors (SDDs) at free-electron lasers and presents an alternative to traditional pulse shaping approaches. Rather than using conventional pulse shaping, the authors demonstrate that waveform fitting with signal amplitude and rise time parameters can achieve simultaneously high energy resolution and high counting rates (2 orders of magnitude higher than conventional digital pulse processors). By avoiding pulse shaping entirely, they achieved rise times of tens of nanoseconds, which resulted in reduced pulse pile-up. This approach allows decomposition of remaining pile-up at photon separation times down to hundreds of nanoseconds while maintaining 10 nanosecond time-of-arrival precision. However, the excerpt does not explicitly address the trade-off between electronic noise and series noise in determining optimal shaping time, nor does it provide detailed quantitative analysis of the relationship between shaping time and the energy resolution versus throughput trade-off.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017]\n\nStatus: Paper Count=21 | Relevant Papers=4 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=18 | Current Cost=$0.1511 | Disease-Target Evidence=0",
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+                  "end_ts": 2782.600824802
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Good. Now let me read the Currie paper and gather evidence on detection limits, and search for the SDD noise trade-off:",
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+                    "id": "toolu_01R4XA96akT6vHtcV3eGPRMj",
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+                    "id": "toolu_01FNAV5kmdFvTHg1GUnqvKRN",
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+                      "arguments": "{\"query\": \"SDD silicon drift detector noise components parallel series 1/f ballistic deficit shaping time energy resolution optimization\"}",
+                      "name": "paper_search"
+                    }
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+                "role": "tool",
+                "content": "## 1. currie1999detectionandquantification pages 4-6 (Context ID: pqac-00000018)\n\n Poisson counting processes; and  (b)\nof the estimator ^L: under the null hypothesis, at the      (standard deviation) increasing in a linear fashion.\ndetection limit, and at the quanti\u00aecation limit, respec-      Detailed treatment of this issue is beyond the scope\ntively; s20 represents an estimate of   20, based on v      of this document, but further information may be\ndegrees of freedom; z and t represent the appropriate     found in [2]. To illustrate, given normality, negligible\none-sided critical values of the standard normal variate      uncertainty in the mean value of the blank (such that\nand Students-t, respectively; and  represents the non-    0!  B), and   \u0085^S\u0086 increasing with a constant slope\ncentrality parameter of the non-central t distribution.      (d /dS) of 0.04 \u00b1 equivalent to an asymptotic relative\nThe actual value for  (0.05, 0.05, 4) appearing above      standard deviation (RSD) of 4%, we \u00aend the follow-\n(Eq. (5b)) is 4.07.                                           ing:\n  The above relations represent the simplest possible\n                                               LC \u0088 1:645 B;                                     (7)\ncase, based on restrictive assumptions; they should in\nno way be taken, however, as the de\u00aening relations for     LD \u0088 LC \u0087 1:645 D;   with  D \u0088  B \u0087 0:04LD;\ndetection and quanti\u00aecation capabilities. Some inter-                                                           (8)\nesting  complications  arise when  the  simplifying\n                                             LQ \u0088 10 Q;   with  Q \u0088  B \u0087 0:04LQ:           (9)\nassumptions do not apply. These will be discussed\nbelow. It should be noted, in the second expressions        Solutions to Eqs. (8) and (9) are LD\u00883.52  B, and\nfor LC and LD given above, that although s0 may be     LQ\u008816.67  B, respectively. Thus, with a linear relation\nused for a rigorous detection test,   0 is required to      for   \u0085^S\u0086, with intercept  B and a 4% asymptotic RSD,\ncalculate the detection limit. If s0 is used for this      the ratio of the quanti\u00aecation limit to the detection\npurpose, the calculated detection limit must be viewed      limit is increased from 3.04 to 4.73.\nas an estimate with an uncertainty derived from that of          If   increases too sharply, LD and/or LQ may not be\n  /s. Finally, for chemical measurements at least, the      attainable for the CMP in question. This problem may\nfundamental contributing factor to  0, and hence to the     be attacked through replication, given   reduction by                              pdetection and quanti\u00aecation performance characteris-     1=     \u0081\u0081n , but caution should be exercised since unsus-\ntics is the variability of the blank. This, together with     pected systematic error will not be correspondingly\nthe in\u00afuence of heteroscedasticity, is introduced for-     reduced!\nmally in Section 2.2.2.\n   Finally, there is the link to the ``outside world''.      2.2.3. The Zero myth\nDetection or quanti\u00aecation capabilities are generally        In many cases the lay public believes, given suf\u00ae-\nof interest because of an external driving force LR,      cient effort or funding, that a concentration of zero\nwhich we take as an external value that the CMP must    may be detected and/or achieved. Not unlike the third\nbe able to detect (or quantify). To illustrate such a     law of thermodynamics, however, neither is possible,\nrelationship, as well as most of the foregoing princi-     even in concept. A policy of reporting ``zero'' when                                        L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134                              131\n\n^L < LC, yielding the decision ``not detected'', com-      different results being obtained for each realization of\npounds this lack of understanding. These are issues of      the calibration curve, even though the underlying\nmajor national importance, especially in the context of     measurement process is \u00aexed. IUPAC [9] suggests\nlegislation and  regulation, where  necessarily, and      dealing with this problem by considering the median\nappropriately, many of the policy makers have critical      of the distribution of such ``detection limits''. (The\nsociopolitical expertise, but not necessarily scienti\u00aec     expected value is in\u00aenity.) An alternative, suggested in\nor technical expertise. The solution to this sociotech-      [9] and developed in [3], treats the exact, non-normal\nnical dilemma is, once again, very careful commu-      distribution of ^x in developing concentration detection\nnication; and, beyond that, mutual understanding and       limits.\neducation among the complementary disciplines.\n  One possible (partial) solution to this dilemma is the\nsubstitution of a non-zero value L0 for characterizing      3. Trans-definitional issues\nthe null hypothesis. Eq. (1) would then take the form\n                                                                3.1. Specification of the measurement (and\nPr\u0085^L > LCjL \u0088 L0\u0086       :                        (10)                                                               evaluation) process\n  Further discussion of such a non-zero null is given\nin Chapter 1 of [2] in connection with discrimination        This is absolutely essential. Quoting from Section\nlimits (Section 3.3.1).                                      3.7.2 of IUPAC [9]: ``Just as with other performance\n                                                                characteristics, LD and LQ cannot be speci\u00aeed in the\n2.2.4. Signal and concentration domains                absence of a  fully de\u00aened measurement process,\n  Formulation of the generic, de\u00aening ``L'' expres-      including such matters as types and levels of inter-\nsions  for  signal and  concentration  detection and      ference as well as the data reduction algorithm. `Inter-\nquanti\u00aecation limits  is given in [9], and extended      ference  free  detection  limits'  and  `instrument\nin  [3]. Treatment of SC, SD, and SQ  is relatively      detection  limits', for example, are perfectly valid\nstraightforward; but some interesting problems arise      within their respective domains; but if detection or\nin making the transition to the concentration domain,      quanti\u00aecation characteristics are sought for a more\nparticularly when there is non-negligible uncertainty     complex chemical measurement process, involving,\nin the ``sensitivity'' A (slope of the calibration curve).      for example sampling, analyte separation and puri\u00ae-\nFor the simplest (single component, straight  line)      cation, and interference and matrix effects, then it is\ncalibration function the estimated concentration ^x is     mandatory that  all these factors be considered in\ngiven by                                                 deriving values for LD and LQ for that process. Other-\n                                                    wise the actual performance of the CMP (detection,^x \u0088 \u0085y \u00ff ^B\u0086=^A:                                 (11)\n                                                        quanti\u00aecation capabilities) may fall far short of the\n  Although this is the simplest case, it nonetheless      requisite performance''.\noffers challenges, for example, in the application of\nerror propagation for the estimation of the ^x distribu-      3.2. What is sigma?\ntion if ey is non-normal, and for the non-linear parts of\nthe transformation (denominator of Eq. (11)). In [3],       Beyond the conceptual framework for detection and\nwhich treats a normal response only, three cases for      quanti\u00aecation limits, there is probably no more dif\u00ae-\nerror in the estimated slope of the calibration curve are      cult or controversial issue than deciding just what to\nconsidered: (1) negligible (A known), (2) systematic     use for  0 or its estimate s0. Though often ignored, the\n(eA \u00aexed), and (3) random (eA  N(0, VA)). The last of      matter of heteroscedasticity must obviously be taken\nthese is commonly employed to obtain ``calibration''-      into account. But it is crucial also to take into account\nor ``regression''-based detection limits, using a tech-      the complete error budget of the speci\u00aeed measure-\nnique introduced by Hubaux and Vos [6]. This method,     ment process. If this is done successfully, and if all\nhowever, has a drawback in that it yields, ``detection     assumptions are satis\u00aeed, the apparent dichotomy\nlimits'' that are random variables, as acknowledged in     between the intralaboratory approach and the inter-\nthe original publication of the method ([6], p. 850);      laboratory approach to detection and quanti\u00aecation132                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n                                                          estimates for compound CMPs involving different\n                                                       samples, different instruments,  different operators,\n                                                          or even different met\n\n## 2. currie1999detectionandquantification pages 7-8 (Context ID: pqac-00000019)\n\nexamined with respect to contamination and\ninterference contributions, and the whole is then esti-     A graphical representation of these concepts  is\nmated as the sum of its parts \u00b1 with due attention to     given in Fig. 2, where the ``driving force'' in this\ndifferential recoveries and variance propagation. This      hypothetical example is the ability to detect the release\nis an important point: that the blank introduced at one      of speci\u00aec chemical precursors of earthquakes (e.g.,\nstage of the CMP will be attenuated by subsequent      radon)  at  levels corresponding  to earthquakes  of\npartial recoveries. Neither the internal nor the external     magnitude LR and above. Thus LR is the ``requisite\napproach to blank assessment is easy, but one or the       limit'' or maximum acceptable limit for undetected\nother is mandatory for accurate low-level measure-      earthquakes; this is driven, in turn, by a maximum\nments; and consistency (internal, external) is requisite      acceptable loss to society. (Derivation of LR values for\nfor quality. Both approaches require expert chemical      sociotechnical problems, of course, is far more com-\nknowledge concerning the CMP in question.             plex than the subject of this report!) The lower part of\n                                                           the \u00aegure shows the minimum detectable value for the\n                                                     chemical precursor LD, that must not exceed LR, and\n5. Some future challenges                                        its relation to the probability density functions (pdfs)\n                                                                  at L\u00880 and at L\u0088LD together with   and    , and the\n  The ``real world'' holds many complexities and      decision point (critical value) LC. The \u00aegure has been\nchallenges beyond the preceding, relatively straight-     purposely constructed to illustrate heteroscedasticity \u00b1\nforward univariate, linear, and monotonic perspective.\nVery real detection and quanti\u00aecation capability issues         4This example is adapted directly from Section 3.7.3. of [9].134                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n\n                                                                               [2] L.A.  Currie,  (Ed.),  Detection  in  Analytical  Chemistry:\n                                                                          Importance, Theory, and Practice, ACS Symposium Series,\n                                                                                     vol. 361, American Chemical  Society, Washington, DC,\n                                                                        1988.\n                                                                               [3] L.A. Currie, in: International Conference on Environmetrics\n                                                                   and Chemometrics, Las Vegas, NV, 1995, Detection: inter-\n                                                                                national update, and some emerging di-lemmas involving\n                                                                                     calibration,  the  blank, and  multiple  detection  decisions,\n                                                         Chemom. Intell. Lab. Syst. 37 (1977) 151\u00b1181.\n                                                                               [4] R.D. Gibbons, Some statistical and conceptual issues in the\n                                                                               detection  of  low-level environmental  pollutants, Environ.\n                                                                             Ecol. Statist. 2 (1995) 125\u00b1167; [Discussants: K. Cambell,\n                                                              W.A. Huber, C.E. White, H.D. Kahn, B.K. Sinha, W.P. Smith,\n                                                                   H. Lacayo, W.A. Telliard, C.B. Davis].\n                                                                               [5] W. Horwitz, IUPAC Commission on Analytical Nomencla-\n                                                                                         ture, Nomenclature for Sampling in Analytical Chemistry,\n                                                                      Pure Appl. Chem. 62 (1990) 1193.\n                                                                               [6] A. Hubaux, G. Vos, Decision and detection limits for linear\n                                                                                  calibration curves, Anal. Chem. 42 (1970) 849\u00b1855.\n                                                                               [7]  P. Wilrich, Chairman, ISO/DIS 11843-1,2 (1995), Capability\n                                                                           of  Detection, ISO/TC69/SC6, ISO  Standard,  11843-1,\n                                                                        1977.\n                                                                               [8] IUPAC, Orange book, in: H. Freiser, G.H. Nancollas (Eds.),\n                                                           Compendium of Analytical Nomenclature, 2nd ed., Black-\nFig. 2. Detection: needs and capabilities. Top portion shows the             well, Oxford; 1st ed., 1978.\nrequisite limit LR, bottom shows detection capability LD.                   [9] IUPAC, prepared by L.A. Currie, IUPAC Commission on\n                                                                             Analytical Nomenclature, Recommendations in Evaluation\n                                                                             of Analytical Methods including Detection and Quantification\nin this case, variance increasing with signal level, and             Capabilities, Pure Appl. Chem. 67 (1995) 1699\u00b11723.\nunequal   and    . The point of the latter construct is       [10] H. Kaiser, Die Berechnung der Nachweisempfindlichkeit,\nthat, although 0.05 is the recommended default value            Spectrochim. Acta 3 (1947) 40.\nfor these parameters, particular circumstances may       [11] H. Kaiser, Zum Problem der Nachweisgrenze, Z. Anal. Chim.\n                                                                209 (1965) 1.\ndictate more stringent control of the one or the other.                                                                        [12] G.L. Long, J.D. Winfordner, Limit of detection: a closer\nInstructive implicit issues in this example are that (1) a            look at the IUPAC definition, Anal. Chem. 55(7) (1983)\nmajor factor governing the detection capability could           713A.\nbe the natural variation of the radon background       [13]  J. Mandel, R.C.  Paule,  Interlaboratory  evaluation  of  a\n(blank variance) in the environment sampled, and             material with unequal numbers of replicates, Anal. Chem.\n                                                                42 (1970) 1194.\n(2) a calibration factor or function is needed in order                                                                        [14] M. Natrella, Experimental Statistics, NBS Handbook 91, US\nto couple the two abscissae in the diagram. In prin-          Government Printing Office, Washington, 1963.\nciple, the response of a sensing instrument could be       [15] IUPAC, J. Incze\u00c2dy, T. Lengyel, A.M. Ure, A. Gelencse\u00c2r, A.\ncalibrated directly to the Richter scale (earthquake            Hulanicki (Eds.) Compendium of Analytical Nomenclature,\nmagnitude); alternatively, there could be a two-stage            3rd ed., Blackwell, Oxford, 1998.\ncalibration: instrument response\u00b1radon concentration,\n                                                               Note added in proof\nand radon concentration\u00b1Richter scale.\n                                                                          Shortly after the submission of this article to Analytica Chimica\n                                                                 Acta a new edition of the IUPAC Compendium of Analytical\n                                                             Nomenclature was  published  [15].  In  the new  edition  the\nReferences                                                                           deficiencies in the [old] ``IUPAC Definition'' of the Detection\n                                                                        Limit, as discussed in Section 2.1.1, were remedied by incorpora-\n [1] L.A. Currie, Limits for qualitative detection and quantitative        tion of the new IUPAC Recommendations of 1995 [9].\n     determination, Anal. Chem. 40 (1968) 586.\n\n## 3. currie1999detectionandquantification pages 6-7 (Context ID: pqac-00000020)\n\ns done successfully, and if all\nhowever, has a drawback in that it yields, ``detection     assumptions are satis\u00aeed, the apparent dichotomy\nlimits'' that are random variables, as acknowledged in     between the intralaboratory approach and the inter-\nthe original publication of the method ([6], p. 850);      laboratory approach to detection and quanti\u00aecation132                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n                                                          estimates for compound CMPs involving different\n                                                       samples, different instruments,  different operators,\n                                                          or even different methods. In the context of (material)\n                                                       sampling, an excellent exposition of the nature and\n                                                     importance of the hierarchical  structure has been\n                                                        presented by Horwitz [5].\n                                              From the interlaboratory perspective, the \u00aerst popu-\n                                                               lation in Fig. 1 (e1) would represent the distribution of\n                                                              errors among  laboratories;  the second  [S] would\n                                                         re\u00afect  intralaboratory  variation  (``repeatability'');\n                                                  and the third [T], overall variation (``reproducibility'').\n                                                                        If the sample of collaborating laboratories can be\n                                                       taken as unbiased, representative, and homogeneous,\n          Fig. 1. Sampled [S] and target [T] populations.             then the interlaboratory ``process'' can be treated as a\n                                             compound CMP. In this fortunate (at best, asymptotic)\nlimits essentially vanishes.3 Some perspective on this      situation, results from individual laboratories are con-\nissue is given in Section 4.1 of [9] (quoted below), in      sidered random, independent variates from the com-\nterms of sampled and target populations.              pound CMP population. For parameter estimation\n  Sampled population [S] vs. target population [T].     (means, variances) in the interlaboratory environment\nThe above concept has been captured by Natrella [14]         it may be appropriate to use weights \u00b1 for example,\nwith reference to two populations which represent,    when member laboratories employ different numbers\nrespectively, the population (of potential measure-      of replicates [13].\nments) actually sampled, and that which would be\nsampled in the ideal, bias-free case. The correspond-\ning S and T populations are shown schematically in      4. Central role of the blank ([9], Section 3.8.8)\nFig. 1, for a two-step measurement process. When\nonly the S population is randomly sampled (left-hand      4.1. Blank (B)\nside of the \u00aegure), the error e1 from the \u00aerst step is\nsystematic while e2  is random. In  this  case, the       The blank is one of the most crucial quantities in\nestimated uncertainty is likely to be wrong, because      trace analysis, especially in the region of the detection\n(a) the apparent imprecision (  S) is too small, and (b)       limit. In fact, as shown above, the distribution and\nan unmeasured bias (e1) has been introduced. Realiza-      standard deviation of the blank are intrinsic to calcu-\ntion of the T-population (right-hand side of the \u00aegure)      lating the detection limit of any CMP. Standard devia-\nrequires that all steps of the CMP be random \u00b1 i.e., e1      tions are dif\u00aecult to estimate with any precision (ca. 50\nand e2 in the \u00aegure behave as random, independent      observations required for 10% RSD for the standard\nerrors; T thus represents a compound probability      deviation). Distributions (cdfs) are harder! It follows\ndistribution. If the contributing errors combine line-      that extreme care must be given to the minimization\narly and are themselves normal, then the T-distribution     and estimation of realistic blanks for the overall CMP,\nalso is normal. The concept of the S and T populations     and that an adequate number of full scale blanks must\nis absolutely central to all hierarchical measurement     be assayed, to generate some con\u00aedence in the nature\nprocesses (compound CMPs), whether intralaboratory      of the blank distribution and some precision in the\nor interlaboratory. Strict attention to the concept is      estimate of the blank RSD.\nessential  if one  is to obtain consistent uncertainty        Note: An imprecise estimate for the blank standard\n                                                          deviation is taken into account without dif\u00aeculty in\n                                                          detection decisions, through the use of Student's-t.\n  3In  practical  application,  the complexity  of  defining and\n                                                       Detection limits, however, are themselves renderedestimating   goes considerably deeper. For a recent informative\nand provocative discussion of this and related regulatory-detection      imprecise if  B is not well known (see [9], Section\nissues, the reader may consult [4].                                  3.7.3.2).                                        L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134                              133\n\n  Blanks or null effects may be described by three      in the environmental and physical sciences, for exam-\ndifferent  terms, depending upon  their  origin:  the      ples, include: (1) multiple univariate and multivariate\ninstrumental background  is the null signal (which      detection decisions and limits as found, for example,\nfor certain instruments may be set to zero, on the      in the analysis of multicomponent nuclear spectra; (2)\naverage) obtained in the absence of any analyte- or      multivariate environmental blanks, especially in the\ninterference-derived signal; the (spectrum or chroma-     measurement and source apportionment of multiiso-\ntogram) baseline comprises the summation of the      topic chemical species, such as atmospheric carbon\ninstrumental background plus signals in the analyte     monoxide; and (3) the appropriate treatment of detec-\n(peak) region of interest due to interfering species; the      tion and quanti\u00aecation limits for archaeological or\nchemical (or analyte) blank is that which arises from      geophysical artifacts or events that are governed by\ncontamination from the reagents, sampling procedure,      discrete, non-linear, and non-monotonic calibration\nor sample preparation steps, which corresponds to the      curves, as in the case of radiocarbon (14C) dating.\nvery analyte being sought.                      An introduction and references to some of these\n  Assessment of the blank (and its variability) may be     problems in the physical and environmental sciences\napproached by an ``external'' or ``internal'' route, in    may be found in [3].\nclose analogy to the assessment of random and sys-\ntematic error components [2]. The ``external'' approach\nconsists of the generation and direct evaluation of a     Acknowledgements\nseries of ideal or surrogate blanks for the overall\nmeasurement process, using samples that are identical       The author gratefully acknowledges the work of Dr.\nor closely similar to those being taken for analysis \u00b1     David E. Coleman of Alcoa Laboratories, who served\nbut containing none of the analyte of interest. The      as Voluntary Peer Reviewer for the original version of\nCMP and matrix and interfering species should be       this paper.\nunchanged. (The surrogate is simply the best available\napproximation to the ideal blank \u00b1 i.e., one having a\nsimilar matrix and similar levels of interferants.) The     Appendix A\n``internal'' approach has been described as ``propaga-\ntion of the blank''. This means that each step of the     Detection of earthquake precursors4\nCMP is examined with respect to contamination and\ninterference contributions, and the whole is then esti-     A graphical representation of these concepts  is\nmated as the sum of its parts \u00b1 with due attention to     given in Fig. 2, where the ``driving force'' in this\ndifferential recoveries and variance propagation. This      hypothetical example is the ability to detect the release\nis an important point: that the blank introduced at one      of speci\u00aec chemical precursors of earthquakes (e.g.,\nstage of the CMP will be attenuated by subsequent      radon)  at  levels corresponding  to earthquakes  of\npartial recoveries. Neither the internal nor the external     magnitude LR and above. Thus LR is the ``requisite\napproach to blank assessment is ea\n\n## 4. currie1999detectionandquantification pages 2-4 (Context ID: pqac-00000021)\n\nquestion. The \u00aerst, ``signal/noise'' school,\nexplicitly recognizes only the false positive (   , Type-1        1The regrettable confusion between the two types of ``detection\nerror), which in effect makes the probability of the        limits'' arose in part from an oversight in Kaiser's first publication\nfalse negative (  , Type-2 error) equal to 50%. The      on the topic [10] which ignored the idea of the false negative. False\nsecond, ``hypothesis testing'' school employs inde-       negatives nevertheless occur, and when ignored (equivalent to\n                                                                     equating LC and LD) their de facto probability becomes 50%, at\npendent values for   and    , commonly each equal to                                                                                 least for symmetric distributions. Kaiser corrected his error by\n0.05 or perhaps 0.01. In the most extreme case, the       inventing the term ``limit of guarantee for purity'' [11], but this\nsame numerical value of the ``detection  limit''  is       term has scarcely ever appeared in the literature.                                        L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134                              129\n\nformal requests by Codex2 in 1990 to each of the      curve; it is noted that A is not necessarily independent\norganizations for guidance on the terms ``limit of      of x, nor even a simple function of x. Subscripts C, D,\ndetection'' and ``limit of determination'', because of     and Q are used to denote the critical value, detection\nthe urgency of endorsing methods of analysis based on       limit, and quanti\u00aecation limit, respectively.\ntheir capabilities to reliably measure essential and       The de\u00aening  relations,  with  default  parameter\ntoxic elements in foods \u00b1 a problem that Codex had      values in parentheses, are given as follows:\nbeen attempting to resolve since 1982.                     Detection decision (critical value) (LC,  \u00880.05):\n                                                                  Pr\u0085^L > LCjL \u0088 0\u0086       :                            (1)2.2. Summary of the 1995 international\n    recommendations                                     Detection limit (minimum detectable value) (LD,\n                                                       \u00880.05):\n  Detection and quanti\u00aecation capabilities are con-\n                                                                  Pr\u0085^L   LCjL \u0088 LD\u0086 \u0088   :                           (2)sidered by IUPAC as fundamental performance char-\nacteristics  of  the  chemical measurement  process        Quanti\u00aecation limit (minimum quanti\u00aeable value)\n(CMP). As such, they require a fully de\u00aened, and      (LQ, RSDQ\u00880.10):\ncontrolled measurement process, taking into account\n                                             LQ \u0088 kQ Q;  where kQ \u0088 1=RSDQ:              (3)\nsuch matters as types and levels of interference, and\neven the data reduction algorithm. Perhaps the most       Note that LD, LQ, and  Q denote CMP  ``true''\nimportant purposes of these performance character-     parameter values. In practice they may be derived\nistics are for planning \u00b1  i.e., for the selection or     from estimates (or assumptions), such that calculated\ndevelopment of CMPs to meet a speci\u00aec scienti\u00aec      values will be characterized by uncertainties. Also, for\nor regulatory need. In the new IUPAC and ISO docu-    LD and   to be meaningful, LC (  ) must be employed\nments,   detection   limits  (minimum   detectable      for detection decision making. The relation,   vs. LD,\namounts) are derived from the theory of hypothesis       is known as the ``operating characteristic'' (OC) of the\ntesting and the probabilities of false positives    , and      (detection) signi\u00aecance test performed at signi\u00aecance\nfalse negatives    [7,9]. Quanti\u00aecation limits [9] are      level   ; (1\u00ff  ) is the ``power'' of the test. Eq. (1) is\nde\u00aened in terms of a speci\u00aeed value for the relative     given as an inequality, because not all values of   are\nstandard deviation (RSD). Default values for  and        possible for discrete distributions, such as the Poisson.\nare 0.05, each; and the default RSD for quanti\u00aecation     Note that the values of    ,    , and kQ given above are\nis taken as 10%.                              IUPAC recommended default values, which serve as a\n  As CMP performance characteristics, both detec-    common basis for measurement process assessment.\ntion and quanti\u00aecation  limits are associated with     They may be adjusted appropriately  in  particular\nunderlying true values of the quantity of interest; they      applications where detection or quanti\u00aecation needs\nare not associated with any particular outcome or      are more or less stringent.\nresult. The detection decision, on the other hand, is       Also addressed in the IUPAC document is the issue\nresult-speci\u00aec; it is made by comparing the experi-      of reporting. The recommendation is to always report\nmental result with the critical value, which  is the     both the estimated value of the measured quantity (^L)\nminimum signi\u00aecant estimated value of the quantity     and its uncertainty, even when ^L < LC results in the\nof interest. For presentation of the de\u00aening relations, L      decision ``not detected''. Otherwise, there is needless\nis used as the generic symbol for the quantity of      information loss, and of course, the impossibility of\ninterest. This  is replaced by S when treating net     averaging a series of results. The practice of quoting\nanalyte signals; and x, when treating analyte concen-     upper limits for ``non-detects'' can be helpful, but this\ntrations or amounts. The symbol A is used by IUPAC        still impairs future uses of the data. Quoting LD as an a\nto represent the sensitivity, or slope of the calibration      posteriori upper limit is not recommended, as this is\n                                                               really an a priori performance characteristic. Although\n                                                                                     it can be viewed as the ``maximum'' upper limit in the  2Codex Alimentarius Commission, Committee on Methods of\nAnalysis and Sampling, Food and Agricultural Organization, World      case of the null hypothesis, LD does not re\u00afect the new\nHealth Organization.                                        information contained in the experimental result.130                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n2.2.1. Simplified relations                                    ples, an hypothetical example from IUPAC [9] is given\n  Under the very special circumstances where the      in Appendix A.\ndistribution of ^L can be taken as normal, with constant\nstandard deviation  0 (homoscedastic) and the default      2.2.2. Heteroscedasticity\nparameter values, the foregoing de\u00aening relations       The following paragraphs, taken largely from Sec-\nyield the following expressions:                            tion 3.7.8 of [9], address the impact of heteroscedas-\n                                                                     ticity on the relative magnitudes of LC, LD, and LQ.LC \u0088 z1\u00ff   0 ! 1:645  0;                        (4a)\n                                                                           If the variance of the estimated quantity  is not\nLC \u0088 t1\u00ff ;vs0 ! 2:132s0   \u00894 df\u008a;               (4b)      constant, then its variation must be taken into account\n                                                             in computing detection and quanti\u00aecation limits. TheLD \u0088 LC \u0087 z1\u00ff  D ! 2LC \u0088 3:29  0;            (5a)\n                                                                    critical level is unaffected, since it re\u00afects the variance\nLD \u0088      ;  ;v  0   2t1\u00ff  ;v  0 ! 4:26  0   \u00894 df\u008a;    (5b)      of the null signal only. Two types of   variation are\n                                         common in chemical and physical metrology: (a)  2\nLQ \u0088 kQ Q ! 10  0;                               (6)\n                                                           (variance) proportionate to response, as with shot\nwhere   0,  D, and  Q represent the standard deviation      noise and Poisson counting processes; and  (b)\nof the estimator ^L: under the null hypothesis, at the      (standard deviation) increasing in a linear fashion.\ndetection limit, and at the quanti\u00aecation limit, respec-      Detailed treatment of this issue is beyond the scope\ntively; s20 represents an estimate of   20, based on v      of this document, but further information may be\ndegrees of freedom; z and t represent the appropriate     found in [2]. To illustrate, given normality, negligible\none-sided critical values of the standard normal variate      uncertainty in the mean value of the blank (such that\nand Students-t, respectively; and  represents the non-    0!  B), and   \u0085^S\u0086 increasing with a constant slope\ncentrality parameter of the non-ce\n\n## 5. currie1999detectionandquantification pages 1-2 (Context ID: pqac-00000022)\n\n                                        Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n\n\nDetection and quanti\u00aecation limits: origins and historical overview$\n\n                                 Lloyd A. Currie*\n\n                            National Institute of Standards and Technology, Gaithersburg, MD 20899, USA\n\n                                     Received 17 February 1998; accepted 18 February 1998\n\n\n\nAbstract\n\nDetection and quanti\u00aecation capabilities represent fundamental performance characteristics of measurement processes, yet\nthere have been decades of confusion and miscommunication regarding the underlying concepts and terminology. New,\ncoordinated documents prepared for the International Union of Pure and Applied Chemistry (IUPAC) [L.A. Currie, IUPAC\nCommission on Analytical Nomenclature, Recommendations in Evaluation of Analytical Methods including Detection and\nQuanti\u00aecation Capabilities, Pure Appl. Chem. 67 (1995) 1699\u00b11723] and the International Organization for Standardization\n(ISO) [P. Wilrich, Chairman, ISO/DIS 11843-1,2 (1995), Capability of Detection, ISO/TC69/SC6, ISO Standard, 11843-1,\n1977] promise  to  alleviate  this  situation by providing,  for the  \u00aerst time, a harmonized  position on standards and\nrecommendations for adoption by the international scienti\u00aec community. The text begins with (1) a brief historical summary\nof detection limits in chemistry, illustrating the critical need for the development of a sound and uniform system of terms and\nsymbols; and  (2) a review of the ISO\u00b1IUPAC deliberations and the ensuing harmonized position on concepts and\nnomenclature. In the following text a number of special topics are introduced, including: speci\u00aecation of the measurement\nprocess, attention to the meaning and evaluation of ``sigma'', special considerations for calibration (or regression)-based\ndetection and quanti\u00aecation limits, the central role of the blank, and \u00aenally, some challenges for the future. # 1999 Elsevier\nScience B.V. All rights reserved.\n\n\nKeywords: Detection; Quanti\u00aecation; International nomenclature; Metrology; IUPAC; ISO\n\n\n1. Introduction                                           nized. For some three decades, however, efforts to\n                                                     develop an internationally accepted system of nomen-\n  The importance of objective measures for detection      clature and scienti\u00aecally sound conceptual basis for\nand quanti\u00aecation capabilities of chemical and phy-     such capabilities have been impeded by the evolution\nsical measurement processes has long been recog-      of a wide range of terms, concepts, and ad hoc rules\n                                                                that are contradictory, and in some cases not even\n                                                              internally self-consistent. The need for a harmonized\n   *Tel.: +1-301-975-3919; fax: +1-301-216-1134; e-mail:            international position was recognized in 1993, when\ncurrie@nist.gov                                    members of IUPAC and ISO met, with the objective of\n  $Adapted from the Proceedings of the 1996 Joint Statistical                                                      developing such a position, based on documents then\nMeetings (American Statistical Association, 1997). Original title:\n                                                             in draft stage. These efforts culminated in 1995, with``Foundations and future of detection and quantification limits''.\nContribution of the National Institute of Standards and Technology;      the publication of IUPAC recommendations for the\nnot subject to copyright.                                         international chemical community [9], and the pre-\n\n\n0003-2670/99/$ \u00b1 see front matter # 1999 Elsevier Science B.V. All rights reserved.\nPII: S 0 0 0 3 - 2 6 7 0 ( 9 9 ) 0 0 1 0 5 - 1128                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\nparation of an ISO document for metrology in general     employed, e.g., 3.3  0, where  0 is the standard devia-\n[7]. While not identical, the documents are based on      tion of the estimated net signal (S\u00c3) when its true value\nthe same fundamental concepts, and compatible for-      (S) is zero. The ratio   /   for the \u00aerst (signal/noise)\nmulations and terminology. In the following text, we      group, assuming normality,  is thus 0.50/0.0005 or\npresent these concepts, together with their application     1000, far in excess of the unit ratio of the second\nto chemical metrology as developed in the IUPAC      group!1\ndocument. A brief review of the relevant history of the        Unfortunately, many are unaware of the above\ntopic, and discussions of critical approaches and open      subtle differences in concepts and terminology, or\nquestions in the application of the basic concepts      of the care and attention to assumptions required\nwhich follow are drawn, in part, from Currie [2,3].      for calculating meaningful detection limits; but these\nThe literature cited in the foregoing references pro-     become manifest when dif\u00aecult, low-level laboratory\nvides detailed information on the statistical and che-      intercomparisons are made. By way of illustration, in\nmical aspects of the topic.                                the International Atomic Energy Agency's interla-\n                                                        boratory comparison of arsenic in horse kidney (mg/\n                                                g level), several laboratories failed to detect the As, yet\n2. Communication and concepts                           their reported ``detection limits'' lay far below quan-\n                                                                     titative results reported by others; and the range of\n2.1. A very brief history                                 reported values spanned nearly \u00aeve orders of magni-\n                                                        tude ([2], Chapter 9).\n  Early papers on chemical detection limits were\npublished by Kaiser [10] and Currie [1]. In the latter,      2.1.1. Stimuli for the recent IUPAC and ISO efforts\nwhich  treated  the hypothesis  testing approach  to        Early guidance on detection limits, strongly in\u00afu-\ndetection decisions and limits in chemistry,  it was     enced by the work of Kaiser, was given by IUPAC.\nshown that the then current meanings attached to the      Resulting ``of\u00aecial'' recommendations appear in the\nexpression ``detection limit'' led to numerical values      early  editions  of  the Compendium  of  Analytical\nthat spanned three orders of magnitude, when applied     Nomenclature, where the ``limit of detection  . . . is\nto the same speci\u00aec measurement process. Differing      derived from the smallest measure that can be detected\nconcepts are but one side of the problem. A review of     with reasonable certainty for a given analytical pro-\nthe history of detection and quanti\u00aecation limits in      cedure''. This quantity is then related to a multiple k of\nchemistry published in 1988 [2] gives a partial com-      the standard deviation of the blank ``according to the\npilation of terms, all referring to the same, detection     con\u00aedence level desired'', with the general recom-\nlimit concept \u00b1 ranging from ``identi\u00aecation limit'' to     mendation of k\u00883. Hypothesis testing was not men-\n``limiting detectable concentration'' to ``limit of guar-      tioned, nor was the issue of false negatives, nor the\nantee for  purity'', for example. Perhaps the most      quanti\u00aecation limit [8,9]. De\u00aeciencies in the ``IUPAC\nserious terminological trap has been the use of the      de\u00aenition'' have been recognized by many  [12],\nexpression ``detection limit'' (a) by some to indicate     and are responsible, in  part, for the new IUPAC\nthe critical value (LC) of the estimated amount or       effort [9].\nconcentration above which the decision ``detected''     A second important factor in the new IUPAC effort\nis made; but (b) by others, to indicate the inherent      to develop a proper treatment of both detection and\n``true'' detection capability (LD) of the measurement      quanti\u00aecation limits, and a parallel effort by ISO, were\nprocess in question. The \u00aerst, ``signal/noise'' school,\nexplicitly recognizes only the false positive (   , Type-1        1The regrettable confusion between the two types of ``detection\nerror), which in effect makes the probability of the        limits'' arose in part from an oversight in Kaiser's first publication\nfalse negative (  , Type-2 error) equal to 50%. The      on the topic [10] which ignored the idea of the false negative. False\nsecond, ``hypothesis testing'' school employs inde-       negatives nevertheless occur, and when ignored (equivalent to\n                                                                     equating LC and LD) their de facto probability becomes 50%, at\npendent values for   and    , commonly each equal to             \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022]\n\nStatus: Paper Count=21 | Relevant Papers=5 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=23 | Current Cost=$0.1511 | Disease-Target Evidence=0",
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Expanding the detection efficiency of silicon drift detectors\nValid Text Names:\n'schlosser2010expandingthedetection pages 1-2', 'schlosser2010expandingthedetection pages 2-4', 'schlosser2010expandingthedetection pages 4-6', 'schlosser2010expandingthedetection pages 6-7', 'schlosser2010expandingthedetection pages 7-7'\n\nBibTex:\n@article{schlosser2010expandingthedetection,\n    author = \"Schlosser, D.M. and Lechner, P. and Lutz, G. and Niculae, A. and Soltau, H. and Str\u00fcder, L. and Eckhardt, R. and Hermenau, K. and Schaller, G. and Schopper, F. and Jaritschin, O. and Liebel, A. and Simsek, A. and Fiorini, C. and Longoni, A.\",\n    title = \"Expanding the detection efficiency of silicon drift detectors\",\n    year = \"2010\",\n    journal = \"Nuclear Instruments \\& Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment\",\n    volume = \"624\",\n    pages = \"270-276\",\n    month = \"Dec\",\n    doi = \"10.1016/j.nima.2010.04.038\",\n    url = \"https://doi.org/10.1016/j.nima.2010.04.038\",\n    publisher = \"Elsevier BV\",\n    issue = \"2\",\n    issn = \"0168-9002\"\n}\n\n\nRelevant Snippet:\n\u2026 Results of the energy resolution for the 137 Cs 662 keV line \u2026 The serial white and 1/f noise strongly depend on the total \u2026 In contrast the optimal shaping time of a SDD with minimal noise \u2026\n\n\n---\n\n## 2. Novel high-resolution silicon drift detectors\nValid Text Names:\n'lechner2004novelhighresolutionsilicon pages 1-2', 'lechner2004novelhighresolutionsilicon pages 2-4', 'lechner2004novelhighresolutionsilicon pages 4-5', 'lechner2004novelhighresolutionsilicon pages 5-6', 'lechner2004novelhighresolutionsilicon pages 6-6'\n\nBibTex:\n@article{lechner2004novelhighresolutionsilicon,\n    author = \"Lechner, P. and Pahlke, A. and Soltau, H.\",\n    title = \"Novel high-resolution silicon drift detectors\",\n    year = \"2004\",\n    journal = \"X-Ray Spectrometry\",\n    volume = \"33\",\n    pages = \"256-261\",\n    month = \"Jul\",\n    doi = \"10.1002/xrs.717\",\n    url = \"https://doi.org/10.1002/xrs.717\",\n    publisher = \"Wiley\",\n    issue = \"4\",\n    issn = \"0049-8246\"\n}\n\n\nRelevant Snippet:\n\u2026 electronics and detector gives an optimal signal-to-noise ratio\u2026 The noise contributions of an SDD are serial noise, 1/f noise \u2026 Silicon drift detectors benefit from their low shaping times of \u2026\n\n\nUnobtainable Papers:\nCarlo Fiorini, Luca Bombelli, Paolo Busca, Alessandro Marone, Roberta Peloso, Riccardo Quaglia, Pierluigi Bellutti, Maurizio. Boscardin, Francesco Ficorella, Gabriele Giacomini, Antonino Picciotto, Claudio Piemonte, Nicola Zorzi, Nick Nelms, and Brian Shortt. Silicon drift detectors for readout of scintillators in gamma-ray spectroscopy. IEEE Transactions on Nuclear Science, 60:2923-2933, Aug 2013. URL: https://doi.org/10.1109/tns.2013.2273418, doi:10.1109/tns.2013.2273418.\nArslan Dawood Butt, Riccardo Quaglia, Carlo Fiorini, Paolo Busca, Michele Occhipinti, Gabriele Giacomini, Claudio Piemonte, Franco Camera, Nick Nelms, and Brian Shortt. Development of a detector for gamma-ray spectroscopy based on silicon drift detector arrays and 2$^\\prime ^\\prime $ lanthanum bromide scintillator. IEEE Transactions on Nuclear Science, 62:2334-2342, Sep 2015. URL: https://doi.org/10.1109/tns.2015.2464676, doi:10.1109/tns.2015.2464676.\nB. Beckhoff, B. Kanngie\u00dfer, N. Langhoff, R. Wedell, and H. Wolff. Handbook of practical x-ray fluorescence analysis. ArXiv, Jan 2006. URL: https://doi.org/10.1007/978-3-540-36722-2, doi:10.1007/978-3-540-36722-2.\nCarlo Fiorini. Gamma detectors for spectroscopy and imaging based on scintillators coupled to semiconductor detectors. SPIE Proceedings, Nov 2000. URL: https://doi.org/10.1117/12.407570, doi:10.1117/12.407570.\nGriseld Deda, Idham Hafizh, Giacomo Borghi, Marco Carminati, Francesco Ficorella, Giancarlo Pepponi, and Carlo Fiorini. Scarlet: a readout asic bump-bonded to sdd array for large event throughput. IEEE Transactions on Nuclear Science, 71:2323-2333, Oct 2024. URL: https://doi.org/10.1109/tns.2024.3455424, doi:10.1109/tns.2024.3455424.\nK. Hansen and C. Reckleben. Noise analysis of an si-drift detector system with time-variant shaping. IEEE Transactions on Nuclear Science, 51:3845-3852, Dec 2004. URL: https://doi.org/10.1109/tns.2004.839369, doi:10.1109/tns.2004.839369.\nAndrei Stratilatov. Semiconductor detectors for portable energy\u2010dispersive xrf spectrometry. ArXiv, pages 475-500, May 2021. URL: https://doi.org/10.1002/9781119636489.ch19, doi:10.1002/9781119636489.ch19.\nC. Fiorini, A. Gola, A. Longoni, F. Perotti, and L. Struder. Timing properties of silicon drift detectors for scintillation detection. 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515), 2:701-703Vol.2, Jan 2004. URL: https://doi.org/10.1109/tns.2004.829581, doi:10.1109/tns.2004.829581.\nS. G. Basiladze. Application specific integrated circuits for ionizing-radiation detectors (review, part 1). Instruments and Experimental Techniques, 59:1-52, Jan 2016. URL: https://doi.org/10.1134/s0020441216010280, doi:10.1134/s0020441216010280.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022]\n\nStatus: Paper Count=23 | Relevant Papers=5 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=23 | Current Cost=$0.1511 | Disease-Target Evidence=0",
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+              {
+                "role": "assistant",
+                "content": "Now let me read the SDD noise papers and gather more evidence:",
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+                "tool_calls": [
+                  {
+                    "id": "toolu_01JgMwiEyS2LBkST6gDp7jDu",
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+                      "arguments": "{\"text_name_list\": [\"lechner2004novelhighresolutionsilicon pages 2-4\", \"lechner2004novelhighresolutionsilicon pages 4-5\", \"schlosser2010expandingthedetection pages 2-4\", \"niculae2006optimizedreadoutmethods pages 2-3\", \"niculae2006optimizedreadoutmethods pages 3-6\"]}",
+                      "name": "read_text"
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+                    "id": "toolu_0152q4CBfotfRn8Y2ahbVoHS",
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+                      "arguments": "{\"question\": \"Newbury Ritchie low-voltage SEM EDS trace element detection limits sensitivity, how do acquisition parameters change at low beam energy, overvoltage effects at 5 keV, counting strategy for trace elements\"}",
+                      "name": "gather_evidence"
+                    }
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+              },
+              {
+                "role": "tool",
+                "content": "## 1. niculae2006optimizedreadoutmethods pages 2-3 (Context ID: pqac-00000023)\n\n                                                                         (1)  The most frequently used method to operate the SDD     vs\u00f0s\u00de \u00bc\n                                                    Cd 1 \u00fe gds \u00f01 \u00fe Cgs 1 \u00fe s  tf 1 1 \u00fe s  trwith on-chip FET is the source\u2013follower readout [5] with                       gm      Cd\u00de\nthe detector operated in the self-reset mode. As shown in\n                                                     where  Qin  is  the  input  charge, gm and  gds  are  theFig. 2, the integrated JFET is biased in a source\u2013follower\n                                                          transconductance and the channel conductance of the\ncon\ufb01guration and is followed by a voltage ampli\ufb01er. Cd is\n                                                               integrated transistor, respectively; z0  is a high-frequency\nthe total capacitance seen by the detector anode and is a\n                                                            zero  given by  z0 \u00bc gm=Cgs and  plays no  role  at  thesum of the gate-drain capacitance Cgd and the depletion\n                                                              frequencies of interest.\ncapacitances between  the anode and  the  neighboring\n                                                           Considering the input charge as a time-domain step\nregions\u2014Cbulk, Ca  ig, Ca  r1 in Fig. 3. Cgs  is the gate-\n                                                               function,  tr  is the  rise time (the time constant of the\nsource capacitance of the integrated FET and CL  is the\n                                                            exponential increase) of the source signal, whereas tf 1 is the\ntotal load capacitance at the source node.\n                                                        decay time constant of the source signal. They are given by\n  The self-reset mechanism\u2014represented in the circuit by\nthe resistance Rd\u2014works basically in the following way: as                                               CL \u00fe Cin \u00fe Cd\u00feCgsCdCgs     CL \u00fe Cin\nthe  electrons  (signal  or/and  thermally  generated)  are     tr \u00bc              Cd                  Cd                   (2)\ncollected to the detector anode, this becomes more and            gds \u00fe gm Cd\u00feCgs     gds \u00fe gm Cd\u00feCgs\nmore  negative.  Consequently  the  transistor  gate  gets\nincreasingly reverse biased with respect to the channel.                                gds\nAt a given potential difference, a weak avalanche break-     tf 1 \u00bc Rd  Cd \u00fe Cgs                  .                          (3)\n                                                                      gm \u00fe gds\ndown region is formed in the transistor channel between\ngate and drain; the holes generated in  this region are    Analyzing the expression of tr from Eq. (2), one can see\ncollected at the gate and compensate for the signal/leakage    that the ampli\ufb01er  rise time  is determined by the total\nelectrons. A very detailed characterization of the dischar-    capacitance seen by the source node and the transistor\nging mechanism can be found in Ref. [6].                   parameters gm and  gds. Since the optimization of the\n  Performing the small-signal analysis of the circuit in    integrated transistor with respect to  this parameters  is\nFig.  2,  the  expression  of  the  source  voltage  vs\u00f0s\u00de  in    limited by the technology, the minimization of the signal                            ARTICLE IN PRESS\n\n338                     A. Niculae et al. / Nuclear Instruments and Methods in Physics Research A 568 (2006) 336\u2013342\n\nrise time is also limited. Typical values of tr are in the range    assumptions like ideal operational ampli\ufb01er A0 with A0 !\nof 80\u2013100 ns for 10 pF total load capacitance.       1 and in\ufb01nite bandwidth and is given by:\n  The output voltage of the whole ampli\ufb01er chain  is\n                                                                        Qin     s  t1     s  t2\ngiven by                                                                vout\u00f0s\u00de                                                       (5)\n                                                         Ca  ig  1 \u00fe s  t1 1 \u00fe s  t2\n                Cin    s  tf 2\nvout\u00f0s\u00de \u00bc   vs\u00f0s\u00de                                             (4)    where\n                Cfb  1 \u00fe s  tf 2\n                                                                     t1 \u00bc Rd Ca  ig;   t2 \u00bc Rfb  Cin.                           (6)\nwhere  tf 2 \u00bc Cfb  Rfb  is the decay time constant of the\nvoltage ampli\ufb01er.                                   The time constants t1 and t2 are determined with the\n                                                       approximation  that  t1bt2  which   is  valid  since  the\n2.2. Charge sensitive ampli\ufb01er readout and self-reset                                                       dynamical resistance Rd  is very large (e.g. hundreds of\noperation                                                  GO). One can observe that the frequency bandwidth of the\n                                                         ampli\ufb01er is no more limited by the integrated transistor\n  The rise time limitations of the source\u2013follower readout                                                         parameters gm and gds. The rise time of the output signal\ncon\ufb01guration can be overcome by choosing an alternative                                                                                  is then determined by the rise time of the incoming charge\nreadout scheme of the SDD, which is the charge-sensitive-                                                                     signal.\nampli\ufb01er (CSA) readout. This readout concept  is com-\nmonly used for PIN diode detector types (with external\n                                                                      3. Pulsed reset operation mode\nfront-end transistors) and has also been implemented for\nsome special types of SDD detectors having an integrated\n                                                As  described  in  the  previous  section,  the  self-reset\nfeedback capacitor [7,8].\n                                                           operation  is a very comfortable way of operating the\n  The  standard SDDs  detectors  have no  integrated\n                                               SDDs. However, the reset current provided by the self-reset\ncapacitors; nevertheless one can use the parasitic capacitor\n                                                   mechanism to discharge the anode acts in the same way as\nbetween the detector anode and the transistor guard ring\n                                                             the  detector  leakage  current  as  far  as  the  noise  is\n(Ca  ig  in  Fig.  3)  as  feedback  capacitor. The  circuit\n                                                           concerned. Since the reset current is proportional to the\nschematic is shown in Fig. 4. The integrated transistor is\n                                                            input photon  rate,  it  is unavoidable  that  the energy\nstill biased in the source follower con\ufb01guration, but  is\n                                                               resolution degrades with the increasing photon rate. For\nfollowed by a low input impedance, high gain ampli\ufb01er\n                                                              application requiring constant energy resolution over a\nresulting  into a high gain  inverting  voltage ampli\ufb01er.\n                                                                 large range of input count rates, the pulsed reset operation\nThe collected charge will be integrated over the feedback\n                                              mode can be employed.\ncapacitor Ca  ig. Rb is a very large resistance needed to bias\nthe transistor guard ring with a negative voltage, Cc is a\nlarge  coupling  capacitor needed  to decouple  the DC\n                                                                                                                 collecting anode\nvoltages of the guard ring and the ampli\ufb01er output. Their\nin\ufb02uence  in  the  ampli\ufb01er  transfer  function  can  be         integrated FET\nneglected.\n  The frequency transfer function of the CSA readout\ncon\ufb01guration can be determined by  considering some\n\n                                                                                                                                             reset\n\n\n                                                                          S\n                               fd\n SDD\n           Rd                                                     G\n                                                   Rfb                                                                 D\n\n                      Ca-ig      fs                                out\n                                          Ao\n   ~                                   Cin\n  iin           Cd\n\n                          ig\n                                          Cc\n                               Rb\n\n      \n\n## 2. niculae2006optimizedreadoutmethods pages 3-6 (Context ID: pqac-00000024)\n\n\n\n                                                                                                                                             reset\n\n\n                                                                          S\n                               fd\n SDD\n           Rd                                                     G\n                                                   Rfb                                                                 D\n\n                      Ca-ig      fs                                out\n                                          Ao\n   ~                                   Cin\n  iin           Cd\n\n                          ig\n                                          Cc\n                               Rb\n\n                                         Vig\n\nFig. 4. Charge-Sensitive-Ampli\ufb01er readout con\ufb01guration with parasitic     Fig.  5. Schematic top view of the inner part of the SDD with the\nfeedback capacitance of the SDD with integrated FET.                       integrated transistor and the reset diode.                            ARTICLE IN PRESS\n\n                        A. Niculae et al. / Nuclear Instruments and Methods in Physics Research A 568 (2006) 336\u2013342                     339\n\n  To operate the detector in the pulsed reset mode, a reset\nstructure integrated directly onto the detector anode (see\nFig. 5) can be used; by applying short positive pulses to this\ndiode, the signal charge collected at the anode is removed.\n  For  the  pulsed  reset  operation  of  the SDD  with\nintegrated FET, the CSA readout con\ufb01guration shown in\nFig. 4 has been employed.                                                                                                                                                                                                                                         events\n                                                                              of\n\n4. Measurements and results                                                                                                                                                                                                                                         Nunber\n\n  The spectroscopic measurements performed with SDDs\noperated in the readout con\ufb01gurations described in the\nprevious section will be now presented.\n\n\n4.1. Source\u2013follower vs. CSA readout\n\n  To compare the performance of both SF and the CSA                                      Energy [eV]\nreadout con\ufb01gurations, spectroscopic measurements with a                                                                               Fig. 7. Energy spectra of 55Fe source measured in both SF and CSA\nconventional 5 mm2 SDD operated in the self-reset mode     con\ufb01gurations at  20 C and 1 ms shaping time.\nhave been  carried  out.  Fig. 6 shows  the  oscilloscope\nwaveform of the CSA output signal due to a 5.9 keV\nphoton from a 55Fe radioactive source. The  rise time\nmeasured from 10% to 90% of the amplitude (i.e. 2:2   tr)\nis about 50 ns and is much smaller than in the SF readout\n(e.g. 200\u2013300 nS). From the amplitude of the  5.9 keV\nsignals, a value of about 30 fF has been estimated for the           [eV]\nparasitic feedback capacitance Ca  ig.                                                        line\n  The  energy  spectra  of  the  55Fe  radioactive  source\nmeasured in both con\ufb01gurations with the detector cooled             Mn-K\u03b1\nat  20 C and at a shaping time of 1 ms are plotted Fig. 7.      of\nThe     value           of the                 input                    photon rate was                                    about                                          1 kcps.                                          As            FWHMexpected,           the               noise                    performances                                    are                                           similar                                                     in both\ncon\ufb01gurations and this is due to the fact that the noise is\ndetermined entirely by detector capacitance, by the leakage\n\n\n\n\n                                                                                                       Input count rate [kcps]\n\n                                                                               Fig. 8. Energy resolution of Mn-Ka line as a function of the input count\n                                                                                  rate measured with both SF and CSA con\ufb01gurations.\n\n\n\n\n                                                             current and by the  properties of the input  transistor\n                                                               integrated on the detector [9].\n                                                   The  energy  resolution  measured  at  different  input\n                                                    photon rates is plotted in Fig. 8. The operation tempera-\n                                                               ture was again  20 C and the shaping time was reduced to\n                                                      250 ns in order to minimize pile-up events at high count\n                                                                      rates. One can  see  in both  cases  the same  expected\n                                                          degradation of the energy resolution with the increasing\n                                                            input count rate due to the increase of the reset current in\n                                                             the self-reset mechanism, as previously explained.\n                                                       Another consequence of the self-reset mechanism, which\n                                                        has not been discussed so far, is the change of the peak\n           Fig. 6. CSA output signal from a 5.9 keV photon.             position with the changing input count rate, which can be                            ARTICLE IN PRESS\n\n340                     A. Niculae et al. / Nuclear Instruments and Methods in Physics Research A 568 (2006) 336\u2013342\n\n\n\n\n [eV]\n line\n Mn-K\u03b1\n of\n   position\n Peak\n\n\n\n\n\n                               Input count rate [V]\n\nFig. 9. Peak position of Mn-Ka line as a function of the input count rate\nmeasured with both SF and CSA con\ufb01gurations.                              Fig. 10. Oscilloscope picture of the ampli\ufb01er output signal with the SDD\n                                                                        operated in pulsed reset mode.\n\n\nobserved in the plot of Fig. 9. The change is caused by the\ndischarging mechanism which  is self-adapting, therefore\nthe  reset  current  sets  itself  to  the  values needed  to\ncompensate the various rates of signal electrons arriving\nto the anode. This leads to a change of the anode potential\nwhich translates into a change of the depletion capaci-\ntances connected to the anode and contributing to the\nsignal amplitude.                                                                                                                   [mV]\n Now looking at the expression of the source voltage in           \u2206VoutEq. (1), this is inverse proportional to the total capacitance\nCd \u00bc Cg d \u00fe Ca  ig \u00fe Ca  r1 \u00fe Cbulk. The initial increase of\nthe peak position can be explained by the reduction of the\ncapacitance Cg d with more negative gate voltage. At the\nsame time, the other capacitances which contributes to Cd\nincrease with the decreasing anode voltage due to the\nincreasing  input  count  rate.  Their  variation becomes\ndominant for the last part of the plot.                                    (a)                       Reset ON voltage [V]\n  In the case of the CSA readout, only one capacitance\n(Ca  ig) determines the signal amplitude (see Eq. (5)). With\nmore negative anode voltage due to the increase of the\ncount rate, Ca  ig increases and the peak position decrease.\n  In both cases the peak position change with the input\nrate (or with the temperature) can be greatly reduced by\nusing a peak  shift compensation  circuit. Using such a             [mV]\ncircuit, a minimum peak shift of  0:03% (i.e.  2 eV for\n5.9 keV photons) up to input count rates as high as 400           \u2206Vout\nkcps has been reported in Ref. [10].\n\n4.2. Measurements of the SDDs in pulsed reset mode\n\n  As already mentioned, the CSA readout circuit described\nin Fig. 4 has been used for the measurements with SDDs\noperated  in  the  pulsed  reset  mode.  The  dynamical\nresistance Rd of the self-reset mechanism must be however      (b)                     Reset pulse width [ns]\nreplaced by the  reset diode connected to the detector     Fig. 11. Output voltage difference before and after reset as a function of:\nanode.                                                                              (a) reset high voltage and (b) reset pulse width.                            ARTICLE IN PRESS\n\n                        A. Niculae et al.\n\n## 3. schlosser2010expandingthedetection pages 2-4 (Context ID: pqac-00000025)\n\ne FWHM especially at lower X-ray\nenergies. In the low energy regime the bene\ufb01t of a low electronic\nnoise value on the energy resolution is the greatest.\n   Possibilities to improve the energy resolution are the reduction\nof  the  total  detector  capacitance and  the  leakage  current.\nA reduction of  Ctot from 150 to 80 fF  is achieved by moving\nthe anode and the integrated JFET from the center (standard SDD)\nto the border of the SDD (droplet SDD\u00bcSD3) [10,11]. The JFET\nlocated at the SDD border has a second positive effect. Irradiation\nof the integrated JFET can be avoided by mounting an appropriate\ncollimator. Undesired background events can be reduced. This\ncircumstance leads to a higher P/B ratio [10]. Furthermore the\nleakage current could be decreased, through a new fabrication\ntechnology, poly-silicon, to a stable level down to 200 pA/cm2 at\nroom temperature, reducing the energy resolution further.\n   The dependence of the energy resolution of a 10 mm2 SD3 on      Fig. 3. Superposition of spectra of Boron, Carbon and Oxygen measured with a\nthe count rate is illustrated in Fig. 2. Energy resolution values     10 mm2 SD3, with pn-Window at T\u00bc  20 1C. The FWHM of the B2Ka, C2Ka and\ndown to a full width at half maximum (FWHM) of 123 eV at    O2Ka lines are down to 38, 42 and 48 eV.\nthe Mn2Ka  line have been currently measured at moderate\ntemperatures of T\u00bc  20 1C. The charge sensitive ampli\ufb01er (CSA)\n\n                                                               readout con\ufb01guration  in combination with the pulsed  reset\n                                                                  operation mode ensures a nearly constant energy resolution up\n                                                                     to a few hundred kcps [9].\n\n\n\n                                                                             3. Optimizing the detector for light element performance\n\n\n                                                                  Apart from the detector noise, the detector entrance window is\n                                                               important  at low X-ray  energies. A modi\ufb01ed new  detector\n                                                                entrance window, pn-Window, has been developed for optimum\n                                                                            light element detection. The pn-Window reduces the loss of\n                                                                generated electrons in the SDD p+ layer of the entrance window\n                                                                           after an interaction of a X-ray photon in this region, so that a\n                                                             lower number  of events with  partial charge  collection  are\n                                                                     detected. This leads to an improved energy resolution measured\n                                                                         at lower X-ray  energies. The  spectra  of boron and carbon\n                                                         measured with a 10 mm2 SD3 detector are plotted in Fig. 3.\nFig. 1. Energy resolution against X-ray energy for different contributions of the    Energy resolution values of 38 eV for Boron line (138 eV) or 42 for\nelectronic noise.                                                Carbon line (277 eV) have been determined.272                              D.M. Schlosser et al. / Nuclear Instruments and Methods in Physics Research A 624 (2010) 270\u2013276\n\n\n\n\n\n                                                                                                Fig. 6. FWHM at Mn  Ka of a circular 30 mm2 SDD vs. shaping time at  20 and\nFig. 4. Spectra of two 10 mm2 SD3 with a standard entrance window (EW) (gray)      30 1C. At optimal shaping times of 2 or 3ms FWHM of 129 eV have been\nand a optimized EW (black), while irradiating with a 55Fe source. The optimization     measured.\nof the P/B and P/V ratios by the pn-Window is obvious.\n\n\n\n\n\n                                                                                                Fig. 7. FWHM at Mn2Ka of a square 100 mm2 SDD vs. shaping time at   20,   25,\n                                                                        30 and   351C.\n\nFig. 5. Spectrum of a 20 mm2 SD3 with optimized pn-Window, while irradiating\nwith a 55Fe source. The FWHM of the Mn2Ka line is 125 eV and a P/B ratio of up to\n16 000 has been measured.\n\n\n\n   The P/B and P/V (peak to valley) ratio of the SDDs with\npn-Window is improved by the same physical mechanism also for\nhigher X-ray energies e.g. Mn\u2013Ka. This effect is shown in Fig. 4.\n\n\n4. Optimization of area and geometry to increase the\ndetection ef\ufb01ciency for the \ufb02uorescent X-rays\n                                                                                                   Fig. 8. Detector consisting of 6  100 mm2 cells with an on chip collimator.\n   The optimization of the geometry of the detection area is\nimportant  for  applications  requiring  maximum  collection   FWHM  at Mn2Ka  of  a  100 mm2  circular SDD  for  four\nef\ufb01ciency of the incoming photons. This can be achieved by    temperatures is plotted against the shaping time.\nmaximizing  the  detection  area,  by  matching  the  detector        Increasing the detector area furthermore to several cm2 by\ngeometry to the geometry of the system, as well as by maximizing    maintaining the energy resolution and avoiding dead area  is\nthe detection solid angle for the incident radiation.                  possible with monolitical SDD arrays. Detectors with large areas\n    Fig. 5 shows the spectrum of 55Fe measured with a droplet    have been produced in that way [11]. The one presented here has\nshaped, SD3, detector, of which the detection area has been    an area  of 6  100 mm2, consisting  of  six  cells. The energy\nincreased to 20 mm2. The energy resolution at Mn2Ka line is     resolution of this detector is down to 140 eV at the Mn2Ka line\n125 eV at T\u00bc  20 1C with a P/B ratio of 16 000. Prototypes of    and moderate temperatures of   201 for each channel. Operation\n30 mm2 SD3 have also been developed. They are  still under      is possible for input count rates of up to 3 Mcps. By means of an\ninvestigation.                                                 adapted radiation entrance window, these detectors can also be\n    Fig. 6 shows the FWHM at Mn2Ka of a 30 mm2 circular SDD    used in combination with scintillators for gamma ray detection\nagainst shaping time at two different temperatures. In Fig. 7 the     (Figs. 8 and 9).                                 D.M. Schlosser et al. / Nuclear Instruments and Methods in Physics Research A 624 (2010) 270\u2013276                          273\n\n\n\n\n\n                                                            Fig. 9. 55Fe spectra of each channel of the six element SDD.\n\n\n\n\n\n                                                                                                Fig. 12. SDD without a housing, electrically coupled by a \ufb02ex lead, as a detector to\n                                                                          be integrated arbitrarily into analysis instruments  e.g. electron microscopes,\n                                                                      where the space for the detector is limited.\n\n\n                                                                                cooling plate\n\n                                                                                                              peltier element\n\nFig. 10. Rococo 2 consists of four SDDs, with an area of 15 mm2 each, a central\nhole and a on chip collimator.\n\n\n\n\n                                                                       ceramic\n                                                           SDD chip\n\n\n                                                                                                Fig. 13. Example of a construction for the \ufb02exlead SDD shown in Fig. 12, which is\n                                                                                 cooled in this case by a cooling plate and a peltier element.\n\n\n                                                                     Speci\ufb01c devices with a central hole for close arrangement of the\n                                                                     detector to the sample to ensure high collection ef\ufb01ciency of X-ray\n                                                               \ufb02uorescence photons have been developed and tested (Fig. 10)\n                                                                              [12]. In such a geometry the detector covers a bigger solid angle\n                                                           from the excitation point of the \ufb02uorescent X-rays on the sample,\n                                                                so that the detected fraction of \ufb02uorescent X-rays is increased\n           \n\n## 4. lechner2004novelhighresolutionsilicon pages 2-4 (Context ID: pqac-00000026)\n\nard the drift rings. This\noperating conditions. The arrows indicate the paths of                                              new layout allows the design of a readout anode which has\nelectrons drifting to the anode.                                                          a smaller area. As the capacitance of the readout node is\n                                                        mainly given by the area of the anode, reducing the area\n                                                             helps greatly.\nthe low collecting anode capacitance being independent of       The capacitance of the readout node in\ufb02uences the\nthe detector area. This results in low series and 1/f noise      electronic noise of the detector. The noise contributions of an\ncontributions [see Eqn (1)]. The anode capacitance is about    SDD are serial noise, 1/f noise and parallel noise:\n200 fF for standard SDDs.\n                                                                           2kBT C2  A continuous discharge of the anode capacitance  is          ENC2 D A1                                                     C A22 afC2 C  A3qIl        \u25b71\u25c1\ndirectly implemented within the integrated FET, so a pulsed                     gm\n                                                                                                                                                                 serial 1/f noise    parallel noise\nreset mechanism is avoided. The high electric \ufb01eld in the gate-                                     serial white noise\ndrain channel region is responsible for a weak avalanche\n                                                    where\nprocess, which injects holes into the gate. This process\ndischarges the collected signal and thermally generated       ENC D numberofelectrons:equivalentnoise charge (C);\nelectrons.11\n\n\n\nCopyright \uf6d92004 John Wiley & Sons, Ltd.                                                                       X-Ray Spectrom. 2004; 33: 256\u2013261258    P. Lechner, A. Pahlke and H. Soltau\n\n\n\n\n\n                                                                 Drift Rings\n\n\n\n                                                         Irradiated area\n\n\n                                                    Signal electrons\n\n\n                                         Anode and\n                                                      integrated FET\n\n\n\n\n      Figure 3. Layout of the SD3 chip. The integrated JFET is\n     moved to the margin of the chip. The drift \ufb01eld is de\ufb01ned in\n     such a way as to make all signal electrons drift towards the\n      readout anode situated next to the JFET. The size of the anode     Figure 4. Photograph of a mounted and bonded SD3 chip.\n        is 400 \u00b5m2.                                              The chip is mounted on a TO8 housing. The droplet-like shape\n                                                              can be seen.\n\n           gm D transconductance of the JFET (A V  1);               The standard SDD achieves an energy resolution of\n      A1, A2, A3 D constants depending on the \ufb01lter function of the     152 eV  at   11 \u00b0C (shaping time  1.0 \u00b5s)  at  5.9 keV (Mn\n                  shaper;                                     K\u02db) and a count rate of a few thousand cps, whereas\n          T D temperature (K);                                   the SD3 has an energy resolution of 134 eV under the\n         C D total detector capacitance (F);                  same conditions. By further cooling the SD3  to   15 \u00b0C\n                    af D constant parameterizing the 1/f noise (V2);        and using a smaller collimator (0.8 mm radius; see later)\n                        Il D leakage current (A);                           which covers the outer margin of the chip, the energy\n         D shaping time (s);                                    resolution can be improved to 128 eV  at a count  rate\n              q D elementary charge (C);                              of 100 cps  (see  Fig. 5). The shaping time  is  1.0 \u00b5s  for\n              kB D Boltzmann\u2019s constant (J K  1).                          this measurement. By further cooling the chip to   25 \u00b0C\n                                                        and at low count rates \u25b7<<1 kcps\u25c1, an energy resolution\n     For the noise equation, the mathematical frequency spectrum\n                                                                        of 125 eV could be achieved at shaping times of about\n   1  \u03c9 1 is used. The readout electronics use a source\n                                                                           1.5 \u00b5s (Rohde M, R\u00a8ontek Holding, personal communication,\n      follower con\ufb01guration. An Amptek A250 serves as a charge-\n                                                                         2001).\n      sensitive preampli\ufb01er.12\n                                                                          All measurements were performed with a radioactive\n       By reducing the capacitance, the electronic noise contri-                                                                        55Fe source. In the spectrum (Fig. 5) the Mn K\u02db (5895 eV) and\n      butions of serial white and serial 1/f noise can be minimized.\n     The detector capacitance of an SD3 is determined from ENC2\n     vs shaping time measurement and is measured to be about                                  energy (eV)\n     120 fF compared with 200 fF for standard SDDs.                          1000   2000   3000   4000   5000   6000\n         In Fig. 4, a mounted and bonded SD3 chip is shown. The        10000\n      chip is mounted on a TO8 housing with 16 pins for the                    shaping time 1,0 \u00b5s\n                                                                                    Temperature -15\u00b0C     supply voltages. A thermoelectric element is included in the         1000\n                                                                                    energy resolution 128 eV (Mn-K\u03b1)\n      housing. The droplet-like shape of the detector can easily be\n      seen. The homogeneous entrance window which is shown\n                                                                     100     on the picture consists of a \ufb02at p implant covered with a thin                  counts\n     aluminum layer. The detector is back-side illuminated.\n                                                                      10\n\n   MEASUREMENTS ON SD3 COMPARED WITH\n                                                                       1\n   STANDARD SDD                                               500     1000    1500    2000    2500    3000\n                                                                                                     channel\n    Energy resolution\n     To characterize the properties of the new SD3, chip measure-     Figure 5. Fe55 spectrum, showing an energy resolution of\n     ments were performed on standard SDD and SD3 chips from     128 eV at  15 \u00b0C. The spectrum was recorded using a shaping\n      the same wafer. The substrate orientation was < 100 >. Both      time of 1 \u00b5s, temperature  15 \u00b0C and count rate 100 cps. The\n     SD3 and standard SDDs underwent the same production      collimator used has a diameter of 1.6 mm. The\n      steps.                                                       peak-to-background value is \u00be9000.\n\n\n\n       Copyright \uf6d92004 John Wiley & Sons, Ltd.                                                                       X-Ray Spectrom. 2004; 33: 256\u2013261                                                                                Novel high-resolution silicon drift detectors   259\n\n\nMn K\u02c7 (6492 eV) lines can be seen. The theoretical limit for         350\nenergy       resolution is given by the Fano noise: FWHMFANO D                           0.25 \u00b5s   p\n2 ln\u25b72  2\u25c1  \u03b5FE  , where \u03b5  is the pair production energy         300              0.5 \u00b5s\n                                                                                            1.0 \u00b5s(3.7 eV for silicon at room temperature), F the Fano factor           (eV)                   2.0 \u00b5s\n(0.115 for silicon) and E  the energy of the absorbed photon         250\n(5895 eV for the Mn K\u02db line). This gives a theoretical limit                                                                                                                               Mn-K\u03b1\nof 118 eV for a detector based on silicon for the detection of         200\nthe Mn K\u02db line. The electronic noise of the detector can bedetermined in a good approximation by                                              FWHM 150\n\n               FWHM2  FWHM2FANO                     100\n         ENC D       p                      \u25b72\u25c1             -15   -10    -5    0     5    10    15    20    25\n                         2 ln\u25b72  2\u25c1\u03b5\n                                                                               Temperature (\u00b0C)\nThe electronic noise for an energy resolution of 128 eV was     Figure 7. Temperature dependence of the energy resolu\n\n## 5. lechner2004novelhighresolutionsilicon pages 4-5 (Context ID: pqac-00000027)\n\n                                                                                                    Mn-K\u03b1\nof 118 eV for a detector based on silicon for the detection of         200\nthe Mn K\u02db line. The electronic noise of the detector can bedetermined in a good approximation by                                              FWHM 150\n\n               FWHM2  FWHM2FANO                     100\n         ENC D       p                      \u25b72\u25c1             -15   -10    -5    0     5    10    15    20    25\n                         2 ln\u25b72  2\u25c1\u03b5\n                                                                               Temperature (\u00b0C)\nThe electronic noise for an energy resolution of 128 eV was     Figure 7. Temperature dependence of the energy resolution of\ndetermined as 5.7 electrons, which is independent of energy.     an SD3 chip. Even at room temperature the energy resolution\n   The improvement in energy resolution compared with       for the Mn K\u02db line is better than 200 eV. Cooling to  5 \u00b0C is\nstandard SDDs is a result of the reduced detector capacitance.      suf\ufb01cient for an energy resolution down to 140 eV.\nElectronic noise with regard to serial and 1/f  noise  is\nreduced. For comparison, SD3  detectors with standard                                                                   In Fig. 7 the temperature dependence of the spectroscopic\nreadout anode design were processed. They show the same                                                         performance of an SD3 chip is plotted. For a shaping time of\nenergy resolution as standard SDDs. The newly designed                                                                 0.25 \u00b5s the energy resolution is better than 200 eV for room\nreadout anode  is therefore the reason for the improved                                                             temperature. The in\ufb02uence of the temperature-dependent\nenergy resolution.                                                             leakage current can be reduced by the use of short shaping\n   The reduced energy resolution plays an important role                                                            times at room temperature. For temperatures below 0 \u00b0C the\nfor the detection of low-Z elements. For photon energies                                                 optimum shaping time changes to 0.5 or 1.0 \u00b5s because of the\nof 1000 eV the Fano noise is only 49 eV. Electronic noise of                                                                         serial noise contribution. Cooling to  15 \u00b0C is suf\ufb01cient for\nthe detector remains constant for all energies, as mentioned                                                 optimum energy resolution. This temperature can easily be\nabove. An improvement in energy resolution of 15 eV at                                                           achieved by the thermoelectric element which is included in\n5.9 keV, as has been seen for SD3 chips compared with                                                               the TO8 housing.\nstandard SDDs, is therefore very important for the detection\nof photons in the low energy range.                       Count rate dependence\n                                                    The count rate dependence is a very important point in many\nNoise measurement                                          \ufb01elds of applications.7 Si(Li) detectors are at a disadvantage\nTo extract the noise parameters of an SD3 chip, energy     because of their long shaping times. Silicon drift detectors\nresolution is measured for different shaping times (see Fig. 6).     bene\ufb01t from their low shaping times of less than 1.0 \u00b5s.\nThe chip is cooled with a thermoelectric element to  15 \u00b0C.         In Fig. 8, the count rate dependence of FWHM of Fe K\u02db\nUsing Eqn (1) \ufb01tting of a ENC2 vs shaping time measurement     (6400 eV) is plotted for a standard SDD compared with the\ngives a leakage current of 2.76 pA, a 1/f  coef\ufb01cient of     SD3 for two different shaping times. As x-ray source an x-\n4.79 \u00f0 10  12 V2 and a total detector capacitance of 120 fF.     ray tube with an iron anode was used. The gradient for the\nTypical total capacitance values for standard SDDs are 200 fF.\nLeakage current and 1/f coef\ufb01cient are the same for standard\n                                                              280\nSDDs.\n                                                              260            0.5 \u00b5s Std. SDD        1 \u00b5s\n                                                                                          1.0 \u00b5s Std. SDD\n                                                              240    120                                                                                                        (eV)                 0.5 \u00b5s SD3\n            leakage current:      1.37 pA                           220            1.0 \u00b5s SD3                 0.5 \u00b5s\n    100      1/f coefficient:        5.6475e-12 V2                                                                                                                              Fe-K\u03b1 200\n             detector capacitance: 119 fF\n                                                              180\n     80\n                                                              160 [q2]                                                                                                               FWHM\n ENC2  60                                                        140                                                              120\n     40                                                                 1000         10000        100000        1000000\n                                                                                 count rate (cps)\n     20\n                                                             Figure 8. Count rate dependence of FWHM of Fe for an SD3\n      0                                                         chip compared with a standard SDD. Because of the\n       0       1       2       3       4       5      6\n                                                           asymmetric shape of the SD3 chip the count rate dependence\n                                    \u03c4 [\u00b5s]\n                                                                                     is larger than that of a standard SDD. Nevertheless, even at a\nFigure 6. ENC2 vs  measurement for an SD.3 The \ufb01tting gives     count rate of 105 cps the energy resolution is better than\na total capacitance of 119 fF.                                180 eV for the Fe K\u02db line.\n\n\n\nCopyright \uf6d92004 John Wiley & Sons, Ltd.                                                                       X-Ray Spectrom. 2004; 33: 256\u2013261260    P. Lechner, A. Pahlke and H. Soltau\n\n\n     SD3 is somewhat higher than for standard SDDs. The reason        7000\n      for this behavior is the asymmetric shape of the detector.        6000\n     The rise time of the signal varies with the position of the                                                                   5000             SD3\n      incident photon. Especially for low shaping times which are                               standard SDD\n     needed for high count rates this results in a degraded energy        PTB 4000      resolution.                                                    3000\n                                                                                                                                              Partial events at\n         Nevertheless, using a shaping time of 0.5 \u00b5s count rates of        2000      Partial events at                  the outer margin                                                                                           the integrated FET\n      105 cps are feasible with an energy resolution of better than\n                                                                   1000\n     180 eV for Fe. The SD3 chip can therefore be used for count\n      rate applications up to 105 cps as well as the standard SDD.            0\n                                                                                      0.0     0.2     0.4     0.6     0.8     1.0     1.2\n                                                                                               collimator radius (mm)\n     Peak-to-background value\n   A good peak-to-background (PTB) value is important for     Figure 10. Peak-to-background values of an SD3 compared\n     low-energy spectroscopy. PTB is de\ufb01ned as the maximum      with a standard SDD for different collimator radii. The PTB of\n     amplitude of the Mn K\u02db line from a 55Fe radioactive source      the SD3 is no longer limited by partial events occurring at the\n     divided by the average amplitude of the continuum in the      integrated FET but only by the entrance windows and the outer\n     energy range from 800 to 1200 eV. The background of the     margin of the detector.\n    SDD spectrum is given by partial events occurring near the\n     FET, at the outer margin of the chip or in the \ufb01rst few      partial e\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027]\n\nStatus: Paper Count=23 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=28 | Current Cost=$0.1511 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000028\n\nFrom text 'rinaldi2015electronprobemicroanalysis pages 7-8'.\n\nRomano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.\n\nAt low beam energies (<5 keV), FEG electron sources can achieve finely focused beams (<100 nm) with relatively high currents (up to 100 nA), reducing the effective ionization range to sub-micrometer scales and improving lateral resolution and surface sensitivity. For trace element analysis, detection limits of a few ppm are achievable through high-beam currents (up to 3 \u03bcA) and long acquisition times. Improved methods employ fractional counting times at multiple sample positions to mitigate beam damage, statistical data filtering, and improved background modeling. Analyses for trace elements at high resolution have been performed at 35 keV with 500 nA and total counting times of 15 minutes. However, at low voltages (5-6 keV), accuracy challenges arise with systematic deviations in transition element analysis, including Cr underestimation (-0.7 to -17%) and Fe/Ni overestimation (+14 to +42%), highlighting the need for careful standard selection and X-ray line choices at low overvoltages.\n\n\n---\n\n## pqac-00000029\n\nFrom text 'wuhrer2016lowvoltageimaging pages 7-10'.\n\nRichard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.\n\nThe excerpt discusses low-voltage SEM microanalysis and acquisition parameter adjustments. It explains that lowering accelerating voltage improves spatial resolution and image quality, requiring selection of lower excitation energy X-ray lines (L- and M-family lines at 0-4 kV) rather than K-lines. Beyond voltage adjustment, reducing probe current and changing scan speed are necessary acquisition parameter modifications. The excerpt mentions improved detector technology with SDD detectors achieving greater X-ray collection efficiencies and better sensitivity for low-energy X-rays. New soft X-ray spectroscopy systems offer superior energy resolution and detection limits for light elements below 100 ppm. Higher accelerating voltages create larger interaction volumes that degrade spatial resolution, while lower voltages reduce the analytical volume. However, the excerpt does not specifically address overvoltage effects at 5 keV or detailed counting strategies for trace element detection.\n\n\n---\n\n## pqac-00000030\n\nFrom text 'wuhrer2016lowvoltageimaging pages 10-12'.\n\nRichard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.\n\nThe excerpt discusses challenges with low-voltage EDS analysis that relate to trace element detection and sensitivity. At lower accelerating voltages, there is improved spatial resolution but analysts must shift to L- and M-family X-ray lines (0-4 kV) rather than K-lines. However, measurement of low-energy L-lines presents complications including low fluorescence yield, increased X-ray absorption, X-ray interferences from other elements, and poorly determined mass absorption coefficients. The use of transition element L-lines specifically results in poor accuracy and sensitivity. Large quantification errors exist on lower energy X-ray lines, limiting quantitative analysis capabilities. The excerpt emphasizes that for accurate results, standards-based analysis is preferable to standardless analysis, though errors remain.\n\n\n---\n\n## pqac-00000031\n\nFrom text 'gollaschindler2026edswithlowvoltage pages 3-6'.\n\nUte Golla-Schindler and Gerhard Schneider. Eds with low-voltage sem: possibilities and limitations of lithium detection and quantification. EPJ Web of Conferences, 349:01004, Jan 2026. URL: https://doi.org/10.1051/epjconf/202634901004, doi:10.1051/epjconf/202634901004. This article has 0 citations and is from a peer-reviewed journal.\n\nThis excerpt discusses low-voltage EDS analysis and how lowering accelerating voltage addresses detection limits and spatial resolution challenges. It explains that reducing accelerating voltage from 20 keV to 1 keV decreases interaction volume by approximately 100 times, improving both information depth and spatial resolution. The information depth is roughly one-third to one-half of the electron range. The excerpt notes that detection limits depend on scattering cross-section and signal detection capabilities. It also addresses acquisition parameter adjustments, noting that lowering beam current and current density reduces all beam damage effects. At lower voltages, knock-on damage decreases but beam damage from heating and ionization may increase due to enhanced cross-sections for inelastic and elastic scattering. The text emphasizes that these factors become increasingly critical with decreasing acceleration voltage, particularly for light element detection.\n\n\n---\n\n## pqac-00000032\n\nFrom text 'gollaschindler2026edswithlowvoltage pages 1-3'.\n\nUte Golla-Schindler and Gerhard Schneider. Eds with low-voltage sem: possibilities and limitations of lithium detection and quantification. EPJ Web of Conferences, 349:01004, Jan 2026. URL: https://doi.org/10.1051/epjconf/202634901004, doi:10.1051/epjconf/202634901004. This article has 0 citations and is from a peer-reviewed journal.\n\nThis paper by Golla-Schindler and Schneider addresses EDS (Energy Dispersive X-ray Spectroscopy) detection capabilities in low-voltage SEM, specifically focused on lithium detection and quantification in lithium-ion batteries. The work discusses how low accelerating voltages improve detection by increasing effective cross-sections for elastic and inelastic interactions, thereby generating more secondary and backscattered electrons. The study presents methods to reduce examination artifacts through lower accelerating voltages and beam currents. Key challenges addressed include contamination, radiation damage, and charging effects that can compromise EDS analysis accuracy. The authors demonstrate the use of a windowless Oxford Extreme EDS detector (100 mm\u00b2 size, 124.7 eV energy resolution for Mn) that enables low-energy X-ray detection. The paper also introduces a novel quantification method called 'Li by difference' for calculating lithium content from non-normalized EDS quantification. However, the excerpt provided does not contain specific information about Newbury-Ritchie detection limits, detailed acquisition parameters at specific beam energies like 5 keV, overvoltage effects, or counting strategies for trace elements.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032]\n\nStatus: Paper Count=23 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=33 | Current Cost=$0.1950 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
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+                "role": "assistant",
+                "content": "Let me now gather evidence specifically from the Newbury papers and Goldstein text for the Bethe/overvoltage derivation and detection limits:",
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+                "tool_calls": [
+                  {
+                    "id": "toolu_01RyKKfXXXjamkfbkiyiy3yQ",
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+                      "arguments": "{\"question\": \"Newbury Ritchie EDS detection limits trace analysis 0.001 mass fraction measurement time dose counting statistics precision accuracy standardless vs standards-based quantification\"}",
+                      "name": "gather_evidence"
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+                  {
+                    "id": "toolu_014Vv5PkK6B2RGN1hC6sSaDS",
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+                      "arguments": "{\"text_name_list\": [\"newbury2019electronexcitedxraymicroanalysis pages 13-15\", \"newbury2019electronexcitedxraymicroanalysis pages 15-16\", \"newbury2019electronexcitedxraymicroanalysis pages 16-18\", \"newbury2015performingelementalmicroanalysis pages 2-4\", \"newbury2015performingelementalmicroanalysis pages 17-20\"]}",
+                      "name": "read_text"
+                    }
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+                "role": "tool",
+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000033\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 1-2'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 609 citations and is from a peer-reviewed journal.\n\nThis paper demonstrates that SDD-EDS enables trace element detection with limits of detection below 0.001 mass fraction (1000 ppm) within practical measurement times of 500 seconds. The authors describe the k-ratio protocol for quantitative analysis, where characteristic X-ray intensities from unknowns are compared to standards under identical conditions (same beam energy, dose, and detector efficiency). This approach allows the detector efficiency to cancel out mathematically, improving accuracy and precision. The k-ratio/ZAF matrix correction method represents a standards-based quantification approach where measurements don't require standards that closely match the unknown composition, providing flexibility for analyzing complicated multi-element materials. The SDD advances provide accuracy and precision comparable to wavelength-dispersive spectrometry on electron probe microanalyzers, with high-count spectra enabling accurate peak fitting even for severe peak overlaps.\n\n\n---\n\n## pqac-00000034\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 13-15'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses EDS (Energy Dispersive Spectrometry) detection limits and analytical precision for trace element analysis. Trace elements are defined as those with mass concentration C < 0.01. Detection limits ranging from 0.0002\u20130.0005 mass fraction (200\u2013500 ppm) can be achieved with counting times below 500 seconds, depending on the element and matrix composition. The detection limit formula CDL = [3NB1/2/(NS \u2212NB)]CS is presented, where NB is background counts, NS is peak counts, and CS is the known concentration. The excerpt includes precision data showing relative standard deviations (\u03c3 relative) ranging from 0.008\u20131.8% and combined uncertainties from 0.0044\u20131.7% for various elements. The analysis addresses challenges including peak overlap from major/minor constituents and peak interference situations that can be resolved through peak fitting techniques.\n\n\n---\n\n## pqac-00000035\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 1-2'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThis review article by Newbury and Ritchie from 2019 discusses the 50-year evolution of energy dispersive X-ray spectrometry (EDS) in electron-excited X-ray microanalysis. The authors highlight that EDS has matured into a fully quantitative analytical technique capable of matching wavelength dispersive spectrometry (WDS) accuracy for major constituents (>0.1 mass fraction) and minor constituents (0.01-0.1 mass fraction). Importantly, the article indicates that useful analytical accuracy can extend into the trace constituent range (0.001 < mass fraction < 0.01), even when severe peak interference occurs. The excerpt discusses the foundational standards-based k-ratio protocol with matrix correction factors (Z, A, F, c corrections) developed by Castaing. The article emphasizes the importance of controlling measurement parameters such as dose, spectrometer performance, and instrumental drift. The presence of pages 1-2 suggests the full article likely contains more detailed discussion of detection limits, measurement time requirements, counting statistics, precision, accuracy, and potentially comparisons between standardless and standards-based quantification methods.\n\n\n---\n\n## pqac-00000036\n\nFrom text 'ritchie2018exploringthelimits pages 9-11'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThis study explores EDS (Energy Dispersive Spectroscopy) capabilities for rare earth element analysis using silicon drift detectors (SDD). For major/minor elements above 1% mass fraction, SDD achieved relative deviations better than 10%. Between 0.1-1% mass fraction, detection was inconsistent with large uncertainties. Below 0.1% mass fraction, detection was unreliable. The analysis required extended acquisition times (10 minutes live-time per measurement). The authors note that WDS (Wavelength Dispersive Spectroscopy) maintains lower detection limits due to superior peak-to-background ratios. While most EDS measurements remain qualitative or standardless with large error bars, careful analysts using standards-based quantification can achieve accurate results comparable to WDS for major/minor elements. The study suggests combining SDD speed and accuracy for major elements with WDS sensitivity for trace elements.\n\n\n---\n\n## pqac-00000037\n\nFrom text 'ritchie2018exploringthelimits pages 1-4'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThis paper discusses EDS (energy-dispersive X-ray spectrometry) capabilities for trace element analysis, specifically examining rare-earth element detection. The authors explain that EDS detection limits are primarily constrained by the background (continuum) level relative to signal (characteristic) level. They demonstrate that trace measurements in the 0.1-1.0% mass fraction range can be performed accurately with modern silicon drift detectors (SDDs). However, SDDs cannot match WDS (wavelength-dispersive X-ray spectrometry) at the lowest trace levels due to inferior peak-to-background ratios. The paper emphasizes recent improvements in EDS technology\u2014particularly SDDs\u2014that have dramatically enhanced throughput and resolution (approaching 120 eV at Mn-K\u03b1). The authors note that peak-to-background ratios in EDS depend on channel ranges used for continuum and peak estimation, with optimal results achieved by integrating peaks over the central full-width half-max. Recent advances allow EDS to match or exceed WDS accuracy and precision in many applications.\n\n\n---\n\n## pqac-00000038\n\nFrom text 'ritchie2018exploringthelimits pages 4-5'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThis paper addresses EDS (Energy Dispersive Spectroscopy) microanalysis capabilities for trace element detection, specifically focusing on rare earth elements (REE) in mineral samples. The authors discuss measurements of materials with trace quantities below 10% mass fraction, which present challenges for both WDS and EDS techniques. The paper covers the k-ratio quantification method comparing unknown samples to standards, matrix corrections accounting for atomic number (Z), absorption (A), and secondary fluorescence (F) effects, and the importance of multiple measurements for quality assurance. For accurate trace analysis, the authors recommend collecting multiple spectra (5-10 acquisitions) to enable inter-comparison, outlier rejection, and improved spectral quality. The paper includes practical examples using rare earth element-containing glasses at approximately 3-4% mass fraction, demonstrating EDS measurement capabilities at these concentration levels.\n\n\n---\n\n## pqac-00000039\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 18-20'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThis excerpt from Newbury & Ritchie (2019) discusses standardless quantification methods in EDS microanalysis. Standardless analysis requires only beam energy and spectrometer takeoff angle, but lacks electron dose information, necessitating normalization to 100 wt% for meaningful results. Early testing showed standardless analysis produced relative deviations (RDEV) spanning \u00b125% range for 95% of results. The authors note that approximately 95% or more of EDS quantitative compositional results are derived from standardless analysis. The excerpt includes analysis data from NIST reference materials (K523 glass and SRM 610 trace elements glass) measured at 20 keV, demonstrating detection capabilities for trace elements and providing measured concentrations with uncertainties. However, the excerpt does not explicitly address detection limits at 0.001 mass fraction, measurement time, dose-counting statistics relationships, or detailed comparisons of standardless versus standards-based approaches.\n\n\n---\n\n## pqac-00000040\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 16-18'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses two quantification approaches in EDS analysis: first-principles standardless analysis and standards-based methods using remote standards. The remote standards method is described as inherently more accurate than first-principles standardless analysis, providing a compromise between the two approaches since it is tied to measurements of real materials. However, the authors note a significant limitation: vendors implementing standardless quantification often lack adequate documentation explaining their methodology for deriving numerical concentrations. The excerpt emphasizes the importance of understanding which quantification method is being employed and how it affects analytical accuracy. Additionally, the text mentions detector calibration methods, including use of a 'golden detector' calibrated at a beamline to transfer calibration to other detectors.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040]\n\nStatus: Paper Count=23 | Relevant Papers=14 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=41 | Current Cost=$0.2376 | Disease-Target Evidence=0",
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+                "content": "## 1. newbury2015performingelementalmicroanalysis pages 2-4 (Context ID: pqac-00000041)\n\n                                     as determined by a mature version of the k-ratio/matrix\nunknown and standards required for Eq. (1) [3]. To place\n                                                               correction procedure in 1975 is shown in Fig. 1 for WDS\nthe specimen reproducibly within the narrow spatial range,                                                      measurements of major1 constituents [5]. This distribution\nspanning a few micrometers, over which the WDS had\n                                                       can be characterized by a standard deviation of 2.5 %\nconstant  X-ray  transmission,  a  \ufb01xed-position  optical\n                                                                      relative, so that approximately 95 % of the analyses fall\nmicroscope with a shallow depth of focus was incorporated\n                                                            within the span of \u00b15 % relative error.\ninto the EPMA at the coincident focal position for  all\nspectrometers. The condition of the specimen surface was\nrecognized to be another critical requirement [4]. It came to\nbe understood early in the development of EPMA that the\nspecimen had to metallographically polished to a very high\ndegree of surface \ufb01nish, but not chemically etched. To\ncreate contrast in optical metallography, chemical etching\ntypically produces topography through orientation-depen-     1 Note: in this paper, the following arbitrary convention for broadly\ndent etch rates in different grains and phases, but even \ufb01ne-     classifying the concentration range will be followed:\nscale topography can in\ufb02uence measured X-ray intensities,\n                                                                                    \u2018\u2018major,\u2019\u2019 mass concentration C [ 0.1 (more than 10 wt%)\nespecially  for low-energy photons. Moreover,  in some\n                                                                                \u2018\u2018minor\u2019\u2019 0.01 B C B 0.1 (1\u201310 wt%)\ncases, chemical etching induces changes in the surface/         \u2018\u2018trace\u2019\u2019 C \\ 0.01 (\\1 wt%).\n\n123J Mater Sci (2015) 50:493\u2013518                                                                                        495\n\n\nFurther development: energy-dispersive X-ray               continuum, various strategies were developed to determine\nspectrometry                                                     characteristic  intensities,  including  digital  \ufb01ltering  for\n                                                      background removal followed by  multiple  linear  least\nThe development of semiconductor-based X-ray detection    squares (MLLS) \ufb01tting and background modeling under the\nin the 1960s led to the \ufb01rst successful energy-dispersive    peak window  constrained by  the continuum  intensity\nX-ray spectrometer (EDS) using lithium-compensated sil-    measured in energy windows where no peaks occurred [8,\nicon [Si(Li)-EDS] operated on an electron-column instru-    10]. The background-corrected  characteristic  intensities\nment,  an EPMA  [6]. As  compared  to  the  narrow    for the unknown and the standards were used to calculate\ninstantaneous energy range of the WDS, the Si(Li)-EDS     k-ratios followed by the matrix correction procedure. The\nprovided a view of the entire excited X-ray spectrum from     k-ratio matrix correction procedure with the Si(Li)-EDS\na  threshold  of approximately 100 eV (modern  perfor-   was demonstrated to be capable of achieving relative errors\nmance) to the Duane-Hunt limit set by the incident beam    within the WDS distribution for major constituents when\nenergy, up to 20 keV or higher. This wide energy range    the characteristic X-ray peaks did not suffer signi\ufb01cant\nenabled detection of all elements, with the exception of H    overlap from the peaks of other elements. An example is\nand He (modern performance), at every location sampled   shown in Table 1 for the Si(Li)-EDS analysis of gold-\nby the beam, which provided an enormous advantage when    copper alloys (NIST Standard Reference Material 482)\ndealing with complex microstructures where local segre-    where the observed relative errors range from -1.6 to\ngation can create unexpected compositional variation and    1.0 %, falling well within the WDS analysis error distri-\nwhere unexpected elements can be localized as inclusions.    bution of Fig. 1.2 Further development of the EDS quan-\nComprehensive elemental analysis capability, combined     titative microanalysis method enabled accurate analyses\nwith the relative simplicity of non-focusing line-of-sight   when signi\ufb01cant peak overlaps occurred providing the\ndetection, the large solid angle of collection which exceeds     intensities of the mutually interfering species were similar.\nthat of WDS by at least a factor of 10, and the long-term\noperating stability, resulted in the enthusiastic acceptance    Typical SEM/EDS microanalysis practice\nof EDS, especially by the rapidly developing scanning\nelectron microscope (SEM) community. The combination    Despite the level of analytical accuracy demonstrated for\nof SEM imaging with EDS X-ray microanalysis has given    the EDS k-ratio/matrix corrections protocol and the avail-\nthe materials community one of its most powerful micro-     ability of this procedure within most commercial imple-\nstructural characterization tools [2].                         mentations of EDS analytical software, modern SEM/EDS\n  The capability of Si(Li)-EDS to perform quantitative    microanalysis practice has developed along a  different\nX-ray microanalysis was established soon after its intro-    trajectory that minimizes the need for the user\u2019s expertise.\nduction by several members of the microanalysis commu-   As an unintended consequence, EDS microanalysis as\nnity, most  of whom had  extensive WDS  quantitative    performed in the SEM has acquired an unfortunate repu-\nmicroanalysis experience [7\u201311]. Thus, the  initial EDS    tation as a \u2018\u2018semi-quantitative\u2019\u2019 technique. This situation\nimplementation of quantitative analysis was based upon    has developed because of three contributing factors: (1) the\ntheir experience with the WDS k-ratio protocol. The EDS     rise of standardless analysis which now dominates EDS\ncould be used in an equivalent manner by measuring the    quantitative analysis [14]; (2) the severe effects of speci-\nintensities  for  the unknown and  appropriate  standards   men geometry on the accuracy of X-ray microanalysis\nunder the same carefully controlled conditions of surface    which occur no matter which analytical protocol is fol-\ncondition (highly polished), beam energy, known dose    lowed, standards-based or standardless [15]; and (3) the\n(beam current 9 detector live time), beam incidence angle,    occasional but signi\ufb01cant failures in qualitative analysis,\ndetector elevation angle (\u2018\u2018take-off angle\u2019\u2019), and detector      i.e., incorrect elemental identi\ufb01cation, which immediately\nef\ufb01ciency (e.g., constant detector-to-target distance to yield    undermines con\ufb01dence in the method [16\u201318].\nconstant detector solid angle). The enormous advantages of\nthe EDS over WDS for analysis were quickly recognized:   The rise of \u2018\u2018standardless\u2019\u2019 quantitative analysis\n(1) all elements in the unknown were measured simulta-\nneously minimizing the dose to the specimen; (2) the large   By necessity, WDS measures each element in the sample\nsolid angle of the EDS relative to WDS further improved     relative to the same element in an appropriate standard to\nef\ufb01ciency of detection which lowered the necessary dose\nrelative to WDS; and (3) the stability of the EDS meant\n                                                                                2 Materials analyzed in this paper include NIST Standard Reference\nthat the spectra of standards could be archived and recalled\n                                                                           Materials, NIST microanalysis research materials (glasses), natural\nas needed. Since the measured EDS spectrum consists of     minerals, and stoichiometric compounds con\ufb01rmed to be homoge-\nthe characteristic X-ray peaks superimposed on the X-ray    neous on a micrometer lateral scale.\n\n                                  123496                                                                                                                  J Mater Sci (2015) 50:493\u2013518\n\n\nTable 1 Si(Li)-EDS analysis of NIST Standard Reference Material 482 Copper\u2013Gold Alloysa (all concentration values in mass fraction)\n\nCu (certi\ufb01ed)        Analyzed              Rel. error (%)      Au (certi\ufb01ed)        Analyzed              Rel. error (%)        Total\n\n0.198               0.198 \u00b1 0.002           0.0                0.801               0.790 \u00b1 0.002       -1.4                0.988\n\n0.396               0.399 \u00b1 0.001           0.8                0.603               0.594 \u00b1 0.002       -1.6                0.993\n\n0.599               0.605 \u00b1 0.001           1.0                0.401               0.402 \u00b1 0.002        \n\n## 2. newbury2015performingelementalmicroanalysis pages 17-20 (Context ID: pqac-00000042)\n\nfeatureless background\npeaks are separated by 4 eV. The results of k-ratio protocol    under the composite peaks. Figure 17b demonstrates that\nanalysis of seven replicates with DTSA-II are also pre-   when peak \ufb01tting is performed without including a peak\nsented in Table 11, using elemental Ti and the mineral    reference for Ti, the TiKa and TiKb peaks can be recog-\nsanbornite (BaSi2O5)  for Si and Ba as references and    nized in the residuals. This example illustrates that com-\nstandards, with O calculated by assumed stoichiometry.    prehensive analysis of an unknown must be performed\nAfter quanti\ufb01cation with DTSA-II, the relative errors are     iteratively. In  the  \ufb01rst round,  qualitative  analysis  \ufb01rst\nless than 2.5 % for all measured constituents.                 identi\ufb01es with high con\ufb01dence the major constituents and\n\n\n                                  123510                                                                                                                  J Mater Sci (2015) 50:493\u2013518\n\n\n\n\n\n                                               SrWO4\n                                                              E0 = 10 keV\n                                                                         Fi  ng with SrF2 and W\n                                      O by stoichiometry\n\n\n\n\n\nFig. 15 SDD-EDS spectrum of SrWO4 at a beam energy of E0 = 10 keV (red); residual spectrum (blue) after peak \ufb01tting with SrF2 and W\n(Color \ufb01gure online)\n\n\nTable 9 NIST DTSA-II SDD-EDS analysis of SrWO4 at E0 = 10 keV; SrF2 and W as references and standards; O by stoichiometry; 15\nreplicates\n\nParameter              Raw analytical total        O (atomic conc.,             Sr (atomic conc.)      W (atomic conc.)\n                           (mass concentration)          by stoichiometry)\n\nMean                       1.0017                        0.6660                     0.1678                     0.1661\n\nRelative error (%)                                     -0.10                       0.68                     -0.33\nr                          0.0019                        0.00053                    0.00065                    0.00033\nr relative (%)                0.19                           0.80                        0.39                        0.20\n\n                                   O (mass conc.)                Sr (mass conc.)       W (mass conc.)\n\nSingle analysis                     1.0029               0.1913                       0.2627                       0.5489\n\nRelative error (%)                                         0.27                          0.58                          0.16\n\nk error (%)                                                                               0.0007, 0.27                   0.0009, 0.16\n\nA-factor error (%)                                                                        0.0093, 3.5                    0.0077, 1.4\n\nZ-factor error (%)                                                                2.7E-5, 0.010               5.8E-5, 0.011\n\nCombined errors (%)                                                                      0.0093, 3.5                    0.0078, 1.4\n\n\n\nany well-resolved minor and trace constituents present.     The residual spectrum can also be used to estimate\nAfter peak \ufb01tting and quantitative analysis for those ele-    limits of detection for trace constituents of interest, and the\nments are performed, careful examination of the residual    analytical strategy can be modi\ufb01ed if necessary to lower\nspectrum with those peaks stripped off may reveal previ-    the limit of detection by accumulating more counts.\nously unrecognized minor and trace constituents hidden\nunder the higher intensity peaks. In the second round, the    Quantifying a trace constituent with severe interference\nfull analysis is then repeated, including the newly recog-    from a major constituent\nnized minor/trace constituents. If inspection of the latest\nresiduals reveals no new peaks, the analysis can be con-   NIST microanalysis glass K873, the spectrum of which is\nsidered complete.                                   shown  in  Fig. 18 and whose composition  is  listed  in\n\n123J Mater Sci (2015) 50:493\u2013518                                                                                        511\n\n\n\n                                               WSi 2\n                                                             E0 = 10 keV\n                                                                        Fi  ng with Si and W\n\n\n  Counts\n\n\n\n\n\n                                             photon Energy (kev)\n\nFig. 16 SDD-EDS spectrum of WSi2 at a beam energy of E0 = 10 keV (red); residual spectrum (blue) after peak \ufb01tting with Si and W (Color\n\ufb01gure online)\n\n\nTable 10 NIST  DTSA-II  SDD-EDS   analysis   of  WSi2   at    Ba, Al2O3 for Al, CeO2 for Ce, PbTe for Pb, and with O\nE0 = 10 keV; Si and W as references and standards; 12 replicates      calculated by assumed stoichiometry. The relative errors in\nParameter        Raw analytical total   Si (atomic W (atomic    the trace constituents are 20 % for Ce and -20 % for Ta,\n                   (mass concentration)   conc.)       conc.)       which might be further reduced by accumulating higher\n                                                               counts.\nMean              0.9801               0.6615      0.3385\n\nRelative error (%)                      -0.78       1.55\n                                                             Quantitative X-ray microanalysis of low atomic number\nr                  0.0057               0.0011      0.0011\n                                                          elements\nr relative (%)       0.58                  0.17        0.33\n\n                                 Si (mass conc.)  W (mass conc.)    Quantitative electron-excited X-ray microanalysis of the\n                                                   low atomic number elements, including C, N, O, and F that\nSingle analysis        0.9894   0.2262           0.7632\n                                                       can only be measured with X-ray peaks whose energies fall\nRelative error (%)             -3.4           -0.36\n                                                    below 1 keV, has presented a great challenge since the\nk error (%)                      0.0002, 0.088     0.0005, 0.066\n                                                                       earliest years of the electron-excited X-ray microanalysis\nA-factor error (%)               0.0002, 0.088     0.0047, 0.62\n                                                           technique [2]. When measured with wavelength-dispersive\nZ-factor error (%)             6.6E-6, 0.0029   0.0002, 0.026\n                                                             spectrometry, the low-energy photon peaks are subject to\nCombined errors (%)            0.00028, 0.13     0.0047, 0.62\n                                                               the so-called \u2018\u2018chemical effects\u2019\u2019 manifested as shifts in the\n                                                       X-ray peak position and changes in peak shape that depend\n                                                   on chemical binding. These effects have been described in\nTable 12, features two examples of interference of a major     detail in the classic series of papers by Bastin and Heiligers\nconstituent upon a trace constituent: Ba (concentration    [26], who developed a \u2018\u2018peak-shape\u2019\u2019 factor correction to\n0.219 mass fraction) on Ce (0.0041) (Ba/Ce = 53/1) and Si    compensate for chemical shifts that signi\ufb01cantly affected\n(0.115) on Ta (0.0041) (Si/Ta = 28/1). The BaLb1 and   \ufb01xed peak-channel WDS measurements. The low-Z spec-\nCeLa peaks are separated by 12 eV, while the BaLb2 and    trum measurement problem is further complicated by peak\nCeLb1 peaks are separated by 106 eV. The SiKa  falls    interferences that often arise from the L-, M-, and N-family\nbetween the TaMa (-30 eV) and the TaMb (26 eV). The    X-rays of heavier elements that occur throughout this low\nresults of k-ratio protocol analysis of seven replicates with    photon energy range. Because of the signi\ufb01cantly poorer\nDTSA-II are also presented in Table 12, using as standards    spectral resolution of EDS compared to WDS and the\nelemental Mn and Ta, with sanbornite (BaSi2O5) for Si and    consequent impact of interfering peaks, direct quantitative\n\n\n                                  123512                                                                                                                  J Mater Sci (2015) 50:493\u2013518\n\n\n                   Minor element (0.01\u2264 C \u2264 0.1) quantification with major element (C > 0.1) overlap\n\n (a)                                                               K2496 glass\n                                                                                 E0 = 10 keV\n                                                                   1000 nA-s\n              K2496\n               \n\n## 3. newbury2019electronexcitedxraymicroanalysis pages 13-15 (Context ID: pqac-00000043)\n\n          Concentration)            Concentration)              Concentration)\n\n\n        Mean                        0.9823                    0.3197               0.2256                    0.0176                   0.4371\n\n          As-synthesized                                         0.3230               0.2291                    0.0180                   0.4299\n\n        RDEV (%)                                          \u22121.0                \u22121.5                    \u22122.2                         1.7\n\n        \u03c3 (seven                                              0.000049             0.00028                  0.00031                  0.00058\n           replicates)\n\n        \u03c3 relative (%)                                           0.008                 0.13                        1.8                       0.13\n\n         k uncertainty                                                                    0.0001, 0.044%            0.0003, 1.7%              0.0007, 0.16%\n\n           A-factor                                                                          0.0015, 0.66%             0.0000039, 0.022%        0.000019, 0.0044%\n          uncertainty\n\n           Z-factor                                                                       0.000011, 0.0049%        0.0000003, 0.0014%       0.00000021, 0.000048%\n          uncertainty\n\n        Combined                                                                       0.0015, 0.66%              0.0003, 1.7%              0.0007, 0.16%\n          uncertainty\n\n\n\n      the lateral resolution and reducing the sampling depth (Goldstein   Microanalysis of Trace Elements\n       et al., 2018). However, to excite a particular characteristic X-ray\n                                                             Measurement of trace elements, arbitrarily defined in this paper\n      peak, the beam energy must exceed the critical shell excitation\n                                                                            as those present at a mass concentration C < 0.01, involves fitting\n       energy, Ec, ideally by a factor of at least 1.25. This condition places                                                                   peaks that are close to the X-ray continuum background and that\n       practical constraints on the selection of E0. A beam energy of                                                     may also be subject to overlap from the significantly more\n      5 keV  is the lowest value at which at least one characteristic\n                                                                         intense peaks of major and minor constituents. In the absence\n      X-ray peak or family can be excited for  all elements of the                                                                            of significant peak overlap, limits of detection in the range\n       Periodic Table, except for H and He which do not produce char-                                                                   0.0002\u20130.0005 mass concentration (200\u2013500 parts per million),\n        acteristic X-rays. As the beam energy is reduced below 5 keV, an                                                                depending  on  the   particular  element  and  the  matrix\n       increasing number of elements becomes inaccessible to EPMAdue   composition, can be reached with counting times below 500 s\n       to the lack of a practically measurable characteristic X-ray peak   (Newbury &  Ritchie,  2016b). An  example   is  shown  in\n     (Newbury & Ritchie, 2016a). Even with the selection of E0 =    Figure 10 for NIST microanalysis glass K523, which has the\n      5 keV, the analyst is forced to make use of unfamiliar X-ray fam-    as-synthesized composition listed in Table 22. For peaks that\n         ilies for some elements. For example, Ba is typically analyzed with   do not suffer interference, CDL, the limit of detection (minimum\n      the Ba L-family X-rays (L3 = 5.247 keV), but this family is not   mass fraction) can be estimated from the measured (or indepen-\n       available with E0 \u22645 keV, requiring the use of the Ba M-family,    dently known) composition as\n      which is illustrated in Figure 9a. A difficult low beam energy anal-\n        ysis involving the Ba M-family is presented in Figure 9b, which\n                                                                         CDL = [3NB1/2/(NS \u2212NB)]CS,               (6)      shows the spectrum for YBa2Cu3O7 and the peak-fitting residual.\n      This analysis involves interference of the O K-L2,3 family and the\n     Cu L-M family with the Ba M-family. The results, including oxy-   where NB is the number of counts in the background under the\n      gen analyzed with a standard, are presented in Table 21, where the   peak (integral across the contiguous channels that define the\n       largest RDEV is 6.5% relative for Y. Ba, despite the severe interfer-    peak), NS is the number of counts in the peak integral, and CS\n      ence of the O K-L2,3 family and the Cu L-M family, is analyzed     is the known (or measured) concentration of the trace constitu-\n      with an RDEV of 0.5%. Additional challenges that become signif-   ent (Goldstein et al., 2018). For the particular measurement con-\n       icant at low beam energy include the stratified nature of most    ditions listed in Table 22, the values of CDL estimated with\n       materials. Native oxides and other surface layers make a more sig-   equation (6) are listed for several of the trace constituents.\n       nificant contribution to the measured spectrum at low incident     An example of trace measurements at the extreme limit of EDS\n     beam energy compared with the measurement at conventional    microanalysis (spectrum integral 0.1\u201320 keV = 1.7 billion counts)\n     beam energies, where the surface layer comprises only a small     is presented in Figure 11, which shows the spectrum of NIST\n       fraction of the total electron range. Contamination from carbon  SRM 610 (\u201cTrace Elements  in Glass\u201d) containing numerous\n      deposition can increase the absorption of X-rays with energies    trace elements at a nominal level of 0.0005 mass fraction (500\n      near the carbon K-edge (0.284 keV) above that expected from    parts per million) in a matrix of O\u2013Na\u2013Al\u2013Si\u2013Ca. There are\n      the compositions of the unknown and standard. While this effect   many peak interference situations encountered in the analysis of\n       also occurs for conventional beam energy analysis, the analytical  SRM 610, but those that involve mutual interferences of trace\n       strategy can usually make use of more energetic characteristic    constituents that produce peaks of similar intensity, e.g., the Ti\n      X-ray peaks that are much less affected by absorption from the   K-family and the Ba L-family, can be solved with peak fitting.\n      contamination layer.                                            Table 23 gives the results of the DTSA-II analysis. With some\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X     14                                                                                 Dale E. Newbury and Nicholas W.M. Ritchie\n\n\n\n\n\n        Fig. 8. EDS spectrum of an inclusion in NIST SRM 168 (E0 = 20 keV) for the photon energy range from 0 to 10 keV: (a) full spectrum with a linear intensity axis; (b) full\n      spectrum with a logarithmic intensity axis; (c) spectrum and peak fitting residual spectrum (blue) after fitting for Ti, Cr, Fe, Co, Nb, and Ta; (d) expansion 0\u20135 keV\n      showing the detection of the W M-family in the peak fitting residual spectrum; and (e) original spectrum (green) and comparison of second (red) and third (blue)\n      peak fitting residual spectra, showing the detection of Mo L-family. Note that where the red and blue traces overlap exactly, the red spectrum dominates the display.\n\n      exceptions, e.g., Cu, the EDS results are consistent with the bulk    When the X-ray peak for a trace constituent is buried under\n      analysis  values reported  for  this SRM (Newbury &  Ritchie,    the interfering peak of a major or minor constituent, the measure-\n     2016b).                                                ment challenge  is substantially increased. Moreover, there are\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X      Microscopy and Microanalysis                                                                                          15\n\n\n\n\n\n         Fig. 8. Continued.\n\n\n\n       Table 15. Analysis of an Inclusion in SRM 168 (E0 = 20 keV) Pure Element Standards.\n\n                                Analytical\n     \n\n## 4. newbury2019electronexcitedxraymicroanalysis pages 15-16 (Context ID: pqac-00000044)\n\ntchie,    the interfering peak of a major or minor constituent, the measure-\n     2016b).                                                ment challenge  is substantially increased. Moreover, there are\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X      Microscopy and Microanalysis                                                                                          15\n\n\n\n\n\n         Fig. 8. Continued.\n\n\n\n       Table 15. Analysis of an Inclusion in SRM 168 (E0 = 20 keV) Pure Element Standards.\n\n                                Analytical\n         SRM168_Inclusion     Total        C           Ti         Cr         Fe       Co         Ni       Nb         Mo        Ta     W\n\n\n            First analysis        0.9325 \u00b1     0.0696 \u00b1    0.0495 \u00b1    0.0120 \u00b1    0.0011 \u00b1    0.0144 \u00b1    0.0086 \u00b1    0.5733 \u00b1                   0.2040 \u00b1\n                               0.0083      0.0074     0.0002     0.0001     0.0001     0.0002     0.0002     0.0036                   0.0009\n\n        Second analysis      1.001 \u00b1     0.0751 \u00b1    0.0502 \u00b1    0.0121 \u00b1    0.0011 \u00b1    0.0144 \u00b1    0.0086 \u00b1    0.6012 \u00b1                   0.2051 \u00b1     0.0328 \u00b1\n                               0.0092      0.0079     0.0002     0.0001     0.0001     0.0002     0.0002     0.0040                   0.0011       0.0022\n\n          Third analysis        1.014 \u00b1     0.0763 \u00b1    0.0503 \u00b1    0.0121 \u00b1    0.0011 \u00b1    0.0144 \u00b1    0.0086 \u00b1    0.6061 \u00b1        0.0073 \u00b1   0.2053 \u00b1     0.0329 \u00b1\n                               0.0094      0.0081     0.0002     0.0001     0.0001     0.0002     0.0002     0.0040          0.0005   0.0011       0.0022\n\n\n\n       Table 16. Analysis of Binary Fluorides [All Analyses Performed with E0 = 10 keV and the K-L2,3 Peak (Na and Ca), L3-M4,5 Peak (Sr, Ba, and La), M5-N6,7 (Pr and Nd)].\n\n                          Fmean (Atom        RDEV        \u03c3 (Seven         Relative \u03c3        Metalmean (Atom       RDEV        \u03c3 (Seven            \u03c3Relative\n          Fluoride        Concentration)         (%)          Replicates)          (%)            Concentration)          (%)          Replicates)         (%)\n\n        NaF                0.5143               2.9          0.00069            0.13                0.4857             \u22122.9          0.00069           0.14\n\n         CaF2               0.6686               0.29         0.00074            0.11                0.3314             \u22120.57         0.00074           0.22\n\n          SrF2                0.6611            \u22120.83         0.00021           0.032               0.3389               +1.7          0.00021           0.062\n\n         BaF2               0.6527            \u22122.1          0.00152            0.23                0.3473               +4.2          0.00152           0.44\n\n         LaF3               0.7600               1.3          0.00283            0.37                0.2400             \u22124.0          0.00283            1.2\n\n          PrF3               0.7825               4.3          0.00267            0.34                0.2175          \u221213            0.00267            1.2\n\n        NdF3               0.7526               0.35         0.0139             1.8                 0.2474             \u22121.1          0.0139             5.6\n\n\n\n        relatively few materials of known composition with such major/    to 1,000:1, the k-ratio for the trace constituent is recovered with\n     minor  interferences on  trace  constituents  that can  serve  as   an RDEV of 26% for U in a Th-matrix and \u22129.4% for Th in a\n     unknowns to test the performance of peak fitting in such situa-   U-matrix. Figure 12 shows the spectra for the U-matrix with Th\n       tions. As an  alternative,  the \u201cspectrum  arithmetic\u201d  tools  in    additions. When Th  is not included in the peak fitting suite,\n     NIST DTSA-II can be used to create suitable synthesized compos-    the peak fitting residual spectra visually reveal the Th constituent\n        ite spectra from experimentally measured spectra. The synthe-   down to the 1% level. Figure 13 shows the same sequence for the\n       sized spectra are then subjected to peak fitting using different   Th-matrix with U additions, and again when U is not included in\n      experimentally measured spectra as peak references. Examples    the peak fitting suite, the peak fitting residual spectra visually\n       of such studies are presented in Table 24 for the interference of    reveal the U constituent down to the 1% level.\n      the Th M-family and the U M-family for which Th M4-N6\n      (3.146 keV) and U M5-N6,7 (3.165 keV) families are separated                                                                   \u201cStandardless\u201d Analysis\n      by 19 eV at photon energy where the EDS resolution is 99 eV.\n      For an intensity ratio of 100:1, the k-ratio for the trace constituent    \u201cStandardless\u201d analysis avoids the need to measure a standard\n         is recovered with an RDEV of 2% for U in a Th-matrix and \u22121.1%    intensity for the denominator of the k-ratio in equation (4) either\n       for Th in a U-matrix. When the relative intensity ratio is increased   by calculating an intensity from the equations of X-ray generation\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X     16                                                                                 Dale E. Newbury and Nicholas W.M. Ritchie\n\n\n      Table 17. Analysis of Binary Oxides (All Analyses Performed with E0 = 10 keV and the K-L2,3 Peak, except for Zn L3-M4,5 and Y L3-M4,5).\n\n                     Omean (Atom        RDEV        \u03c3 (Seven          Relative \u03c3        Metalmean (Atom       RDEV        \u03c3 (Seven             \u03c3Relative\n        Oxide        Concentration)         (%)          Replicates)          (%)            Concentration)          (%)          Replicates)          (%)\n\n      MgO             0.4966            \u22120.68          0.00064             0.13                0.5034              +0.67          0.00064            0.13\n\n         Al2O3            0.5905            \u22121.6           0.00039             0.07                0.4095              +2.4           0.00039            0.10\n\n        SiO              0.4989            \u22120.20          0.00033             0.07                0.5011              +0.20          0.00033            0.07\n\n        SiO2             0.6568            \u22121.5           0.00030             0.05                0.3432              +3.0           0.00030            0.09\n\n        TiO2             0.6702             +0.54          0.0011              0.16                0.3297             \u22121.1           0.0011             0.32\n\n        Cr2O3            0.5962            \u22120.64          0.0117              2.0                 0.4038              +0.95          0.0117              2.9\n\n        Fe2O3            0.5988            \u22120.20          0.00068             0.11                0.4012              +0.30          0.00068            0.17\n\n       Cu2O             0.3292            \u22121.2           0.00069             0.21                0.6708              +0.62          0.00069            0.10\n\n      CuO             0.5065             +1.30          0.0022              0.44                0.4935             \u22121.3           0.0022             0.45\n\n       ZnO             0.4905            \u22121.90          0.0058              1.2                 0.5095              +1.10          0.0058             1.10\n\n        Y2O3             0.5998            \u22120.04          0.00071             0.12                0.4002              +0.05          0.00071            0.18\n\n\n\n      Table 18. Analysis of Binary Nitrides [All Analyses Performed with E0 = 5 keV (ZrN at 10 keV); K-L2,3 Peak for B, Al, and Si; All others L-Family].\n\n                      Nmean (Atom        RDEV        \u03c3 (Seven         Relative \u03c3        Metalmean (Atom       RDEV        \u03c3 (Seven            \u03c3Relative\n         Nitride        Concentration)         (%)          Replicates)          (%)            Concentration)          (%)          Replicates)         (%)\n\n      BN                0.5202                4.0           0.0085              1.6                 0.4798            \u22124.0           0.0085             1.8\n\n        AlN               0.4784            \u22124.3           0.0024             0.50               0.5216                4.3           0.0024            0.46\n\n         Si3N4             0.5857              +2.5           0.0036             0.61               0.4143            \u22123.3           0.0036            0.86\n\n        TiN               0.5098              +2.0           0.0016             0.31               0.4902            \u22122.0           0.0016            0\n\n## 5. newbury2019electronexcitedxraymicroanalysis pages 16-18 (Context ID: pqac-00000045)\n\ntration)         (%)          Replicates)          (%)            Concentration)          (%)          Replicates)         (%)\n\n      BN                0.5202                4.0           0.0085              1.6                 0.4798            \u22124.0           0.0085             1.8\n\n        AlN               0.4784            \u22124.3           0.0024             0.50               0.5216                4.3           0.0024            0.46\n\n         Si3N4             0.5857              +2.5           0.0036             0.61               0.4143            \u22123.3           0.0036            0.86\n\n        TiN               0.5098              +2.0           0.0016             0.31               0.4902            \u22122.0           0.0016            0.32\n\n       VN                0.5118              +2.4           0.0051              1.0                 0.4882            \u22122.4           0.0051             1.0\n\n        Cr2N              0.3322            \u22120.33          0.0046              1.4                 0.6678              +0.17          0.0046            0.69\n\n        Fe3N              0.2573              +2.9           0.0069              2.7                 0.7427            \u22121.0           0.0069            0.93\n\n      GaN              0.4717            \u22125.7           0.0020             9.43               0.5283              +5.70          0.0020            0.38\n\n       ZrN               0.4959            \u22120.82          0.0033             0.66               0.5041               0.82          0.0033            0.65\n\n\n\n      Table 19. Analysis of Binary Carbides [Analyses Performed with the K-L2,3 Peak (E0 = 10 keV) or L-Family for Hf (E0 = 5 keV)].\n\n                                                  \u03c3 (Five or                                                   \u03c3 (Five or\n                     Carbonmean (Atom      RDEV          More           Relative \u03c3       Metalmean (Atom      RDEV          More               \u03c3Relative\n        Carbide        Concentration)         (%)          Replicates)          (%)           Concentration)         (%)          Replicates)          (%)\n\n         SiC            0.5112 \u00b1 0.3925           2.2           0.0004              0.07          0.4888 \u00b1 0.0002        \u22122.2           0.0004             0.07\n\n         TiC            0.4897 \u00b1 0.0477        \u22122.1           0.0008              0.16          0.5103 \u00b1 0.0005           2.1           0.0008             0.16\n\n       VC             0.4963 \u00b1 0.2517        \u22120.7           0.0017              0.33          0.5037 \u00b1 0.0006           0.7           0.0017             0.33\n\n         Cr3C2          0.3925 \u00b1 0.2127        \u22121.9           0.0029              0.73          0.6075 \u00b1 0.0008           1.3           0.0029             0.47\n\n         Cr7C3          0.2960 \u00b1 0.1608        \u22122.0           0.0097              3.3           0.7059 \u00b1 0.0009          0.84          0.0098              1.4\n\n         Cr23C6         0.2086 \u00b1 0.1143          0.82          0.0057              2.7           0.7914 \u00b1 0.0010          0.21          0.0057             0.72\n\n        Fe3C           0.2531 \u00b1 0.1572           1.2           0.00073            0.29          0.7469 \u00b1 0.0015          0.41          0.00073            0.10\n\n        HfC            0.4742 \u00b1 0.0121        \u22125.2           0.00272            0.57          0.5258 \u00b1 0.0006           5.2           0.00272            0.52\n\n\n\n    and propagation (\u201cfirst-principles\u201d method) or by using a library    fluorescence yield, especially for L- and M-shell X-rays. Since\n      of remotely measured standards (\u201cremote standards\u201d method)    the remote standards method  is tied to measurements of real\n     (Goldstein  et  al., 2018). The accuracy  of the  first-principles    materials, it is inherently more accurate and is a good compro-\n    method is limited by the lack of accurate values for critical phys-   mise between first-principles standardless analysis and locally col-\n       ical parameters such as the ionization cross section and the    lected standards-based analysis. However, the user is often left\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X      Microscopy and Microanalysis                                                                                          17\n\n\n       Table 20. Analysis of Binary Borides (All Analyses Performed with E0 = 5 keV; B K-L2,3 Peak, C K-L2,3 Peak, Ti and Cr L-Family, and La M-Family Peaks).\n\n                                                  \u03c3 (Five or                                                    \u03c3 (Five or\n                      Boronmean (Atom      RDEV          More            Relative \u03c3       Metalmean (Atom       RDEV          More               \u03c3Relative\n         Boride        Concentration)         (%)          Replicates)          (%)           Concentration)         (%)          Replicates)          (%)\n\n         B4C           0.7744 \u00b1 0.1104        \u22123.2           0.0033              0.43           0.2256 \u00b1 0.1240       13              0.0033              1.5\n\n          TiB2          0.6609 \u00b1 0.1887        \u22120.87          0.0043              0.65           0.3391 \u00b1 0.0003         1.7             0.0043              1.3\n\n         CrB2          0.6552 \u00b1 0.5276        \u22121.7           0.00092             0.14           0.3448 \u00b1 0.0034         3.5             0.00092            0.27\n\n         CrB           0.4913 \u00b1 0.4563        \u22121.7           0.0055               1.1            0.5087 \u00b1 0.0028         1.7             0.0055              1.1\n\n         Cr2B          0.3362 \u00b1 0.3283          0.86          0.0047               1.4            0.6638 \u00b1 0.0026       \u22120.42          0.0047             0.70\n\n         LaB6          0.8702 \u00b1 0.2183           1.5           0.00063             0.07           0.1298 \u00b1 0.0012      \u22129             0.00063            0.49\n\n\n\n\n\n         Fig. 9. (a) EDS spectrum of BaCl2 at E0 = 5 keV; note the extended Ba M-family. (b) EDS spectrum (red) of YBa2Cu3O7\u2212x at E0 = 5 keV and the peak fitting residual\n       spectrum (blue).\n\n\n\n\n       Table 21. Analysis of YBa2Cu3O7 at E0 = 5 keV. O (Y2O3 Standard and Reference); Cu (Standard and Reference); Y (Y2O3 Standard and Reference); Ba (BaF2 Standard\n      and BaCl2 Reference), Values in Normalized Mass Concentration; Combined Uncertainties as Estimated from NIST DTSA-II.\n\n                         Raw Analytical Total (Mass         O (Mass             Cu (Mass                Y (Mass              Ba (Mass\n         Parameter                    Concentration)               Concentration)           Concentration)           Concentration)           Concentration)\n\n\n        Mean                  1.026                                    0.1627                  0.2983                   0.1248                  0.4143\n\n          Ideal                                                          0.1681                  0.2862                   0.1335                  0.4123\n\n        RDEV (%)                                                  \u22123.2                        4.2                   \u22126.5                        0.5\n\n        \u03c3 (five replicates)                                               0.0022                  0.0040                   0.0019                  0.0076\n\n        \u03c3 relative (%)                                                       1.3                        1.3                        1.5                        1.8\n\n        Combined                                                       \u00b10.0013,                  \u00b10.0052,                  \u00b10.0004,                  \u00b10.0053,\n          uncertainty                                              \u00b10.8%                 \u00b11.7%                \u00b10.32%                \u00b11.3%\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X     18                                                                                 Dale E. Newbury and Nicholas W.M. Ritchie\n\n\n\n\n\n        Fig. 10. EDS spectrum of NIST microanalysis glass K523 (E0 = 20 keV): upper, 0\u201315 keV; lower, 0\u201310 keV with an expanded intensity axis.\n\n\n     guessing how vendors implement their \u201cstandard-less quantifica-    corrected. One method is to use a \u201cgolden detector\u201d calibrated\n      tion\u201d because they have typically not provided the customer with    at a beamline and a carefully chosen reference material to trans-\n     adequate documentation on what is actually being done to derive    fer the calibration from the golden detector to others (Alvisi\n     numerical concentrations.                                                et al., 2006).\n       The remote standards library is populated with characteristic       Standardless analysis requires only\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045]\n\nStatus: Paper Count=23 | Relevant Papers=14 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=46 | Current Cost=$0.2376 | Disease-Target Evidence=0",
+                "name": "read_text",
+                "tool_call_id": "toolu_014Vv5PkK6B2RGN1hC6sSaDS",
+                "info": {
+                  "start_ts": 2919.501040849,
+                  "end_ts": 2934.070308387
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me read the dead-time model more carefully and search for the Donovan dead time paper and more Goldstein:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01UCKP9WxxM8PsBoLzYdzVrc",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"text_name_list\": [\"goldstein2018energydispersivexray pages 9-10\", \"donovan2023anewmethod pages 2-3\", \"donovan2023anewmethod pages 3-4\", \"donovan2023anewmethod pages 4-5\"]}",
+                      "name": "read_text"
+                    }
+                  },
+                  {
+                    "id": "toolu_01GLLGDKo7sADfUGLPZF3SS8",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"question\": \"What is the Bethe ionization cross-section formula? How does ionization cross-section Q vary with overvoltage U = E0/Ec? Where is the maximum of the ionization cross-section and why does it determine the optimal accelerating voltage? What is the Kanaya-Okayama electron range equation?\"}",
+                      "name": "gather_evidence"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "## 1. goldstein2018energydispersivexray pages 9-10 (Context ID: pqac-00000046)\n\n Level of System Dead-Time\nbins will define an X-ray peak. Since the peak width is a func-   X-rays are generated randomly in time with an average rate\ntion of photon energy, as described by Eq. (16.2), decreasing  determined by the flux of electrons striking the specimen,\nfrom approximately 129 eV at Mn K-L3 (5.895 keV) to   thus scaling with the incident beam current. As discussed\napproximately 50 eV FWHM for C K-L2 (0.282 keV), a selec-   above, the EDS system can measure only one X-ray photon at\ntion of a 5-eV bin width is a useful choice to optimize peak   a time, so that it is effectively unavailable if another photon\nfitting since this choice will provide 10 channels across C   arrives while the system is \u201cbusy\u201d measuring the first photon.\nK-L2. The number of bins that comprise the spectrum multi-  Depending on the separation in the time of arrival of the sec-\nplied by the bin width gives the energy span. It is useful to  ond photon, the anti-coincidence function will exclude the\ncapture the complete energy spectrum from a threshold of  second photon, but if the measurement of the first photon is\n0.1 keV to the incident beam energy, E0. Thus, to span   not sufficiently advanced, both photons will be excluded\n0\u201320 keV with 5 eV bins requires 4096 channels.            from the measurement and effectively lost. Due to this pho-\n                                                        ton loss, the output count rate (OCR) in counts/second of the\nChoosing the Solid Angle of the EDS                                                              detector will always be less than the input count rate (ICR).\nThe solid angle \u03a9 of a detector with an active area A at a dis-  The relation between the OCR and ICR is shown in .\u2003 Fig. 16.9\ntance r from the specimen is                                    for a four-detector SDD-EDS. An automatic correction func-\n                                                              tion measures the time increments when the detector is busy\n    W = A / r 2                                           (16.4)   processing photons, and to compensate for possible photon\n                                                                    loss during this \u201cdead-time,\u201d additional time is added at the\n                                                          conclusion of the user-specified measurement time so that all\n\n. .\u200a\u200a\u200aFig. 16.9\u2003  Output count rate\nversus input count rate for a four-                               Quad SDD (medium peaking time)\ndetector SDD-EDS\n                                       1,000,000                                                               80\n                                  Mn\n                           OCR           E0 = 20 keV\n                                                                                                         70                                      SDD 470 ns\n                                                shaping                                       800,000\n                                                time\n                                                                                                         60\n                                                                                           Single SDD\n                                                                 Maximum = 130 kcps\n                                                                                                         50\n                                       600,000                                550 kHz\n                                                                       (c/s)\n                                                         rate                                                 127.5 eV at MnK\u03b1              40                                                                                                                                                                                                                                                                                                                                                                                                         Deadtime\n                                       400,000                                                                       Count                                                ICR (c/clock-s)                  30\n\n                                                                 OCR (Medium)\n                                                                                                         20\n                                       200,000\n                                                                            Deadtime\n                                                                                                         10\n                                                         Single SDD chip: maximum output ~ 130 kHz\n\n                                         0                                                               0\n                                           0       500 kHz     1MHz        1.5 MHz    2 MHz    2.5 MHz\n                                                                              Input count rate           218    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n         measurements are made on the basis of the same \u201clive-time\u201d  time over the full dead-time range to 80\u2009% or higher. (Note\n          so as to achieve constant dose for quantitative measurements.   that as a component of a quality measurement system, the\n         The level of activity of the EDS is reported to the user as a  dead-time  correction  function  should  be  periodically\n          percentage \u201cdead-time\u201d:                                  checked by systematically changing the beam current and\n                                                             comparing the measured X-ray intensity with predicted.)\n                                                                          (16.5)  However, as the dead-time increases and the arrival rate of               Deadtime ( % ) = \uf8ee\uf8f0 ( ICR \u2212 OCR ) / ICR \uf8f9\uf8fb\u00d7 100%\n                                                                   X-rays at the EDS increases, coincidence events become\n         Dead-time increases as the beam current increases. The   progressively more prominent. This effect is illustrated in\n         dead time correction circuit can correct the measurement   .\u2003 Fig. 16.10 for a sequence of spectra from a glass with six\n\n\n\n               140 000                                             K412\n                                                                             E0 = 20 keV                  K412 (mass frac)\n               120 000                                   7% deadtime             O            0.428\n                                                                       Mg          0.117\n               100 000                                                                                        Al           0.0491\n                                                                                                                                     Si           0.212\n                80 000                                                                      Ca           0.109                                  Counts                                                                                                  Fe           0.0774\n\n                60 000\n\n\n                40 000\n\n\n                20 000\n\n\n                    0\n                      0                   2                  4                  6                   8                  10\n                                                           Photon energy (keV)\n\n\n                                             Coincidence               Coincidence\n               14 000                                           peaks                    peaks\n\n\n\n\n                   K16           12 000\n                                                                                            K-L                               V        CrK-L                                       NaK                          SiK+O\n               10 000                                                                                                   not                                       not                         2MgK     2AlK   2SiK               not\n             K                                                                 K412 (mass frac)\n                8 000       2O\n                                         20DT                                     O           0.428                                  Counts\n                                                                           Mg          0.117                                                                                                                                                                                                                       \n\n## 2. donovan2023anewmethod pages 3-4 (Context ID: pqac-00000047)\n\ne values of our dead time constants when utilizing\nsion which should be utilized if count rates exceed 100 to                                                                      of\n                                                                 these more precise dead time models, to account for improved\n200 kcps (depending on the exact value of the dead time con-\n                                                        modeling of these nonlinear effects at higher count rates.\nstant). This new expression is again merely an extended form\n                                                                  Typically, this means slightly lowering the dead time constants\nof this Maclaurin like expansion series as shown here, with an                                                        a few hundredths of a \u03bcs as discussed below. This is a tiny nu-                     Wisconsin\nadditional four terms of the series to further improve modeling                                   -\n                                                              merical change which is essentially invisible at low to moder-\nof these nonlinear dead time effects (further increasing the\n                                                                  ate count rates. The appropriate dead time values to be used\nnumber of terms has essentially little to no effect even at these                                                          with these more precise dead time models should be obtained                Madisonhigh count rates):\n                                                              using                                                                     the dead                                                                          time                                                                                       calibration                                                                                methods                                                                                                       as                                                                                                               detailed                                                                                                                bellow.\n                                                       At even                                                                        higher                                                                         count                                                                                            or 400                                                                                                        kcps,                                                                                                   depending                                                                                                on         user                                                                                             rates (>300                                            icps\n                                      \udbff\udf13Icps =   \udbff\udf12                                                                the hardware specifics) these nonlinear effects come to domin-     on                                    \u03c43        \u03c44     1 \u2212   icps \u00b7\u03c4 +i2cps \u00b7\u03c42 + i3cps \u00b7  + i4cps \u00b7  +i5cps \u00b7\u03c45 +i6cps \u00b7\u03c46       ate the pulse processing electronics, and the dead time correc-     17                  2      3      4      5      6\n                                                                  tion becomes extremely sensitive to the exact value of the dead       May                                                              (3)                                                            time constant utilized. For example, some instruments multi-\nSuch high count rates are quite readily obtained at even mod-    plex the pulse pileup processing from multiple spectrometers         2023\nerately high beam currents when utilizing modern instruments     into a single circuit, while other electronic processing delays\nwith large area Bragg diffraction crystals with strong emission    can become more relevant when pulse streams approach the\nlines. Though in fact, this extended form of the dead time cor-    frequency of the response time in the processing electronics.\nrection expression can still be utilized at low and moderate      Regardless of pulse processing limitations, it might be ap-\ncount rates to correct for simple photon coincidence because    propriate to utilize an even more radical mathematical model\nthese high-order terms are all close to zero at low to moderate    such as the exponential expression proposed by Schiff (1936)4                                                                      Microscopy and Microanalysis, 2023, Vol. 00, No. 0\n\n\nTable 2. Calculated Count Rates Using All 4 Dead Time Expressions at a 1.5 \u03bcs Assumed Dead Time Constant where \u201c1t\u201d = Traditional Linear Expression,\n\u201c2t\u201d = Willis et al. (1993), \u201c6t\u201d = Six-Term Expansion, and \u201cnt\u201d = Logarithmic Expression. The \u201cObserved\u201d Count Rate is the Recorded Count Rate as it\nwould be Measured in an Actual Instrument After Pulse Processing. The \u201cPredicted\u201d Count Rate is the Theoretical Count Rate as it would be upon\nEntering the Detector Before any Pulse Processing.\n\nobsv cps         1t pred        1t obs/pre        2t pred        2t obs/pre         6t pred        6t obs/pre         nt pred        nt obs/pre\n\n0           0            0            0            0            0            0            0            0\n10,000       10,152.28      0.985          10,153.44      0.984888       10,153.46      0.984886      10,153.46      0.984886\n20,000       20,618.56      0.97           20,628.13      0.96955        20,628.32      0.969541      20,628.32      0.969541                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     Downloaded30,000       31,413.61      0.955          31,446.95      0.953988       31,447.99      0.953956      31,447.99      0.953956\n40,000       42,553.19      0.94           42,634.83      0.9382         42,638.26      0.938125      42,638.26      0.938125             from\n50,000       54,054.05      0.925          54,218.91      0.922188       54,227.67      0.922039      54,227.67      0.922039\n60,000       65,934.06      0.91           66,228.82      0.90595        66,247.88      0.905689      66,247.88      0.905689\n70,000       78,212.29      0.895          78,697         0.889,488      78,734.09      0.889069      78,734.09      0.889069\n80,000       90,909.09      0.88           91,659.03      0.8728         91,725.59      0.872167      91,725.59      0.872167\n90,000       104,046.2      0.865         105,154       0.855888       105,266.3      0.854974      105,266.3      0.854974\n100,000      117,647.1      0.85          119,225       0.83875        119,405.6      0.837481      119,405.7      0.837481\n110,000      131,736.5      0.835          133,919.7      0.821388       134,199.2      0.819677      134,199.3      0.819676\n120,000      146,341.5      0.82           149,290.9      0.8038         149,709.9      0.80155        149,710.1      0.801549\n130,000      161,490.7      0.805         165,397       0.785988       166,009.3      0.783089      166,009.7      0.783087\n140,000      177,215.2      0.79           182,303.5      0.76795        183,178.8      0.764281      183,179.5      0.764278\n150,000      193,548.4      0.775          200,083.4      0.749688       201,311.8      0.745113      201,313.2      0.745108\n160,000      210,526.3      0.76           218,818.4      0.7312         220,515.8      0.725572      220,518.4      0.725563\n170,000      228,187.9      0.745          238,600.7      0.712488       240,915.4      0.705642      240,919.8      0.705629\n180,000      246,575.3      0.73           259,534.3      0.69355        262,655.3      0.685309      262,662.8      0.685289\n190,000      265,734.3      0.715          281,737.1      0.674388      285,905       0.664556      285,917.5      0.664527\n200,000      285,714.3       0.7            305,343.5      0.655          310,864.3      0.643368      310,884.8      0.643325\n210,000      306,569.3      0.685         330,507       0.635388       337,770.3      0.621724      337,803.3      0.621664\n220,000      328,358.2      0.67          357,404       0.61555        366,906.3   \n\n## 3. donovan2023anewmethod pages 2-3 (Context ID: pqac-00000048)\n\nn and processing effects, all of which fall under the general    of an exactly rectilinear pulse shape and constant dead time      by\nterm of dead time, and that we properly correct for these ef-     relative to the count rate, the traditional dead time expression\nfects to allow for accurate quantitative analyses over a wide      is limited to input count rates up to \u223c50 kcps; a region in\nrange of count rates.                                     which the dead time pulse processing effects are minimal com-                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     University\n                                                          pared to the average time between the pulses and yield a fairly                                                                                                                                    of\n                                                                     linear response with beam current. However, as the pulses be-\nThe Linear Dead Time Expression\n                                                                gin to overlap in time at sufficiently high count rates due to the\nThe traditional form of the dead time expression is commonly                                                               imperfect pulse shapes as observed in typical pulse processing\nnotated as                                                                    electronics (Geller & Herrington, 2002), at count rates higher                           Wisconsin-\n                                            icps                           than \u223c50 kcps, these nonideal pulse shapes begin to become\n                            Icps =                                 (1)     similar to the average time between photon pulses and there-                      1 \u2212(icps \u00b7 \u03c4)                                                                       fore, start to impact the accuracy of the traditional dead                     Madison\nwhere: Icps is the dead time corrected (predicted) count rate in    time model. In addition, it is possible that the assumption of\ncps, \u03c4 is the dead time constant in seconds, and icps is the raw    a constant dead time interval at higher count rates is not per-            user\n(observed) count rate in cps.                                         fectly valid (i.e., an extending dead time constant) (Beaman &      on\n  This classic linear expression (Goldstein et al., 1992, Ruark    Solosky, 1972). We therefore must precisely characterize these      17\n& Brammer, 1937, p. 289) has been utilized for decades for    nonlinear dead time artifacts to improve modeling for accur-         May\nthe correction of observed WDS intensities. It is also tradition-     ate quantitative analysis at these higher count rates.\nally used for determination of the WDS dead time constants.       In addition to the above considerations, the linearity of the            2023\nThis equation considers the mathematical probability of a    picoammeter is also critical for accurate estimates of raw or\nphoton coincident within the dead time interval of the spec-    \u201cobserved\u201d count rate versus beam current as utilized in trad-\ntrometer system with an initial incident photon. The equation     itional  determinations  of dead  time  constants.  In  fact,\nfurther assumes that the photon pulse shape is mathematically    Heinrich et al. (1966) proposed a \u201cratio\u201d method for the de-\nrectilinear and that the dead time interval is constant as a func-    termination of dead time that was based on the measurement\ntion of count  rate. In  fact, with these assumptions, the    of simultaneous K\u03b1 and K\u03b2 emissions on two spectrometers,John J. Donovan et al.                                                                                             3\n\n\nthereby eliminating any nonlinearity of the picoammeter.   EPMA count rates. Furthermore, hardware and electronics\nHowever, the Heinrich \u201cratio\u201d method still assumes a linear    pulse processing limitations at extremely high count rates\nresponse of the pulse processing system which is problematic.     will generally restrict the application of these extended expres-\nWe therefore propose a new nonlinear expression for an im-    sions long before reaching their mathematical limits, e.g.,\nproved software correction of WDS intensities for dead time   when the product of count rate and dead time exceed 1 for\neffects. In addition, we also propose a new method for deter-    both the traditional linear and expanded nonlinear expres-\nmining the accuracy of our dead time constants, which utilizes     sions. However, in practice, the six-term expanded expression\nthe ratio of two intensities from two materials, which we call    (Eq. (3)) is applicable to trace, minor and major element WDS                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              Downloaded\nthe \u201cconstant k-ratio\u201d method. Simply because the traditional    microanalysis from low count rates to count rates up to ap-\nWDS k-ratio should (ideally) remain constant as a function of    proximately 300 to 400 kcps depending on the actual dead         from\nbeam current, if the dead time correction is being properly ap-    time constants of the particular EPMA hardware.\nplied in software.                                               Thankfully, we can greatly simplify this expression by rec-\n                                                              ognizing the Maclaurin series of ln(1 \u2212 x), where ln denotes\n                                                                the natural logarithm:\nExpressions for Nonlinear Dead Time Correction\nA significant improvement in dead time correction accuracy at                  ln(1 \u2212x) \u2248\u2212x \u2212x2 \u2212x3 \u2212x4 \u2212. . .\nthese higher count rates has been described by the use of an                           2   3   4\nadditional term in the traditional linear expression as shown    and with x = \u03c4 \u00b7 icps:\nhere from Willis et al. (1993).\n                                                                                                           \u03c42 \u00b7 i2cps   \u03c43 \u00b7 i3cps   \u03c44 \u00b7 i4cps\n                                            icps                                 ln(1 \u2212\u03c4 \u00b7 icps) \u2248\u2212\u03c4 \u00b7 icps \u2212     \u2212     \u2212      \u2212. . .\n                     Icps =   \udbff\udf12         \udbff\udf13               (2)                           2      3      4\n                                               \u03c42\n                 1 \u2212   icps \u00b7 \u03c4 + i2cps \u00b7                        hence, we have:                                2\n                                                                                                                                       icps\nThis nonlinear expression was originally developed for calcu-                              Icps =                                    (4)\n                                                                      1 + ln(1 \u2212\u03c4 \u00b7 icps)lating work function \u201cdead time\u201d for training of early neural\nnetworks but has now been applied to microanalysis and    With this logarithmic expression, we can correct for not only\nfound useful for correction of observed count rates up to    photon coincidence at low to moderate count rates but also at\nroughly 100 kcps, as we will demonstrate below. These are    higher input count rates for nonlinear response of the WDS de-\ncount rates often encountered when using moderate to high     tectors and pulse processing electronics for improved accuracy\nbeam currents and/or when dead time constants are larger                                                                    at high beam currents, which have been previously impractical\nthan 2 \u00b5s. This Willis expression has been sufficient for most                                                                  for quantitative analysis. Once again, all of these new expres-\nEPMA work  until the rece\n\n## 4. donovan2023anewmethod pages 4-5 (Context ID: pqac-00000049)\n\n  0.725572      220,518.4      0.725563\n170,000      228,187.9      0.745          238,600.7      0.712488       240,915.4      0.705642      240,919.8      0.705629\n180,000      246,575.3      0.73           259,534.3      0.69355        262,655.3      0.685309      262,662.8      0.685289\n190,000      265,734.3      0.715          281,737.1      0.674388      285,905       0.664556      285,917.5      0.664527\n200,000      285,714.3       0.7            305,343.5      0.655          310,864.3      0.643368      310,884.8      0.643325\n210,000      306,569.3      0.685         330,507       0.635388       337,770.3      0.621724      337,803.3      0.621664\n220,000      328,358.2      0.67          357,404       0.61555        366,906.3      0.599608      366,958.8      0.599522\n230,000      351,145        0.655          386,238.2      0.595488      398,614       0.576999      398,696.5      0.57688\n240,000      375,000        0.64           417,246.2      0.5752         433,309.3      0.553877      433,437.6      0.553713\n250,000      400,000        0.625          450,704.3      0.554687       471,503.4      0.530219      471,701.4      0.529996\n260,000      426,229.5      0.61          486,937       0.53395        513,831.5      0.506002      514,135.1      0.505704\n270,000      453,781.5      0.595          526,328.6      0.512988       561,093.4      0.481203      561,556.9      0.480806\n280,000      482,758.6      0.58           569,337.1      0.4918         614,309.8      0.455796      615,015.9      0.455273\n290,000      513,274.3      0.565         616,513       0.470388       674,804.8      0.429754      675,879.8      0.42907\n300,000      545,454.6      0.55           668,523.7      0.44875        744,326.6      0.403049      745,966.3      0.402163\n\n\n\n\nfor extending dead times. Such an expression can be solved for    begins to diverge, and above 200 kcps, the six-term or loga-\nIcps by using the Lambert W-function which can be numerical-    rithmic expressions deviate even further. Though it must bely evaluated. Unfortunately, this exponential expression is    noted that for quantitative analysis, the sensitivity of these                                                                                                                                                                                                                                                https://academic.oup.com/mam/advance-article/doi/10.1093/micmic/ozad050/7165464\nquite limited in practice, in that the product of the dead time    graphical plots for predicted versus observed count rates is in-      by\nand count rate cannot exceed 1/e. This mathematically limits     sufficient for properly evaluating these various expressions, as\nits application to count rates of 245 kcps or less at 1.5 \u03bcs   we will discuss further below.\nand 123 kcps or less at dead times of 3 \u03bcs. Therefore, it is      For an instrument with roughly twice this dead time con-                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     University\nnot considered further in this paper.                              stant (typical of Cameca instruments), these corrections are                                                                                                                                    of\n                                                          even more significant. Assuming a dead time constant of\n                                              \u223c3 \u03bcs, we obtain the following plot as seen in Figure 3 which,\nDiscussion of the Various Dead Time Expressions      though limited to 200 kcps observed count rates, looks muchThe predicted count rates from each of the four dead time cor-    the same as the 1.5 \u03bcs plot from Figure 2 which utilizes ob-                           Wisconsin-\nrection expressions, i.e., traditional (Eq. (1)), Willis two-term    served count rates to 400 kcps. In other words, the predicted\n(Eq.  (2)), six-term expansion (Eq.  (3)), and logarithmic    count rates in Figure 3 are almost the same as Figure 2 yet(Eq. (4)) are shown in Table 2 to identify the mathematical    with only half the input count rates. Hence, the typically high-                     Madison\n                                                                    er dead                                                                   time                                                                           constants                                                                                      of Cameca                                                                                            instrument                                                               WDS spectrom-(modeled)           differences                   between                               the various                                           expressions                                              and\n                                                                          lose                                                                     accuracy                                                                                             faster                                                                                                                                  if not properly                                                                                                             corrected,                                                                                               and the            usercan be examined                 graphically                            as shown                                         in Figure                                                  1, where                                         we     eters\ncan see the dead time corrected theoretical (predicted) inten-    six-term and logarithmic expressions appear to start deviating      on\nsities for recorded (observed) intensities up to 300 kcps with    from the traditional expression above \u223c100 kcps input count      17\na nominal dead time constant of 1.5 \u03bcs.                             rates.                                                                                            May\n  Note that the six-term expression plots underneath the loga-       In addition, the gas detector itself can contain other laten-\nrithmic expression and is not visible in this plot, but which can     cies, for example, the time for the bias voltage to return to            2023\nbe better resolved by plotting the observed count rate up to    nominal while the gas ionization is neutralized. When the\n400 kcps as seen in Figure 2. On an instrument with \u223c1.5 \u03bcs    count rate increases to a time comparable to the duration of\ndead times (typical of JEOL instruments) and up to about    the gas ionization interval, the detector will undergo \u201cparalyz-\n200 kcps, the traditional dead time expression appears to per-    ing\u201d behavior, and the observed count rate drops to zero.\nform similarly. But above that count rate (or with higher dead   Though this gas ionization time constant appears to relatively\ntime constants), the Willis et al. (1993) two-term expression     insignificant until count rates over 500 to 1,000 kcps areJohn J. Donovan et al.                                                                                             5\n\n                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              Downloaded\n                                                                                                                                                                                                                                                                      from\n\n\n\n\n\nFig. 1. Plotting all four dead time correction expressions at a dead time of 1\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049]\n\nStatus: Paper Count=23 | Relevant Papers=15 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=50 | Current Cost=$0.2376 | Disease-Target Evidence=0",
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+                "content": "Let me search for the specific Bethe/Powell paper and the Rinaldi review more carefully:",
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+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nDavid Bote and Francesc Salvat. Calculations of inner-shell ionization by electron impact with the distorted-wave and plane-wave born approximations. Physical Review A, 77:042701, Apr 2008. URL: https://doi.org/10.1103/physreva.77.042701, doi:10.1103/physreva.77.042701.\nMathias Procop and Ralf Terborg. Measurement and calculation of x-ray production efficiencies for copper, zirconium, and tungsten. Dec 2022. URL: https://doi.org/10.1017/s1431927622012351, doi:10.1017/s1431927622012351.\nXavier Llovet, Claude Merlet, Jos\u00e9 M. Fern\u00e1ndez-Varea, and Francesc Salvat. Relative cross sections for l- and m-shell ionization by electron impact. Microchimica Acta, 132:163-171, Apr 2000. URL: https://doi.org/10.1007/s006040050058, doi:10.1007/s006040050058.\nR. Mayol and F. Salvat. Cross sections for k-shell ionisation by electron impact. Journal of Physics B, 23:2117-2130, Jun 1990. URL: https://doi.org/10.1088/0953-4075/23/12/020, doi:10.1088/0953-4075/23/12/020.\nE. Acosta, X. Llovet, E. Coleoni, J. A. Riveros, and F. Salvat. Monte carlo simulation of x-ray emission by kilovolt electron bombardment. Journal of Applied Physics, 83:6038-6049, Oct 1998. URL: https://doi.org/10.1063/1.367473, doi:10.1063/1.367473.\nAur\u00e9lien Moy and John Fournelle. <i>\u03d5</i>(<i>\u03c1z</i>) distributions in bulk and thin film samples for epma. part 1: a modified <i>\u03d5</i>(<i>\u03c1z</i>) distribution for bulk materials, including characteristic and bremsstrahlung fluorescence. Microscopy and Microanalysis, 27:266-283, Feb 2021. URL: https://doi.org/10.1017/s1431927620024915, doi:10.1017/s1431927620024915.\nFrancesc Salvat, Jos\ufffd M. Fernnndez-Varea, and Xavier Llovet. Monte carlo simulation of electron transport and x-ray generation. i. electron elastic and inelastic scattering. Apr 2004. URL: https://doi.org/10.1007/s00604-003-0153-7, doi:10.1007/s00604-003-0153-7.\nNicholas W.M. Ritchie. Spectrum simulation in dtsa-ii. Microscopy and Microanalysis, 15:454-468, Sep 2009. URL: https://doi.org/10.1017/s1431927609990407, doi:10.1017/s1431927609990407.\nRaynald Gauvin. What remains to be done to allow quantitative x-ray microanalysis performed with eds to become a true characterization technique? Microscopy and Microanalysis, 18:915-940, Oct 2012. URL: https://doi.org/10.1017/s1431927612001468, doi:10.1017/s1431927612001468.\nZihang Zhang, Bo Da, Jiamin Gong, and Z. J. Ding. Calculation of backscattering correction factors in aes for compounds: unraveling matrix effects. Journal of Applied Physics, Aug 2026. URL: https://doi.org/10.1063/5.0342873, doi:10.1063/5.0342873.\nFrancesc Salvat, Laia Barjuan, and Pedro Andreo. Inelastic collisions of fast charged particles with atoms: bethe asymptotic formulas and shell corrections. Physical Review A, Apr 2022. URL: https://doi.org/10.1103/physreva.105.042813, doi:10.1103/physreva.105.042813.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052]\n\nStatus: Paper Count=23 | Relevant Papers=15 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=53 | Current Cost=$0.2725 | Disease-Target Evidence=0",
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+                "content": "## 1. rinaldi2015electronprobemicroanalysis pages 2-4 (Context ID: pqac-00000050)\n\n a world of\nlarge data sets needed for such projects.                       innovation in electron microprobe analysis, so much so\n   Upon returning to my Alma Mater, the University of     that it became dif\ufb01cult to keep the pace of automation and\nModena, a few years later (in 1975), I was charged with the    software development with the existing hardware, still cap-\nresponsibility of running the \ufb01rst automated and computer-    able of excellent performance as to both wavelength (WDS)\ncontrolled electron microprobe in Italy, and I dedicated the    and energy (EDS) dispersive systems.\nnext 10 years or so to the probe lab and to promoting       Those were the years when the study of minerals and\nthe self-catering access to EPMA after training colleagues    rocks received an impulse comparable with that caused,\nand students from all over Italy (Rinaldi, 1978, 1979, 1980,   some 120 years earlier, by the introduction of the polarizing\n1981, 1985).                                                 petrographic microscope for the study of rocks in thin\n   The moon-shot technological jump had also had  its     sections. This is also testi\ufb01ed by the peak that occurred in the\nimpact on EPMA technology, and a totally new generation of    discovery of new minerals. Thanks to the micro-analytical                                                                                                Electron Probe Microanalysis  1055\n\n\n\n\n\n        Figure 2. A more modern American microprobe of the mid-1970s (ARL-SEMQ), at the beginning of computer con-\n          trolled automaton. Note the Programmable Data Processor of the Digital Equipment Corporation next to the printer.\n        There is no computer video display. Note the dual cathode ray tube screens\u2014one for photos (slow scan) and the other\n          for visual inspection, capable of TV scan mode (courtesy of Fritz Priziwarra).\n\n\ncapabilities, many new phases, generally crystallized as small      Raymond was recounting the story of when, during his\ngrains, could be fully characterized. Just looking at my own   PhD thesis work, under the supervision of Professor Andr\u00e9\ndirect experience, eight new minerals were discovered in    Guinier some 32 years before (Castaing, 1951), he was faced\nthose years at my laboratory alone [mazzite, merlinoite,    with great dif\ufb01culties and a good dose of skepticism while\namicite, saneroite, cascandite, jervisite, katoite, and wake-     trying to obtain a measurable X-ray signal with Guinier\u2019s\n\ufb01eldite-(Ce)]. This means that the 300 or so probe labs in    spectrometer from the primary excitation of a stationary\nEarth Science research establishments around the world    electron beam impinging on a metal sample in an electro-\nincreased the number of known natural species of minerals     static transmission electron microscope (TEM) adapted for\nby many hundreds, something like 1/3 more of all species of     that purpose. His gut feelings at the time were rather mixed,\nminerals known until then.                              and he recounted that many times he got totally discouraged.\n   The large throughput of accurate analytical data also    Despite that, he carried on improving the set-up until he\nmade it possible to undertake projects of systematic crystal-   managed to make his supervisor (and himself) quite happy\nchemical studies of complex isomorphic  series of rock-     in the end. Incidentally, Andr\u00e9 Guinier was also sitting at\nforming minerals (feldspars, pyroxenes, amphiboles, spinels,     that same dinner table and found Raymond\u2019s description of\netc.); thereby, vastly extending the knowledge of petrogenetic    those early days quite amusing. After dinner, I had the\nfactors underlying the dynamics of the Earth\u2019s interior. The    courage to go up to Professor Guinier and ask for his auto-\nneed and desire to \ufb01nd all possible nuances in the very rare    graph on the book of abstracts, which he was happy to sign\nand precious moon rock samples induced  scientists  to     for me; a very fond memory to be recalled in this year, the\nundertake very detailed investigations on terrestrial minerals    centennial of X-ray crystallography, of which Guinier had\nand rocks. This way, the lunar exploration helped discover a     also been one of the leading \ufb01gures in the  early days\nlarge quantity of unknown features related to Earth materi-    (Duncumb, 2001; Grillon & Philibert, 2002).\nals, thus greatly improving the knowledge of our planet. On         Besides  his  ingenuity  with  those  rather  primitive\nthe other hand, the complexity of natural materials called for    instruments, Castaing had the great merit to demonstrate the\never improved analytical capabilities. Another example of    proportionality between the intensity of the emitted X-ray\nhow basic research is the most effective driver of technol-     signal and the concentration of the emitting element, once\nogical development.                                        account  is taken (by empirical factors) of the nature of\n                                                              the sample (matrix effect). Castaing had actually formulated\n                                                    two approximations, one regarding the proportionality and\nMore Recent Times                                        the other regarding the matrix effects; the combination of\nIt was during those years, in 1983, that I had the fortune to    these two approximations form the core of what is known\nmeet the founding father of the technique, Professor Ray-    as Castaing\u2019s Principle\u2014the fundamental law of EPMA.\nmond Castaing. The occasion was the 10th International    Curiously enough, Castaing\u2019s basic principle, together with\nCongress on X-Ray Optics and Microanalysis in Toulouse,    the  use  of  appropriate  standards,  is nowadays  being\nwhere I happened to sit at his table during dinner.              re-discovered for the latest quantitative applications of EDS1056  Romano Rinaldi and Xavier Llovet\n\nspectrometry with the latest generation of detectors (Newbury    few years, this assessment proved to be very wrong as will\n& Ritchie, 2013), despite over 60 years of development in    become clear in the following sections.\nmethods for calculating all possible matrix effects from \ufb01rst\nprinciples.                               THE LATEST DEVELOPMENTS AND THE NEW\n    At that same Congress, in 1983, several novelties that\n                                AGE OF EPMA: A BRIEF OVERVIEWwere to become important stepping stones in the advance-\nment of the technique were presented. With no claim to                                                  The constant search for low detection limits and high spatial\ncompleteness,  I will mention just a few that are  still of                                                                resolution has recently given EPMA a whole new scope. The\ninterest to this day. A new approach to matrix effects for                                                               idea of trace element analysis, which has been emerging\nquantitative analysis, the \u03a6-\u03c1-z correction, applied to both,                                                 more and more frequently as a favorite issue, is now con-\nbulk and  layered samples (Pouchou &  Pichoir, 1983a,                                                               sidered almost common place with the new generation of\n1983b), later referred to as the PAP method from the initials                                                                electron probes with both WDS and EDS spectrometers. The\nof the two authors. The application of Monte Carlo (MC)                                                         paper on age dating through EPMA of U, Th, and Pb by John\nsimulation methods to the analysis (Murata et al., 1983) and                                                       Bowles in this issue (Bowles, 2015) is a good example of the\nthickness determination (Armigliato et al., 1979, 1983) of                                                                 possible applications of reliable low and trace element con-\nthin \ufb01lms on substrates. An improved absorption correction                                                               centration analysis by EPMA. Ultimately, the capability of\n(Love et al., 1983) derived by MC \ufb01tting of \u03a6-\u03c1-z curves                                                                   trace element analysis by electron microprobe has become a\ncovering a wide range of experimental conditions. The latest                                                                        reality with present-day instruments and data processing\ndevelopments of some of these themes will be treated in the                                                                 software, reaching well below the 0.1 wt% level and into the\nfollowing sections of this paper.                                                                 parts per million (ppm) range (Jerci\n\n## 2. rinaldi2015electronprobemicroanalysis pages 4-5 (Context ID: pqac-00000051)\n\n centration analysis by EPMA. Ultimately, the capability of\n(Love et al., 1983) derived by MC \ufb01tting of \u03a6-\u03c1-z curves                                                                   trace element analysis by electron microprobe has become a\ncovering a wide range of experimental conditions. The latest                                                                        reality with present-day instruments and data processing\ndevelopments of some of these themes will be treated in the                                                                 software, reaching well below the 0.1 wt% level and into the\nfollowing sections of this paper.                                                                 parts per million (ppm) range (Jercinovic et al., 2012).\n   The instrumental complexities and theoretical chal-                                           On the other hand, high spatial resolution has always\nlenges that Castaing had to overcome initially were only the                                                       been the specialty of the technique. However, when account\nbeginning of a constant challenge that had to be met by                                                                                     is taken of the actual interaction volume which everybody has\npeople running the instruments that were made commercially                                                               learned to appreciate from MC simulations at least from a\navailable starting in the early 60s and until the mid-70s of the                                                                 graphical point of view,  it becomes quite evident that the\nlast century. This favored a constant exchange between users                                                               search for better resolution is essential, as shown in Figure 3.\nand manufactures, which, to this day, enjoy a special kind of                                                                       Traditionally, pushing the limit of the lowest detection\nsymbiosis on the subject, as can be strongly felt during meetings                                                                    limit with a WDS spectrometer has meant increasing the\ndedicated to the technique and its applications.                                                                   collection time, as suggested for instance by the classical\n      It was in this period (early-1960s\u2013mid-1970s) that the                                                             expression proposed by Ziebold (1967):\nanalysis of \u201cplatinoids\u201d (now platinum group minerals, or\nPGM), usually occurring as very small grains dispersed                  CDL>3:29a=\u00f0ntP \u00b4 P=B\u00de1=2\nin rocks, was undertaken by Professor Eugen F. Stump\ufb02, a\npioneer in EPMA of minerals (Stump\ufb02, 1961; Stump\ufb02&    where the limit of detectable concentration (CDL) depends on\nClark, 1965) and the founding father of the lab hosting the    a factor (a) relating to composition and intensity, on the\n2014 EMAS Workshop from which the collection of papers   number of observations (n), and on the counting time (t);\nin this special issue has been derived.                      and where P  is the peak count rate and P/B the peak-\n   As a matter of fact, the beginning of the use of the    to-background ratio.\nelectron microprobe for the analysis of minerals and rocks       More advanced statistical expressions have introduced\nas an established and almost mandatory technique in this    con\ufb01dence levels and standard deviations on the measure-\n\ufb01eld can be traced to around 1964, when some 60 papers    ments and  considerations on  precision and  accuracy,\nwere published worldwide, reporting mineralogical analyses    depending on the peculiarity of the sample examined, such\nobtained by  this technique  (Keil, 1973). Therefore, we\ncan safely assume that this year (2014) marks the 50th\nanniversary of the application of the technique in Earth\nSciences. The year 1964 also coincides with the \ufb01rst meeting\nof the Microbeam Analysis Society in the United States\nof America.\n   Around the mid to  late 1990s  (e.g., Rinaldi, 1997),\nthanks  to  the huge improvements  in  microelectronics,\nautomation, and informatics, EPMA tended more and more\nto become a \u201cblack box\u201d routine for a vast number of users,\nand the general consensus was that it had developed towards\na \u201cmature\u201d technology. In other words, not many more\nimprovements could be expected in the medium term, or at    Figure 3. Electron trajectories in Si with E0 = 1, 5, and 10 keV,\nleast advances  at the same rate as during the previous    computed using Monte Carlo simulations. The penetration range\n10 years or so, could no longer be expected. Within only a     of electrons reduces considerably with decreasing beam energy.                                                                                                Electron Probe Microanalysis  1057\n\n\n\n\n\n        Figure 4. Electron micrographs from Au particles. Left images obtained with a \ufb01eld-emission gun, center with a LaB6\n         cathode, and right with a W \ufb01lament. Top beam current of 10 nA; bottom, 100 nA. Accelerating voltage 10 kV, magni-\n         \ufb01cation 5,000\u00d7 (reproduced with permission of JEOL).\n\n\nas small particles, sensitive material, etc. (Jercinovic et al.,     (current density) almost three orders of magnitude greater than\n2012), and taking into account the stochastic nature of the     that produced by a conventional thermionic emitter such as\ngeneration.                                                 a tungsten \ufb01lament or a lanthanum hexaboride cathode. The\n    In any case, the limit is reached when statistical \ufb02uc-     result is a great improvement in signal-to-noise ratio, spatial\ntuations due to instabilities intrinsic to the system approach     resolution, emitter  life, and  reliability. Each one of these\nthe same level as the signal. The key to improving the    improvements has a bearing on extending the capabilities of the\ndetection limit is, therefore, a strong signal with high stabi-     electron beam instrument as to both image and analysis. The\nlity. The latter  is clearly where the advancement in fast     latter being the most important aspect in EPMA. Figure 4\nresponse (picosecond) electronics comes into play. As to the    provides a visual comparison of the image resolution obtained\nnumber of counts produced, this can be improved by a    with the three kinds of emitters (FEG, LaB6, and W).\nvariety of measures that include high re\ufb02ectivity large crys-         All manufacturers of EPMA instruments and electron\ntals, improved vacuum systems, and, last but not least, a new    microscopes (both SEM and TEM) currently offer the \ufb01eld\nkind of electron emitter making use of the \ufb01eld effect as    emission alternative, and this is seen in the names of the\nopposed to the traditional thermionic emission.               instruments that may have an \u201cFE\u201d or an \u201cF\u201d as suf\ufb01x\n   The \ufb01eld-emission gun (FEG)  is probably the most    or pre\ufb01x. The improved emission from a point source\nremarkable of the latest improvements. When compared    allows sub-micrometer analytical probe sizes (10\u201380 nm;\nwith a W-\ufb01lament emitter, its brilliance is several 100-fold      e.g., Berger & Nissen, 2014), again an improvement of three\nbetter, and  stability, once a dif\ufb01cult requirement to be    orders of magnitude over a traditional emitter. When com-\nobtained, is no longer a nightmare, thanks to fast electronics.    bined with low voltage operation (5\u20137 kV), this results in a\nThe design in itself is quite simple, the emitter cathode is    very shallow penetration depth, and therefore a dramatic\nagain tungsten, but in the form of a solid single crystal cone    reduction of the analytical volume (volume of interaction, as\ntapered into a very \ufb01ne point upon which a strong magnetic   shown in Fig. 3), and a generated signal (thanks to the high\n\ufb01eld extracts the electron beam by a principle as old as that     brilliance), which is still strong enough to provide full ana-\non which the lightening rod was conceived by Benjamin     lytical capabilities for both spectroscopies (WDS and EDS).\nFranklin 265 years ago! As a matter of fact, the theory of \ufb01eld        Although the negative trade-offs for low voltage opera-\nemission kept several eminent physicists busy for a good part    tion may require special care and a whole new approach for\nof the 20th century until its practical application was \ufb01nally     quantitative  analysis (Merlet &  Llovet, 2012; Pinard &\nintroduced as a commercial alternative in electron micro-     Richter, 2014), the advantage of a greatly reduced interaction\nscopy during this last decade. As is often the case, there are    volume opens up a large variety of new applications in the\nseveral different designs of FEG\u2019s, but their description is    characterization of thin \ufb01lms and nanomaterials. The pros\nbeyond the scope of this brief account. It is suf\ufb01cient to note    and cons\n\n## 3. rinaldi2015electronprobemicroanalysis pages 5-7 (Context ID: pqac-00000052)\n\nlthough the negative trade-offs for low voltage opera-\nemission kept several eminent physicists busy for a good part    tion may require special care and a whole new approach for\nof the 20th century until its practical application was \ufb01nally     quantitative  analysis (Merlet &  Llovet, 2012; Pinard &\nintroduced as a commercial alternative in electron micro-     Richter, 2014), the advantage of a greatly reduced interaction\nscopy during this last decade. As is often the case, there are    volume opens up a large variety of new applications in the\nseveral different designs of FEG\u2019s, but their description is    characterization of thin \ufb01lms and nanomaterials. The pros\nbeyond the scope of this brief account. It is suf\ufb01cient to note    and cons of these new avenues offered by the FEG in EPMA\nhere that the electron beam produced by an FEG is much    are discussed in more detail in the Analytical Capabilities\nsmaller in diameter, more coherent, and has a brightness    Today: Advantages and Disadvantages section.1058  Romano Rinaldi and Xavier Llovet\n\n    Another instrumental development has recently pro-    response to different crystal orientations of the sample (and\nvided great improvement in EDS with the introduction,    reference standard) under the beam. Some of these have\nduring the last decade, of a new device\u2014the silicon drift     recently been reviewed (Donovan, 2011). The usual strate-\ndetector (SDD)\u2014the development of which has been as fast     gies to avert or limit these effects include the careful choice of\nas to have already reached its 6th generation. When com-    instrumental parameters, the use of an anti-contamination\npared with the traditional lithium drifted silicon detector (Si    device and/or of a cryostage, careful monitoring of the\n(Li) detector), this new kind of device, although working on     effects, and use of empirical correction coef\ufb01cients as a\nexactly the same principle, provides a considerable number    function of dwell time.\nof advantages. The \ufb01rst and the most noticeable, even to the        Other caveats, especially when working with low-energy\nuntrained eye, is the lack of the cumbersome and incon-     lines (low voltage excitation), include the need to revisit the\nvenient liquid nitrogen cryostat and the reduction in main-    mass attenuation coef\ufb01cients (MACs) (e.g., Gopon et  al.,\ntenance activity this implies. The detector can in fact operate    2013) and the effects due to secondary \ufb02uorescence (SF) at\nat room temperature or with moderate cooling, such as that    grain boundaries (e.g., Llovet et al., 2012; Wade & Wood,\nprovided by the thermoelectric (Peltier) effect, thanks to the    2012). Some of these aspects are treated in more detail in the\nvery  low  leakage  current  generated  within  the  device.    following section, with a few examples of applications.\nThe other main advantage is the count rate performance, which\nis up to two orders of magnitude greater than that of a Si(Li)\ndetector (Newbury & Ritchie, 2013). All this, combined with an   ANALYTICAL CAPABILITIES TODAY:\nenergy resolution close to the theoretical value of 120 eV for a  ADVANTAGES AND DISADVANTAGES\nsilicon device, makes the SDD a desirable analytical tool for all\nkinds of electron microscopy. A comparison of performance   Improved Detection Limits for Trace Analysis\nbetween EDS and WDS spectroscopies now has to take into    Use of electron microprobes for trace element analysis has\naccount the great improvements one can obtain with this latest    increased over the years, mainly because of the improved\ngeneration of solid-state detectors where a de\ufb01nite advantage     stability of electron columns operated at high-beam currents\ncan be scored, for instance, in the acquisition speed of X-ray    and the development of new crystal analyzers with larger\nmaps. However, when energy resolution and low detection     areas. Figure 5 provides a comparison between these newly\nlimits are at stake, WDS detectors remain as the technique of\nchoice for quantitative analysis, especially for trace and light\nelements (Maniguet et al., 2012).\n    In the \ufb01eld of WDS spectroscopy, a very recently\nintroduced device provides considerable improvement in the\nanalysis of very soft X-rays, including Li and Be among the\nelements that can be quantitatively analyzed. This type of\nspectrometer makes use of a new grazing incidence grating\ntechnology, whereby dispersion of the incident X-rays  is\nobtained by Bragg re\ufb02ection over a physical grating rather\nthan a crystal lattice. The combination of a laminar-type\nvaried-line-spaced (VLS)  grating with a  high-sensitivity\nX-ray CCD detector allows simultaneous collection of a full\nspectrum (within a limited wavelength range), thus making\nthe device somewhat comparable with EDS. Having been\nintroduced only very recently, testing of the device is still\nlimited to a few emblematic examples that have been pro-\nvided by the manufacturers. However, there is no reason to\ndoubt the promise to considerably expand the capabilities of\nEPMA, as discussed is more detail in the last section dealing\nwith the envisaged future.\n    Most, if not all, of the above-mentioned advances are\nextending the limits of EPMA toward higher spatial resolu-\ntion and lower detection limits. The trade-off is normally the\nincreasing importance of some adverse effects that the ana-\nlyst has to take into account. Among these effects, a few are\nworth mentioning here even if they will not be discussed in\ndetail according to the nature of this brief review. Carbon    Figure  5. Sensitivity  of  newly  developed LDE2 and LDE2H\ncontamination and sample \u201cdamage\u201d by the electron beam      crystals, as compared with  traditional STE,  for the  analysis  of\nboth merit attention here. The latter comprises effects such     C. Detection limits are 12 (LDE2H), 23 (LDE2), and 49 ppm (STE)\nas migration of elements from the analytical volume, also in      (after Mori et al., 2011). Reproduced with the permission of JEOL.                                                                                                Electron Probe Microanalysis  1059\n\n                                                                Instrumental and sample stability during long acquisi-\n                                                                tion times can be monitored by means of statistical tests (e.g.,\n                                                                \u03c72 test along with Dixon and Grubss \ufb01lters), as discussed by\n                                                           Merlet & Bodinier (1990). This procedure requires the long\n                                                          counting times to be divided into many short counting times\n                                                    and alternating peak and background measurements to\n                                                      minimize instrumental drift.\n                                                      The problem of SF across phase boundaries arises from the\n                                                                          fact that characteristic X-rays and bremsstrahlung produced by\n                                                          primary electrons can ionize atoms at much larger distances\n                                                      from the point of impact than primary electrons. Indeed,\n                                                             although the range of primary electrons is of the order of a\n                                                         few micrometers, that of the generated  characteristic and\n                                                            bremsstrahlung X-rays can be one-to-two orders of magnitude\nFigure 6. Detection limit for Mn in a San Carlos olivine standard     larger. This means that, even for electron beams impacting\nas a function of probe current and peak counting time. Typical     quite a distance from a phase boundary, there can be a \ufb02uor-\nconditions for routine, precision, and high-precision analysis are    escence contribution arising from the neighboring phase. This\nmarked (after Sobolev et  al., 2007). Reprinted with permission     contribution is important for trace analysis, especially when the\nfrom AAAS.                                                  neighboring phase contains an appreciable concentration of the\n                                                           element of interest. This effect will be discussed in more detail\n                                                                  in the Limitations and Problems subsection.\ndeveloped crystals and the traditional one (STE) in C ana-        Examples of improved methods for the analysis of trace\nlysis. These developments have made it possible to decrease    elements include those developed by Merlet & Bodinier\nthe detection limits of the technique down to a few ppm by    (1990) and Fialin et al. (1999). The latter auth\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052]\n\nStatus: Paper Count=23 | Relevant Papers=15 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=53 | Current Cost=$0.2725 | Disease-Target Evidence=0",
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+                "role": "assistant",
+                "content": "Now let me update the plan and read a few more key texts, particularly for the measurement uncertainty paper and the Guyett SEM-EDX optimization paper:",
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+                  {
+                    "id": "toolu_01UDDVRyrAHJbAP4kGZqW2nE",
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+                      "arguments": "{\"text_name_list\": [\"tong2026measurementuncertaintiesof pages 8-11\", \"guyett2024optimizingsemedxfor pages 3-4\", \"guyett2024optimizingsemedxfor pages 4-6\"]}",
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+                    "id": "toolu_01Rs93g1Tkjz8VPN53HsLW2c",
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+                      "arguments": "{\"question\": \"How does the phi-rho-z depth distribution function of X-ray production work in electron probe microanalysis? What are the competing effects between ionization cross-section and electron range that determine optimal accelerating voltage? What did Castaing's tracer experiments demonstrate?\"}",
+                      "name": "gather_evidence"
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+                "role": "tool",
+                "content": "## 1. tong2026measurementuncertaintiesof pages 8-11 (Context ID: pqac-00000053)\n\nRVIEW\nWhen electrons of sufficient energy hit a sample, they generate X-rays of specific energies\ncharacteristic of the elements present. The main challenge of qualitative analysis is to ensure\nthat all X-ray peaks are detected and correctly labelled as a sample element or a detector\nartefact peak. The intensity of the X-ray peaks are not interpreted, although in complex or\nnoisy spectra, low intensities may cause low concentration elements to be missed. Accurate\nqualitative EDX is a prerequisite of any quantitative EDX.\n\n\nPage 1 of 20NPL Report MAT 135\n\n\nAn example of a periodic table that lists the characteristic X-ray emission energies (K\u03b1, L\u03b1,\nand M peaks) for each element can be found at: https://www.edax.com/resources/interactive-\nperiodic-table. X-ray techniques with higher energy resolution, such as X-ray photoelectron\nspectroscopy (XPS) or SEM wavelength dispersive X-ray spectroscopy (SEM-WDS) can split\nthese into multiple lines (e.g. K\u03b11, K\u03b12, K\u03b21, etc.), but since the energy resolution of EDX\ndetectors are usually \u2265 100 eV, only a single broader peak is measured.\n\nElemental assignment of X-ray peaks might be ambiguous if the peaks from multiple\nelements have similar energies (within 30 eV of each other). ISO 22309:2011 Annex B lists\ngroups of elements with ambiguous X-ray peaks.\n\nElectrons can only generate characteristic X-rays with considerably lower energy than the\nprimary electron energy. The ratio between the incident electron energy and the\ncharacteristic X-ray energy is called the electron overvoltage. An electron overvoltage of at\nleast 1.8 is specified for quantitative analysis in ISO 22309:2011. It is not absolutely required\nbut still recommended for qualitative analysis, as X-ray peaks close to the primary electron\nenergy may be hidden or very weak. It is impossible to generate X-rays that have a higher\nenergy than the primary electron energy.\n\nArtefact peaks are not characteristic X-ray peaks of the sample. They need to be identified\nand corrected. EDX analysis software packages generally have features built in to do this,\nbut it is still the operator\u2019s responsibility to check that this has been done correctly and no\npeaks have been mislabelled.\nSum peaks (also known as pile-up peaks) happen when two X-ray photons hit the detector\nat the same time, and are mistakenly detected as a single X-ray whose energy is the sum of\nthe two original photons. These appear as small peaks at higher energies that are the sum of\nmultiple X-ray emission peak energies, e.g. at double the energy of the highest intensity\npeak.\nEscape peaks are caused by X-ray fluorescence of the detector material, usually made of\nsilicon, so that the detected X-ray energy is the X-ray emission peak. Escape peaks appear\nas small peaks at higher energies, e.g. at double the energy of the highest intensity peak.\nThe noise peak at near-zero energy is when electronic noise in the detector is mistaken for\nnear-zero energy photons.\n\n1.2 QUANTITATIVE EDX METHOD OVERVIEW\nEDX quantification is based on the principle that X-ray peak intensities for an element\nincrease with concentration of that element in a sample. However, there are two problems:\n   (1) X-ray detector efficiency is not constant, so identical X-ray intensities hitting the EDX\n      detector at, for example, 1 keV and 8 keV will not lead to identical peak areas at 1 keV\n     and 8 keV; and\n   (2) the generated characteristic X-ray intensities are not linear with concentration, so\n     doubling the atomic concentration of an element does not necessarily double the\n      intensity of characteristic X-rays hitting the EDX detector.\n\nAll quantitative analysis considers the characteristic X-ray peaks only, which means it is\nnecessary to remove the intensity contribution of background X-rays generated by\nBrehmsstralung radiation. Background correction is important in quantification, but different\nEDX analysis software packages use different methods and this usually cannot be tuned by\nthe user. However, a poor background fit (Figure 1b), which leads to inadequate peak area\ndetermination, is still a useful warning sign to the operator that that the quantitative results\nhave high uncertainty.\n\n\n\n\nPage 2 of 20NPL Report MAT 135\n\n\n\n              (a)\n\n\n\n\n\n              (b)\n\n\n\n\n\n      Figure 1: Example spectra with (a) good and (b) bad background fit.\n\nProblem (1) explains why elemental standards are needed for full quantitative analysis, so\nthat differences in detector efficiency can be cancelled out. The detector window material\naffects detector efficiency, especially in the low X-ray energy range (see Figure 9 in [5]).\nBeryllium windows absorb the majority of X-rays below 1 keV and therefore are not suitable\nfor use with low-Z elements below Na (Na K = 1.04 keV). Si3N4 or polymer thin windows\nperform better, but the efficiency drops off significantly and is discontinuous in this energy\nrange. Windowless detectors would be preferable but are not currently available at NPL in\n2024. Contamination buildup in the SEM can also affect efficiency for all detector\nconfigurations.\n\nProblem (2) is why background subtraction and matrix corrections are needed (also known\nas ZAF corrections: Z = atomic number, A = X-ray absorption, F = X-ray fluorescence).\nThese account for the effects of:\n -   Electron backscattering (which increases with atomic number Z), where incoming\n    electrons are either scattered back out of the sample without generating an X-ray, and\n    electron stopping power, which describes how electrons lose energy (and the\n    corresponding ability to excite atoms and generate X-rays) as they penetrate the sample.\n -   X-ray Absorption, which means that X-rays generated by the sample are absorbed\n    before they leave the sample and never make it to the detector.\n -  Secondary X-ray Fluorescence, which means that high-energy X-rays generated in the\n    sample generate lower-energy X-rays. As a result, the high-energy X-ray is not detected,\n    but extra low-energy X-rays are detected by EDX.\n\n\nPage 3 of 20NPL Report MAT 135\n\n\nThe theory relating to ZAF matrix corrections are more naturally described by weight\nfractions instead of atomic fractions. This is why EDX compositions are calculated as\nweight % even though the k-ratios are more naturally expressed in atom %.\n\nNot every X-ray line is in the standards database, so for example the Fe-L peaks (0.705 keV)\nmay not be used for quantification if only the Fe-K peaks (6.403 keV) are included in the\ndatabase. This must then be taken into account when selecting SEM accelerating voltage \u2013\nfor example, the Fe-K peak requires at least 12 kV electron energy to be adequately excited\nfor quantitative analysis.\n\n\n\n\n\nPage 4 of 20NPL Report MAT 135\n\n\n\n                                                                                                                                                                                              (4) All elements in                             (1) Conductive and                                          (2) Flat, polished,                                                                                                                                             (3) All sample                         sample (incl. trace                         stable in vacuum and                          homogeneous surface,                                                                                                           elements are Z > 11?                        elements) already                           electron beam?                              normal to electron beam?                                                                                                                                       known?\n\n                Yes          No                       Yes       No             Yes          No                Yes        No\n\n                    Qualitative                                                                                                                               Consider                                                                                                                            low                                       Try                                    10                             nm C                                                                Any                                                                                                                                                                      over-                                                                                                                           \u2265 1.8 \u00d7                                                                                                                                                                                                                 Unnormalised                                                                                               Qualitative            \n\n## 2. guyett2024optimizingsemedxfor pages 4-6 (Context ID: pqac-00000054)\n\n     0.00          0.07\n           Cl         <LOD     <LOD     <LOD     <LOD     <LOD     <LOD      <LOD     <LOD        0.02          0.03\n           Total         97.00        98.16        98.48        98.74        98.82        99.15        99.25        99.18        100.04       99.24\n\n\n      NMNH 72854\n          SiO2          76.3         76.9         77.1         77.3         77.3         77.4          77.4         77.9          77.9          78.1\n           Al2O3         11.9        12           12.1         12.2         12.2         12.2          12.1         12.2          12.2          12.2\n         K2O           4.95         4.84         4.94         5.01         4.93         4.94          4.95         5.07          5.08          5.08\n         Na2O         3.67         3.5          3.44         3.37         3.17         3.7           3.53         2.99          2.91          3.28\n           FeO(t)        1.02         1.11         1.22         1.12         1.15         1.2           1.17         1.18          1.18          1.18\n        CaO          0.00         0.00         0.26         0.44         0.47         0.47          0.45         0.48          0.48          0.47\n           Cl         <LOD     <LOD     <LOD       0.02         0.04         0.11          0.12         0.12          0.11          0.11\n          TiO2       <LOD     <LOD     <LOD     <LOD     <LOD     <LOD        0.01         0.05          0.08          0.09\n       MgO       <LOD     <LOD     <LOD     <LOD     <LOD     <LOD      <LOD       0.01          0.01          0.01\n       MnO       <LOD     <LOD     <LOD     <LOD     <LOD     <LOD      <LOD     <LOD      <LOD        0.01\n          P2O5       <LOD     <LOD     <LOD     <LOD     <LOD     <LOD      <LOD     <LOD      <LOD      <LOD\n           Total         97.84        98.35        99.06        99.46        99.26        100.02       99.73        100.00       99.95        100.53\n\n\n\n        2568  | J. Anal. At. Spectrom., 2024, 39, 2565\u20132579                                       This journal is \u00a9 The Royal Society of Chemistry 2024                                                                                                                                        View Article Online\n\n        Paper                                                                           JAAS\n\n\n        and  counts  per  analysis.  However,  these  analyses  were   analyses in rhyolite glass NMNH 72854 was adversely a\ufb00ected\n         completed with a scanning FoV of 1 mm to avoid partial analysis   only at high counts ($5M). Even lower beam currents can result\n          of microlites. An EDX map and BSE image were collected to   in Na-loss over an extended period  of  time.16 Hence,  to\n          highlight the  microlite  density. The  voltage and working\n          distance remained  as  before  but  the beam  current was\n         increased to 3 nA to o\ufb00set the e\ufb00ect of the smaller FoV on the\n           total number of counts and the process time was set to 2. This\n         increased beam current increases the SEM counts per second to\n         approximately 800 kcps. For the map, the \ue103eld of view was set to\n         50 mm. Both a BSE image and an EDX map were collected withPM. Licence.    a resolution of 2048 \u00d7 1557, with a pixel dwell time of 10 ms per\n           pixel for the BSE image and 200 ms per pixel for the EDX map.\n          The cryptotephra from the Laki 1783-84 AD eruption was7:38:13 Unported\n         analysed using a wavelength-dispersive JEOL 8600 electron\n   3.0\n         microprobe in 2016. This analysis was completed using an7/23/2025          accelerating voltage of 15 kV, a 6 nA current and a beam\non\n         diameter of 10 mm. Peak count times were 30 s for most           Attribution         elements and 10 s for Na. Due to the small size (25\u201340 mm long\n         but with analyzable areas of <20 mm) of the cryptotephra, onlyDownloaded      one EPMA analysis was acquired successfully.42 The crypto-       Commons\n2024.       tephrausing asamplesTescan wereMira reanalysedXMU FE-SEMin theequippedsame yearwithbyanSEM-EDXOxford        Creative    Instruments X-Max 80 mm2 EDX detector and Oxford Inca\n a    so\ue09dware. In total, nine basaltic shards were analysed.42September     under\n03\non licensed   4.4.1  OptimalResultsnumberandof countsdiscussion\n  is\n        The number of counts per analysis  is a trade-o\ufb00betweenPublished       article     sensitivity on the one hand and acquisition runtime and cation\n          mobilisation on the other. Fig. 2 shows the relative standardArticle. This\n          deviations (RSD%) of SEM-EDX glass analyses conducted over\n         a range of total counts (complete data can be found in Table 1Access\n        and ESI Table 1\u2020). For almost all elements the most precise\nOpen        results came from the analyses that collected the highest\n        number of counts. The quickest analyses, those acquired with\n        10k and 20k counts (below one second analysis time), displayed\n           relative standard deviation (RSD%) >5% on elements over 10 wt\n         oxide%, and RSD% >10% on elements above 1 wt oxide%. Once\n         the number of counts per analysis is above 100k (one to three\n         second analysis time), all elements over 1.5 wt oxide% exhibited\n         a RSD% of <5%. These results here may have implications on\n            fully quanti\ue103able alternative SEM-EDX applications such as\n         element mapping, where analysis of large cumulative areas\n          necessitates rapid analysis. When >1M counts were acquired,\n         the RSD% for major element oxides was <2% for both basaltic\n          glass VG-2 and rhyolitic glass NMNH 72854. For fully quanti-\n           tative EDX analysis, we recommend collecting a minimum of\n      1M counts, as this will result in rapid acquisition (approxi-\n         mately 15 seconds using the above SEM parameters) of accurate\n         major element data. It is possible to attain data of similar    Fig. 3  Repeat analyses on basaltic NMNH VG-2 and rhyolitic glass\n                                                  NMNH 72854 to investigate potential beam-induced elemental loss on\n          precision  for  higher  concentration  trace  elements  (those\n                                                                      Na2O, K2O and Cl. Each glass is analysed in four separate areas up to\n         present at >0.1 wt% or above) in both glasses, but this requires   a total of 20M counts. Analyses comprised either 1M, 2M, 5M and 10M\n          analyses of c. 10M counts.                                      count intervals. Panels (a)\u2013(e) display analyses on elements in decreasing\n            Certain elements (e.g., Na, K and Cl), are known to display   abundance. K2O in NMNH 72854 and Na2O in both glasses are major\n          mobility  during beam  interaction  due  to  heating.15,16,25   elements (panels (a)\u2013(c)), and the remaining K2O (NMNH VG-2) and Cl\n                                                         (NMNH 72854) analyses are minor elements (panels (d) and (e)).\n         However,  it is evident from Fig. 2 that the precision of Na\n\n\n\n           This journal is \u00a9 The Royal Society of Chemistry 2024                                                    J. Anal. At. Spectrom., 2024, 39, 2565\u20132579  | 2569                                                                                                                                        View Article Online\n\n      JAAS                                                                                        Paper\n\n\n           Table 2  Repeated spot analysis on NMNH VG-2 and NMNH 72854. For each glass four separate areas were analysed summing up to a total of\n       20M counts\n\n\n          Counts (million)    1        1        1        1        1        1        1        1        1        1        1        1\n\n      NMNH VG-2       33a      33b      33c      33d      33e       33f      33g      33h       33i        33j      33k       33l\n          SiO2                50.7      50.8      51.0      51.1      50.8      51.0      51.0      51.0      51.0      51.1      51.1      51.1\n           Al2O3               14.1      14.2      14.2      14.1      14.1      14.1      14.2      14.1      14.1      14.2      14.1      14.2\n           FeO(t)              11.7      11.7      11.6      11.7      11.8      11.6      11.6      11.4      11.7      11.8      11.6      11.6\n        CaO                11.1      11.1      11.1      11.2      11.1      11.1      11.1      11.2      11.1      11.2      11.2      11.2\n       MgO               7.00      6.93      6.93      7.06      7.02      6.89      6.96      6.86      7.00      6.94      6.94      6.91\n                               2.63                                         2.76                                                    2.67                                                              2.65                                                             \n\n## 3. guyett2024optimizingsemedxfor pages 3-4 (Context ID: pqac-00000055)\n\nf which may be too small for  from komatiite to rhyolite and with a range of alkali contents\n       WDS-EPMA.                                                         (SiO2: 45.5\u201376.7; Na2O: 0.83\u20134.44; K2O: 0.19\u20135.10 wt%). These\n\n\n\n        2566  | J. Anal. At. Spectrom., 2024, 39, 2565\u20132579                                       This journal is \u00a9 The Royal Society of Chemistry 2024                                                                                                                                        View Article Online\n\n        Paper                                                                           JAAS\n\n\n          glasses include the Smithsonian National Museum of Natural  so\ue09dware version 5.1 (and subsequently version 6.1) at the iCRAG\n          History (NMNH) glasses NMNH VG-2, NMNH 72854, NMNH   Laboratory in Trinity College Dublin. Additional analyses were\n         113498-1 and NMNH 113716-1,30 MPI-DING glasses ATHO-G,  undertaken using a Tescan Tiger Mira3 FE-SEM operating\n         T1-G, StHs6/80-G and GOR132-G,31 as well as rhyolitic glasses  under high vacuum conditions, \ue103tted with two XMaxn 150 mm2\n         ID3506 (ref. 32) and Oregon Obsidian from the MINM25-53  EDX detectors running Oxford Instruments AZtec microanalysis\n         standard mount (ESI Table 1\u2020). The glass samples employed  so\ue09dware version 3.2. Unless otherwise speci\ue103ed, analyses were\n          in this study are of known composition and are widely used as  undertaken with a voltage of 20 kV, a 4.5 nm wide beam with\n          reference materials in WDS-EPMA analyses of glasses (e.g., ref.  beam current of 300 pA, and a process time of \ue103ve, following the\n         33 and 34). The two glasses initially investigated to determine  SEM-EDX protocol de\ue103ned in Ubide et al. (2017).8 Beam current\n         optimal experimental setup are the basaltic glass NMNH VG-2  dri\ue09dwas controlled by analysis of cobalt a\ue09der each samplePM. Licence.    and the rhyolitic glass NMNH 72854.30 These were selected as   change, however it is worth noting that modern FE-SEMs show\n         two homogenous end members which span a broad composi-   considerably lower dri\ue09dcompared to older W-SEM systems.43\n          tional range. The MINM25-53 mount contains a suite of silicate   Process time is a dimensionless time index between one and six7:38:13 Unported\n        and sulphide minerals, produced by Astimex Standards Ltd,   within the AZtec so\ue09dware. It is a time index where a lower\n   3.0\n         Canada.                                           number prioritises analysis time and a higher number priori-7/23/2025          The study chose to focus on glass because  it  is non-   tizes energy resolution.\non\n          stoichiometric, and thus presents a greater challenge than      Fully quanti\ue103ed SEM-EDX analysis requires the microscope           Attribution         minerals for which stoichiometry provides an additional check   to be set up correctly and to have the highly-polished and \ue104at\n        on data quality (e.g., ref. 35) and also because of the potential for  sample under the beam at an appropriate working distanceDownloaded      beam-induced elemental mobility. Fully quantitative SEM-EDX  (WD) which herein is 15 mm. There are two main ways to collect       Commons\n2024.       analysiswhile preciseon  glasssamplethuspreparationrequires  carefulis neededinstrumentto accountset-upfor  SEM-EDXAnalysis modespectracollectsthroughdataAZtec;by rasteringAnalysisa 4.5Modenm beamor Pointover& theID.        Creative     issues with specimen geometry. Samples were polished on an   scanning window for a determined runtime and collecting all X-\n a    automatic lap using progressively \ue103ner diamond grits down to 1   ray information within this \ue103eld of view at a high magni\ue103cationSeptember     under    micron to ensure a \ue104at and highly polished surface to attain   while Point & ID collects a reference image such as back-\n03            fully quantitative SEM-EDX results. The samples also need to be   scattered electron (BSE) at a lower magni\ue103cation and analysis is\non\n            fully conductive to avoid charging of electrons on the surface,   acquired from selected areas within this image. The selected        licensed\n  is     typically this will require specimens to be coated in a thin layer   area can be a selected point or a shape (e.g., a circle, rectangle,\n          of carbon or gold. All samples were coated with 12 nm of carbon   or user-de\ue103ned polygon). The acquisition of an image showingPublished       article    before being introduced into the SEM chamber for analysis.   the location of the SEM-EDX spot analyses when using the Point\n           Finally,  additional  analyses  were  undertaken on  natural  & ID method makes it initially quite appealing; however, thereArticle. This\n          volcanic glass shards to further highlight SEM-EDX data quality   are drawbacks with this approach. In practice, due to the\n        and to demonstrate some of the advantages o\ufb00ered by this   resolution of the acquired image at lower magni\ue103cation, it isAccess\n          technique. These samples include:                            not always possible to ensure that the sample  is polished\nOpen           Tephra layer TM-24-3b from an eruption of Ischia and   completely \ue104at. In mineral samples, there may be material\n         deposited at Lago Grande di Monticchio, Italy (LGdM) (ref. 36  removed along grain boundaries or along cleavage planes and\n        and 37) 80 km to the east. This sample was previously analysed  such areas need to be avoided. Accurate and fully quantitative\n         by EPMA37 and  is reanalysed here by SEM-EDX  to allow  SEM-EDX analysis requires \ue104at, polished samples that are in-\n         comparison of the data quality achieved by the two techniques.   focus which is not always possible during Point & ID spot\n           Ma\ue103c tephra from the PdB (Pomici di Base) eruption of   analysis; a very well-polished geologic sample may still have\n        Somma-Vesuvius which is challenging to analyse because the   varying topography. Analysis Mode ensures that the sample is\n         tephra is microlite rich38 and the spacing between microlites is   in-focus, thus providing more con\ue103dence in the quality of the\n          smaller than the interaction volume produced by a 10 mm beam.   analysis. In both methods it is possible to collect the data using\n         This resulted in the acquisition of mixed compositions (glass   a set runtime or until a set number of counts has been attained.\n        and crystal phases) with the EPMA method (ref. 39: their Fig. 7).      X-ray peak  energies  for each peak were  calibrated  to\n                Basaltic cryptotephra shards from the Laki 1783-84 AD   concentrations using a range of mineral and glass standards.\n         eruption identi\ue103ed in Brackloon Wood, Co. Mayo, Ireland (ref.   For optimal matrix matching of silicate glasses, we used the\n         40 and 41). Analysis of these tephra presents a challenge   following phases on the Astimex MINM25-53 standard mount\n         because of their extremely small size (<40 mm vesicular shards   for standardisation:  apatite, chromite, diopside, kaersutite,\n         with analyzable areas of <20 mm) and only two out of 24 were   magnetite, olivine, orthoclase, pentlandite, rhodonite, rutile\n          successfully analysed by EPMA.42                          and tugtupite (ESI Table 1\u2020). All chemical data presented in this\n                                                                       study are presented as oxide weight percent where oxygen has\n       3.  Methodology                               been calculated by stoichiometry in AZtec, with the exception of\n                                                                       Cl (element %). Standard phases were analysed for 2M counts,\n         This study uses a Tescan S-8000 FE-SEM operating under high  and as the instrument is collecting 100k counts per second, and\n        vacuum conditions, \ue103tted with four 170 mm2 Ultim Max EDX  has a dead time of c. 15%, each analysis took approximately 25\n          detectors running the Oxford Instruments AZtec microanalysis\n\n\n\n           This journal is \u00a9 The Royal Society of Chemistry 2024                                                    J. Anal. At. Spectrom., 2024, 39, 2565\u20132579  | 2567                                                                                                                                        View Article Online\n\n      JAAS                                                                                        Paper\n\n\n         seconds. Standardisation is undertaken at the start of each day/   K, Cl). To quantify the risk of loss of mobile and volatile\n          session.                                                      elements, consecutive analysis under increasing count times on\n            Following SEM setup for  fully quanti\ue103ed EDX analysis,  both the basaltic and rh\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052, pqac-00000053, pqac-00000054, pqac-00000055]\n\nStatus: Paper Count=23 | Relevant Papers=17 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=56 | Current Cost=$0.2725 | Disease-Target Evidence=0",
+                "name": "read_text",
+                "tool_call_id": "toolu_01UDDVRyrAHJbAP4kGZqW2nE",
+                "info": {
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+                  "end_ts": 3110.060027675
+                }
+              },
+              {
+                "role": "tool",
+                "content": "No relevant evidence found for your question.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052, pqac-00000053, pqac-00000054, pqac-00000055]\n\nStatus: Paper Count=23 | Relevant Papers=17 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=56 | Current Cost=$0.3082 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
+                "tool_call_id": "toolu_01Rs93g1Tkjz8VPN53HsLW2c",
+                "info": {
+                  "start_ts": 3104.645571291,
+                  "end_ts": 3117.905648366
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "I have extensive evidence now. Let me update my plan and start creating artifacts and the final answer. Let me mark objectives as completed and gather any remaining gaps:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01LvbMj9QNiv1dUfwumiuitp",
+                    "type": "function",
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+                      "arguments": "{\"plan_objective_id\": 1, \"updated_plan_objective_json\": \"{\\\"id\\\": 1, \\\"objective\\\": \\\"Research ionization cross-section physics and overvoltage ratio optimization\\\", \\\"rationale\\\": \\\"Need to trace the physics basis for the U0 ~ 2-3 recommendation\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\\\", \\\"evaluation\\\": \\\"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\\\"}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models (paralyzable/non-paralyzable) and the derivation of the 20-40% dead-time guidance for optimal throughput\",\n      \"rationale\": \"Need to explain the counting-rate optimization that yields the dead-time recommendation\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\",\n      \"rationale\": \"Need to explain the detector electronics basis for process time recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01LvbMj9QNiv1dUfwumiuitp",
+                "info": {
+                  "start_ts": 3171.64280487,
+                  "end_ts": 3171.645486114
+                }
+              },
+              {
+                "role": "assistant",
+                "content": null,
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_015goBjacFSmU7C4yFqCakTW",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 2, \"updated_plan_objective_json\": \"{\\\"id\\\": 2, \\\"objective\\\": \\\"Research dead-time models and throughput optimization\\\", \\\"rationale\\\": \\\"Need to explain the counting-rate optimization\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\\\", \\\"evaluation\\\": \\\"Comprehensive coverage of dead-time models with both physics and practical recommendations.\\\"}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_01LAfPYdGfcVfrw8uwURVK9w",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 3, \"updated_plan_objective_json\": \"{\\\"id\\\": 3, \\\"objective\\\": \\\"Research pulse shaping/process time trade-offs\\\", \\\"rationale\\\": \\\"Need to explain detector electronics basis for process time recommendations\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\\\", \\\"evaluation\\\": \\\"Good evidence on the noise components and practical trade-off.\\\"}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_0176umtLhJ54syS43ZRxDp2i",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 4, \"updated_plan_objective_json\": \"{\\\"id\\\": 4, \\\"objective\\\": \\\"Research Poisson counting statistics and Currie detection limits\\\", \\\"rationale\\\": \\\"Need to trace statistical foundations\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found Currie 1999 review paper with full derivation of detection decisions: LC = 1.645*sigma0, LD = 2*LC = 3.29*sigma0 (for alpha=beta=0.05, Gaussian), LQ = 10*sigma0. Also found Newbury 2019 CDL formula CDL = [3*NB^0.5/(NS-NB)]*CS. Rinaldi quotes Ziebold 1967 CDL formula. These trace back to Currie's 1968 Analytical Chemistry paper.\\\", \\\"evaluation\\\": \\\"Excellent coverage with primary source (Currie) and application in EDS context.\\\"}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_01LjHXC2RdKS4eFATSnriEaW",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 5, \"updated_plan_objective_json\": \"{\\\"id\\\": 5, \\\"objective\\\": \\\"Research ISO/ASTM standards and round-robin studies\\\", \\\"rationale\\\": \\\"Distinguish optima from conventions\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found ISO 22309:2011 specifies overvoltage of at least 1.8 for quantitative analysis from Tong 2026. Newbury 2015 shows that the k-ratio/matrix correction protocol achieves ~2.5% relative standard deviation accuracy based on 1975 WDS data. Guyett 2024 recommends minimum 1M counts for major elements. No specific round-robin studies for EDS parameter settings were found - these are largely physics-derived optima codified by committees.\\\", \\\"evaluation\\\": \\\"Partial coverage - clear that standards draw on physics models rather than systematic round-robin validation of parameter ranges.\\\"}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_013cjc4ZTDfJeRTWB8b8TZJn",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 6, \"updated_plan_objective_json\": \"{\\\"id\\\": 6, \\\"objective\\\": \\\"Research low-voltage microanalysis and trace-element quantification shifts\\\", \\\"rationale\\\": \\\"Need to explain how parameter optima shift for low-kV and trace analysis\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found Newbury 2019 discussion of 5 keV beam energy as lowest for all elements, requirement to use unfamiliar X-ray families (Ba M-family), challenges with absorption and surface layers. Rinaldi 2015 discusses systematic errors in transition element analysis at low kV. Wuhrer 2016 covers reduced interaction volume and shift to L/M lines. Golla-Schindler 2026 on lithium detection. Newbury shows CDL of 200-500 ppm achievable in <500s at conventional voltages.\\\", \\\"evaluation\\\": \\\"Good coverage of low-kV challenges and trace analysis capabilities.\\\"}\"}",
+                      "name": "update_plan"
+                    }
+                  },
+                  {
+                    "id": "toolu_014nQAVXyspk8reByMm6jy2f",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 7, \"updated_plan_objective_json\": \"{\\\"id\\\": 7, \\\"objective\\\": \\\"Create summary artifacts and submit final answer\\\", \\\"rationale\\\": \\\"Synthesize all findings into a comprehensive answer\\\", \\\"status\\\": \\\"in-progress\\\", \\\"result\\\": null, \\\"evaluation\\\": null}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\",\n      \"rationale\": \"Need to explain the detector electronics basis for process time recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_015goBjacFSmU7C4yFqCakTW",
+                "info": {
+                  "start_ts": 3241.663719543,
+                  "end_ts": 3241.665825024
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01LAfPYdGfcVfrw8uwURVK9w",
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+                  "start_ts": 3241.665865363,
+                  "end_ts": 3241.666327824
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+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics and Currie detection limits\",\n      \"rationale\": \"Need to trace statistical foundations\",\n      \"status\": \"completed\",\n      \"result\": \"Found Currie 1999 review paper with full derivation of detection decisions: LC = 1.645*sigma0, LD = 2*LC = 3.29*sigma0 (for alpha=beta=0.05, Gaussian), LQ = 10*sigma0. Also found Newbury 2019 CDL formula CDL = [3*NB^0.5/(NS-NB)]*CS. Rinaldi quotes Ziebold 1967 CDL formula. These trace back to Currie's 1968 Analytical Chemistry paper.\",\n      \"evaluation\": \"Excellent coverage with primary source (Currie) and application in EDS context.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_0176umtLhJ54syS43ZRxDp2i",
+                "info": {
+                  "start_ts": 3241.666356741,
+                  "end_ts": 3241.66682949
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics and Currie detection limits\",\n      \"rationale\": \"Need to trace statistical foundations\",\n      \"status\": \"completed\",\n      \"result\": \"Found Currie 1999 review paper with full derivation of detection decisions: LC = 1.645*sigma0, LD = 2*LC = 3.29*sigma0 (for alpha=beta=0.05, Gaussian), LQ = 10*sigma0. Also found Newbury 2019 CDL formula CDL = [3*NB^0.5/(NS-NB)]*CS. Rinaldi quotes Ziebold 1967 CDL formula. These trace back to Currie's 1968 Analytical Chemistry paper.\",\n      \"evaluation\": \"Excellent coverage with primary source (Currie) and application in EDS context.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards and round-robin studies\",\n      \"rationale\": \"Distinguish optima from conventions\",\n      \"status\": \"completed\",\n      \"result\": \"Found ISO 22309:2011 specifies overvoltage of at least 1.8 for quantitative analysis from Tong 2026. Newbury 2015 shows that the k-ratio/matrix correction protocol achieves ~2.5% relative standard deviation accuracy based on 1975 WDS data. Guyett 2024 recommends minimum 1M counts for major elements. No specific round-robin studies for EDS parameter settings were found - these are largely physics-derived optima codified by committees.\",\n      \"evaluation\": \"Partial coverage - clear that standards draw on physics models rather than systematic round-robin validation of parameter ranges.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01LjHXC2RdKS4eFATSnriEaW",
+                "info": {
+                  "start_ts": 3241.666854388,
+                  "end_ts": 3241.667182745
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics and Currie detection limits\",\n      \"rationale\": \"Need to trace statistical foundations\",\n      \"status\": \"completed\",\n      \"result\": \"Found Currie 1999 review paper with full derivation of detection decisions: LC = 1.645*sigma0, LD = 2*LC = 3.29*sigma0 (for alpha=beta=0.05, Gaussian), LQ = 10*sigma0. Also found Newbury 2019 CDL formula CDL = [3*NB^0.5/(NS-NB)]*CS. Rinaldi quotes Ziebold 1967 CDL formula. These trace back to Currie's 1968 Analytical Chemistry paper.\",\n      \"evaluation\": \"Excellent coverage with primary source (Currie) and application in EDS context.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards and round-robin studies\",\n      \"rationale\": \"Distinguish optima from conventions\",\n      \"status\": \"completed\",\n      \"result\": \"Found ISO 22309:2011 specifies overvoltage of at least 1.8 for quantitative analysis from Tong 2026. Newbury 2015 shows that the k-ratio/matrix correction protocol achieves ~2.5% relative standard deviation accuracy based on 1975 WDS data. Guyett 2024 recommends minimum 1M counts for major elements. No specific round-robin studies for EDS parameter settings were found - these are largely physics-derived optima codified by committees.\",\n      \"evaluation\": \"Partial coverage - clear that standards draw on physics models rather than systematic round-robin validation of parameter ranges.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis and trace-element quantification shifts\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis\",\n      \"status\": \"completed\",\n      \"result\": \"Found Newbury 2019 discussion of 5 keV beam energy as lowest for all elements, requirement to use unfamiliar X-ray families (Ba M-family), challenges with absorption and surface layers. Rinaldi 2015 discusses systematic errors in transition element analysis at low kV. Wuhrer 2016 covers reduced interaction volume and shift to L/M lines. Golla-Schindler 2026 on lithium detection. Newbury shows CDL of 200-500 ppm achievable in <500s at conventional voltages.\",\n      \"evaluation\": \"Good coverage of low-kV challenges and trace analysis capabilities.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_013cjc4ZTDfJeRTWB8b8TZJn",
+                "info": {
+                  "start_ts": 3241.667201719,
+                  "end_ts": 3241.667556316
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics and Currie detection limits\",\n      \"rationale\": \"Need to trace statistical foundations\",\n      \"status\": \"completed\",\n      \"result\": \"Found Currie 1999 review paper with full derivation of detection decisions: LC = 1.645*sigma0, LD = 2*LC = 3.29*sigma0 (for alpha=beta=0.05, Gaussian), LQ = 10*sigma0. Also found Newbury 2019 CDL formula CDL = [3*NB^0.5/(NS-NB)]*CS. Rinaldi quotes Ziebold 1967 CDL formula. These trace back to Currie's 1968 Analytical Chemistry paper.\",\n      \"evaluation\": \"Excellent coverage with primary source (Currie) and application in EDS context.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards and round-robin studies\",\n      \"rationale\": \"Distinguish optima from conventions\",\n      \"status\": \"completed\",\n      \"result\": \"Found ISO 22309:2011 specifies overvoltage of at least 1.8 for quantitative analysis from Tong 2026. Newbury 2015 shows that the k-ratio/matrix correction protocol achieves ~2.5% relative standard deviation accuracy based on 1975 WDS data. Guyett 2024 recommends minimum 1M counts for major elements. No specific round-robin studies for EDS parameter settings were found - these are largely physics-derived optima codified by committees.\",\n      \"evaluation\": \"Partial coverage - clear that standards draw on physics models rather than systematic round-robin validation of parameter ranges.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis and trace-element quantification shifts\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis\",\n      \"status\": \"completed\",\n      \"result\": \"Found Newbury 2019 discussion of 5 keV beam energy as lowest for all elements, requirement to use unfamiliar X-ray families (Ba M-family), challenges with absorption and surface layers. Rinaldi 2015 discusses systematic errors in transition element analysis at low kV. Wuhrer 2016 covers reduced interaction volume and shift to L/M lines. Golla-Schindler 2026 on lithium detection. Newbury shows CDL of 200-500 ppm achievable in <500s at conventional voltages.\",\n      \"evaluation\": \"Good coverage of low-kV challenges and trace analysis capabilities.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer\",\n      \"status\": \"in-progress\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_014nQAVXyspk8reByMm6jy2f",
+                "info": {
+                  "start_ts": 3241.667926566,
+                  "end_ts": 3241.668201184
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me create the summary artifact:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01HPJEhVJGXA7Cf94zmw4US7",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"artifact_type\": \"table\", \"description\": \"Create a comprehensive summary table of the five main SEM-EDS acquisition parameters (overvoltage ratio, dead time, process/shaping time, counting statistics/live time, and detection limit criterion), showing for each: the recommended value, the underlying physics model or derivation, the key primary literature reference, whether it represents a true optimum or an empirical convention, and how it shifts for low-voltage/trace analysis.\"}",
+                      "name": "create_artifact"
+                    }
+                  }
+                ],
+                "info": null
+              }
+            ],
+            "hide_old_env_states": false,
+            "hide_old_action_content": false,
+            "sliding_window": null
+          },
+          "next_agent_state": {
+            "tools": [
+              {
+                "type": "function",
+                "info": {
+                  "name": "paper_search",
+                  "description": "Search for papers in Google Scholar for you to look at.\n\nCan be called repeatedly with identical parameters to retrieve more results (max 2 repeats).\nA short summary of the retrieved papers will be returned, but to examine the full content of each paper,\nyou must use the gather_evidence tool.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "A Google Scholar search query, which can be a specific phrase, complete sentence,\nor general keywords, e.g. 'machine learning for immunology'. Also can be\ngiven search operators like 'author:'.",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "min_year": {
+                        "anyOf": [
+                          {
+                            "type": "integer"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "filter for minimum publication year.\nThe current year is 2026. If unsure about time range, do not set.",
+                        "title": "Min Year"
+                      },
+                      "max_year": {
+                        "anyOf": [
+                          {
+                            "type": "integer"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "filter for maximum publication year.\nThe current year is 2026. If unsure about time range, do not set.",
+                        "title": "Max Year"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "collect_cited_papers_in_evidence",
+                  "description": "Collect papers by traversing the citations of relevant papers to increase the paper count.\n\nThis tool has no effect if called when paper count or relevant papers are zero.\nThis tool will find papers that are likely to lead to more relevant evidence.\nThe papers found have a higher chance of relevance because this tool starts from relevant evidence.\nThis tool's usefulness increases with the amount of gathered evidence as there's more citations to consider.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {},
+                    "required": []
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "open_targets_search",
+                  "description": "Search for disease-target associations from OpenTargets database.\n\nAdds new disease-target association data to the state and returns top search results.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "disease_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of disease names to search for.\nUsage:\ndisease_names = [\"Alzheimer's\"] ->\n    Returns top targets for Alzheimer's\ndisease_names = [\"Alzheimer's\", \"Diabetes\"], target_names = [\"PSEN1\"] ->\n    Filters for only PSEN1-Alzheimer's/Diabetes evidence\ndisease_names = [\"Alzheimer's\"], drug_names = [\"Aducanumab\"] ->\n    Filters for Alzheimer's disease-target pairs treated by Aducanumab",
+                        "title": "Disease Names"
+                      },
+                      "target_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of target names to search for.\nUsage:\ntarget_names = [\"BACE1\"] ->\n    Returns top diseases associated with BACE1\ntarget_names = [\"BACE1\", \"APP\"], disease_names = [\"Alzheimer's\"] ->\n    Filters for only these target-Alzheimer's pairs\ntarget_names = [\"BACE1\"], drug_names = [\"Aducanumab\"] ->\n    Filters for BACE1 disease pairs treated by Aducanumab",
+                        "title": "Target Names"
+                      },
+                      "drug_names": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "List of drug names to generate or filter results.\nUsage:\ndrug_names = [\"Aducanumab\"] ->\n    Returns all disease-target pairs treated by Aducanumab\ndrug_names = [\"Aducanumab\"], disease_names = [\"Alzheimer's\"] ->\n    Filters for Alzheimer's pairs treated by Aducanumab\ndrug_names = [\"Aducanumab\"], target_names = [\"BACE1\"] ->\n    Filters for BACE1 disease pairs treated by Aducanumab",
+                        "title": "Drug Names"
+                      }
+                    },
+                    "required": []
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "create_artifact",
+                  "description": "Create an artifact that can be used in the final answer, based on information\nyou have collected so far.\n\nHow it works: the full message history thus far is passed to another LLM,\nalong with the question and your description. The LLM is tasked to create\nan artifact that matches your specifications, including a title, caption,\nand markdown content. You drive the process by specifying the type and\ndescribing what you want.\n\nOnly use this tool *after* you have gathered sufficient evidence or\ninformation to create a new artifact. Do not call this tool in parallel\nwith tools that are searching for information or evidence that would be\nnecessary to create this artifact.\n\nIt is very helpful after calls to several search tools,\nafter calls to the `gather_evidence` tool, but it is not required.\nHowever, it should be called before the `answer` tool at\nleast one time, but more may be given if specifically helpful for\nthe task, so that the `answer` tool can use the artifacts for the answer.\n\nAn artifact can be any string representable fact or list of facts,\nformatted using markdown syntax. The artifact will be generated as one of\nthe following types:\n- table: Markdown tables with rows and columns (e.g., findings, methods, molecules)\n- code_block: Code snippets in fenced code blocks\n- blockquote: Quoted text or important facts (using > prefix)\n- image: AI-generated image (chart, diagram, or visualization)\n\nEach artifact consists of:\n- A short title (3-8 words) that names what the artifact contains\n- A caption (1-2 sentences) describing what the artifact shows and why it's useful\n- Markdown content in a single element type (validated automatically with retries if needed)\n  For image type, content is a markdown image embed ``![title](data:image/png;base64,...)``,\n  embedding the PNG directly as a base64 data URL.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "artifact_type": {
+                        "description": "Artifact type to create. Must be one of: table,\ncode_block, blockquote, image.",
+                        "title": "Artifact Type",
+                        "type": "string"
+                      },
+                      "description": {
+                        "description": "Description of what you want in the artifact. Be specific\nabout what information should be included, how it should be organized,\nand what columns/sections/content you want. This guides the summary LLM.\nFor image type, describe the visual you want generated in detail.",
+                        "title": "Description",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "artifact_type",
+                      "description"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "clinical_trials_search",
+                  "description": "Search for clinical trials, with support for repeated calls and concurrent execution.\n\nWill add new clinical trials to the state, and return metadata about the number of trials found.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "The search query string. Supports complex boolean expressions, field-specific\nsearches, and query modifiers through operators. All configuration is done through\noperators in the query string.\nQuery Syntax:\n    Basic Search:\n        Simple text automatically uses default EXPANSION[Relaxation] and COVERAGE[Contains]\n        >>> \"heart attack\"\n\n    Modified Search:\n        Use operators to modify search behavior:\n        >>> 'EXPANSION[None]COVERAGE[FullMatch]\"exact phrase\"'\n        >>> 'EXPANSION[Concept]heart attack'\n\n    Field Search:\n        Specify fields using AREA operator:\n        >>> 'AREA[InterventionName]aspirin'\n        >>> 'AREA[Phase]PHASE3'\n\n    Location Search:\n        Use SEARCH operator for compound location queries:\n        >>> 'cancer AND SEARCH[Location](AREA[LocationCity]Boston AND AREA[LocationState]Massachusetts)'\n\n    Complex Boolean:\n        Combine terms with AND, OR, NOT and parentheses:\n        >>> '(cancer OR tumor) AND NOT (EXPANSION[None]pediatric OR AREA[StdAge]CHILD)'\n\n    Date Ranges:\n        Use RANGE to specify date ranges with formats like \"yyyy-MM\" or \"yyyy-MM-dd\".\n        Note that MIN and MAX can be used for open-ended ranges:\n        >>> AREA[ResultsFirstPostDate]RANGE[2015-01-01, MAX]\n\nOperators:\n    EXPANSION[type]: Controls term expansion\n        - None: Exact match only, case and accent sensitive\n        - Term: Includes lexical variants (plurals, spellings)\n        - Concept: Includes UMLS synonyms\n        - Relaxation: Relaxes adjacency requirements (default)\n        - Lossy: Allows missing partial terms\n\n    COVERAGE[type]: Controls text matching\n        - FullMatch: Must match entire field\n        - StartsWith: Must match beginning of field\n        - EndsWith: Must match end of field\n        - Contains: Must match part of field (default)\n\n    AREA[field]: Specifies field to search\n        - See Field Reference for available fields\n\n    SEARCH[type]: Groups field searches\n        - Location: Groups location-related fields\n        - Study: Groups study-related fields\n\nUsage Notes:\n    - All search expressions are implicitly OR expressions\n    - Operator precedence (highest to lowest): terms/source operators, NOT/context operators, AND, OR\n    - Use quotes for exact phrase matching: \"heart attack\"\n    - Use parentheses for grouping: (heart OR cardiac) AND attack\n    - Use backslash to escape operators: \\AND\n    - Default expansion is EXPANSION[Relaxation]\n    - Default coverage is COVERAGE[Contains]\n\nField Reference:\n    High Priority Fields (weight >= 0.8):\n        - NCTId (1.0): Trial identifier\n        - Acronym (1.0): Study acronym\n        - BriefTitle (0.89): Short title\n        - OfficialTitle (0.85): Full official title\n        - Condition (0.81): Medical condition\n        - InterventionName (0.8): Primary intervention name\n        - OverallStatus: Trial status\n\n    Medium Priority Fields (0.5-0.79):\n        - InterventionOtherName (0.75): Alternative intervention names\n        - Phase (0.65): Trial phase\n        - StdAge (0.65): Standard age groups\n        - Keyword (0.6): Study keywords\n        - BriefSummary (0.6): Short description\n        - SecondaryOutcomeMeasure (0.5): Secondary outcomes\n\n    Low Priority Fields (< 0.5):\n        - DesignPrimaryPurpose (0.3): Primary purpose of study\n        - StudyType (0.3)\n        - Various descriptive, location, and administrative fields\n\nSupported Enums:\n    Phase:\n        - EARLY_PHASE1: Early Phase 1\n        - PHASE1: Phase 1\n        - PHASE2: Phase 2\n        - PHASE3: Phase 3\n        - PHASE4: Phase 4\n        - NA: Not Applicable\n\n    StandardAge:\n        - CHILD: Child\n        - ADULT: Adult\n        - OLDER_ADULT: Older Adult\n\n    Status:\n        - RECRUITING: Currently recruiting participants\n        - ACTIVE_NOT_RECRUITING: Active but not recruiting\n        - COMPLETED: Study completed\n        - ENROLLING_BY_INVITATION: Enrolling by invitation only\n        - NOT_YET_RECRUITING: Not yet recruiting\n        - SUSPENDED: Study suspended\n        - TERMINATED: Study terminated\n        - WITHDRAWN: Study withdrawn\n        - AVAILABLE: Available\n        - NO_LONGER_AVAILABLE: No longer available\n        - TEMPORARILY_NOT_AVAILABLE: Temporarily not available\n        - APPROVED_FOR_MARKETING: Approved for marketing\n        - WITHHELD: Withheld\n        - UNKNOWN: Unknown status\n\n    StudyType:\n        - INTERVENTIONAL: Interventional studies\n        - OBSERVATIONAL: Observational studies\n        - EXPANDED_ACCESS: Expanded access studies\n\n    PrimaryPurpose:\n        - TREATMENT: Treatment\n        - PREVENTION: Prevention\n        - DIAGNOSTIC: Diagnostic\n        - ECT: Educational/Counseling/Training\n        - SUPPORTIVE_CARE: Supportive Care\n        - SCREENING: Screening\n        - HEALTH_SERVICES_RESEARCH: Health Services Research\n        - BASIC_SCIENCE: Basic Science\n        - DEVICE_FEASIBILITY: Device Feasibility\n        - OTHER: Other\n\n    InterventionType:\n        - BEHAVIORAL: Behavioral interventions\n        - BIOLOGICAL: Biological interventions\n        - COMBINATION_PRODUCT: Combination product interventions\n        - DEVICE: Device interventions\n        - DIAGNOSTIC_TEST: Diagnostic test interventions\n        - DIETARY_SUPPLEMENT: Dietary supplement interventions\n        - DRUG: Drug interventions\n        - GENETIC: Genetic interventions\n        - PROCEDURE: Procedure interventions\n        - RADIATION: Radiation interventions\n        - OTHER: Other interventions\n\n    DesignAllocation:\n        - RANDOMIZED: Randomized allocation\n        - NON_RANDOMIZED: Non-randomized allocation\n        - NA: Not applicable\n\n    InterventionalAssignment:\n        - SINGLE_GROUP: Single group assignment\n        - PARALLEL: Parallel assignment\n        - CROSSOVER: Crossover assignment\n        - FACTORIAL: Factorial assignment\n        - SEQUENTIAL: Sequential assignment\n\n    ObservationalModel:\n        - COHORT: Cohort\n        - CASE_CONTROL: Case-Control\n        - CASE_ONLY: Case-Only\n        - CASE_CROSSOVER: Case-Crossover\n        - ECOLOGIC_OR_COMMUNITY: Ecologic or Community\n        - FAMILY_BASED: Family-Based\n        - DEFINED_POPULATION: Defined Population\n        - NATURAL_HISTORY: Natural History\n        - OTHER: Other\n\n    DesignMasking:\n        - NONE: None (Open Label)\n        - SINGLE: Single\n        - DOUBLE: Double\n        - TRIPLE: Triple\n        - QUADRUPLE: Quadruple\n\n    WhoMasked:\n        - PARTICIPANT: Participant\n        - CARE_PROVIDER: Care Provider\n        - INVESTIGATOR: Investigator\n        - OUTCOMES_ASSESSOR: Outcomes Assessor",
+                        "title": "Query",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "patent_search",
+                  "description": "Search for patents to increase the patent count.\n\nRepeat previous calls with the same query to continue a search.\nOnly repeat a maximum of three times.\nThis tool can be called concurrently.\nThis tool introduces novel patents, so invoke it when just beginning\nor when unsatisfied with the current evidence.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "A search query for patents (using Google Patents). Never include temporal\nfilters here (e.g. specific years or dates); instead use the `after` and `before`\narguments. Never include author filters here; instead use the `inventor` argument.\nSupports the following syntax, but they can be brittle and are not preferred; try\nsimple queries where possible:\n- Boolean operators: AND (default), OR, and - (NOT)\n- Exact phrases: \"quoted text\"\n- Proximity: NEAR/x, ADJ/x (ordered), WITH (20 words), SAME (200 words)\n- Field search: TI=(title), AB=(abstract), CL=(claims)\n- CPC codes: cpc:A01B or CPC=B60R22/low (includes children)\n- Wildcards: ? (0-1 char), * (0+ chars), # (exactly 1 char)\n- Chemistry: exact molecule names, SSS=molecule (substructure),\n  ~molecule (similar), SMILES strings, SMARTS=pattern, InChI keys,\n  CL=~molecule (chemistry in claims)",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "after": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Minimum patent date. Format: YYYYMMDD.\nExample: '20150101' for patents after Jan 1, 2015.",
+                        "title": "After"
+                      },
+                      "before": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Maximum patent date. Format: YYYYMMDD.\nExample: '20200101' for patents before Jan 1, 2020.",
+                        "title": "Before"
+                      },
+                      "date_type": {
+                        "default": "publication",
+                        "description": "Type of date that after and before refer to. Must be either 'publication'\nor 'filing'. Only necessary to set if after and/or before are set.",
+                        "title": "Date Type",
+                        "type": "string"
+                      },
+                      "inventor": {
+                        "anyOf": [
+                          {
+                            "type": "string"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "Filter by inventor name(s). Comma-separated for multiple.",
+                        "title": "Inventor"
+                      }
+                    },
+                    "required": [
+                      "query"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "create_plan",
+                  "description": "Create a plan for to construct a thorough and accurate answer.\n\nDecompose the input task into a set of sub-objectives that need to\nbe met in order to form the answer. Subsequently, when working on solving\nthe query, you can focus on these objectives one by one. Note that the\n`update_plan` tool allows you to change the objectives if needed.\n\nIn addition to the objectives you deem necessary, add one final objective\nto call the `answer` tool with your final answer, so that you do not\nforget to submit your answer.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "plan_json": {
+                        "description": "A JSON string representing the plan. It should be a dictionary\nwith top-level key \"objectives\", whose value is a list of objectives.\nEach objective should be a dictionary with the following keys:\n- \"id\": (int) an integer id for the plan objective\n- \"objective\": (str) a human readable description of the objective's goal\n- \"rationale\": (str) a human readable rationale\n    describing why this objective is necessary and appropriate for the query.\n- \"status\": (str) updated task status, default to pending,\n    one of: pending, in-progress, or completed.\n    \"pending\" is yet to be started,\n    \"in-progress\" is the current objective being solved,\n    \"completed\" is successfully completed with acceptance criteria met.\n- \"result\": (str|None) The result of the objective, default to None.\n- \"evaluation\": (str|None) Description of why the objective result\n    meets the criteria for being complete. Default to None.",
+                        "title": "Plan Json",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "plan_json"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "update_plan",
+                  "description": "Update the plan for a specific or new objective using a JSON string to create or\nreplace the existing objective.\n\nThe updated_json should be a JSON string representing a single plan objective object.\n\nYou may use this tool to update an objective, create a new one, or change\nstrategy if the current plan is not working. Only change strategy significantly\nas a last resort, after trying very hard to make the current plan work.\n\nOnly mark an objective as completed if you are absolutely sure that it has been fully\nmet. If it is only partially met, you may add additional objectives to the plan for\nwhat is missing.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "plan_objective_id": {
+                        "description": "The id of the objective to update.",
+                        "title": "Plan Objective Id",
+                        "type": "integer"
+                      },
+                      "updated_plan_objective_json": {
+                        "description": "A JSON string representing the updated objective.\nIt should be a dictionary with the with the following keys:\n- \"id\": (int) an integer id matching plan_objective_id, if not found, a new objective is created.\n- \"objective\": (str) a human readable description of the objective's goal\n- \"rationale\": (str) a human readable rationale\n    describing why this objective is necessary and appropriate for the query.\n- \"status\": (str) updated task status, default to pending,\n    one of: pending, in-progress, or completed.\n    \"pending\" is yet to be started,\n    \"in-progress\" is the current objective being solved,\n    \"completed\" is successfully completed with acceptance criteria met.\n- \"result\": (str|None) The result of the objective, default to None.\n- \"evaluation\": (str|None) Description of why the objective result\n    meets the criteria for being complete. Default to None.",
+                        "title": "Updated Plan Objective Json",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "plan_objective_id",
+                      "updated_plan_objective_json"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "gather_evidence",
+                  "description": "Given a specific question, gather evidence from full-text of documents that have been retrieved by\nprevious tool calls.\n\nHere is how the tool works: the provided question is posed to all texts retrieved thus far\nby other tools. An LLM sees each text independently and is prompted to find information relevant\nto the question.\n\nThat is, we sample evidence `e \\sim LLM(prompt, text, q)` for each text. We only return pieces of\nevidence `e` that are sufficiently relevant to the question; if the text is irrelevant, then `e`\nis not included in the final response of this tool. Note that this LLM does not see the conversation\nhistory thus far, only the question and each text. Note that it only sees text, no images or other\nmedia from the contents (though tables and formulae may be parseable in some cases).\n\nThink of this tool as an efficient way to deeply scan all retrieved documents for evidence. It\nis complementary to the `read_text` tool, which can be used to directly inspect a subset of the\nretrieved documents.\n\nA valuable time to invoke this tool is after another tool finds potentially relevant documents.\nFeel free to invoke this tool in parallel with other tools, but do not call this tool in parallel with itself.\nOnly invoke this tool when the document count is above zero, or this tool will be useless.\n\nIf you call this tool 2+ times and repeatedly get 'No relevant evidence found',\nconsider whether the answer might be in visual content (figures/tables) rather than text,\nand use appropriate tools if available to access that content.\n\nOnce you receive evidence from this tool:\n\n1. Read Carefully: Don't skim. The evidence may contain multiple similar terms\n   or values\u2014make sure you identify the RIGHT one.\n\n2. For Comparative Questions: If the question asks \"which X has greatest Y\",\n   check that the evidence includes information about ALL relevant X options, not\n   just one or two. If you only see partial information, gather more evidence.\n\n3. Check for Noise: Verify that numbers or terms aren't just metadata\n   (page numbers, reference IDs, dates). Look for the value in meaningful\n   scientific context.\n\n4. Context Matters: A term appearing 71 times doesn't mean it's always the answer.\n   Verify which occurrence actually answers the question asked.\n\nIf the evidence doesn't clearly answer the question, gather more evidence before\nconcluding. Don't guess based on partial information.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "question": {
+                        "description": "Specific question to gather evidence for.",
+                        "title": "Question",
+                        "type": "string"
+                      },
+                      "text_name_focus_list": {
+                        "anyOf": [
+                          {
+                            "items": {
+                              "type": "string"
+                            },
+                            "type": "array"
+                          },
+                          {
+                            "type": "null"
+                          }
+                        ],
+                        "default": null,
+                        "description": "if there are known text names that are relevant to the question,\nyou can specify them here. This will ensure that the tool will look at these text names\nfirst, and then look at the rest of the evidence. If left as `None`, an embedding\nsearch will be performed on underlying content to find most relevant texts.",
+                        "title": "Text Name Focus List"
+                      }
+                    },
+                    "required": [
+                      "question"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "read_text",
+                  "description": "Given a list of text names, read their contents.\n\nThis tool is valuable to read the full contents of specific parts of documents,\ncomplementing the `gather_evidence` tool's indirect approach.\nThis can be an especially useful tool if `gather_evidence` does not find evidence,\nbut you think it is very likely that specific documents are still relevant to the question.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "text_name_list": {
+                        "description": "A list of up to 10 text names to read.\nThese text names can be any valid text names retrieved by other tools.",
+                        "items": {
+                          "type": "string"
+                        },
+                        "title": "Text Name List",
+                        "type": "array"
+                      }
+                    },
+                    "required": [
+                      "text_name_list"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "view_images",
+                  "description": "Retrieve images from a document.\n\nUse this tool when you need to see figures, tables, or other visual content.\nThe tool works by asking a weaker LLM agent to scan through the document, looking for\nvisual content matching the query you provide. When the agent finds matches, it will\ncrop the page to the relevant region. It can be tasked to return multiple images,\nif desired. Note that the weaker LLM may be worse at *understanding* images than\nyou, so double-check its conclusions about the returned images. It is also stateless,\ni.e. it will not remember what you have asked it to find in the past.\n\nUse this tool carefully. It is difficult to retrieve images, and the images\nthemselves will fill up your context window quickly. Here are some guidelines:\n1. ALWAYS use this tool if the question explicitly mentions 'Table X' or 'Figure Y'.\n   These questions require visual content and cannot be answered with text alone.\n2. Use this tool as a fallback when gather_evidence fails repeatedly (2+ times\n   returning 'No relevant evidence'). This suggests the answer may be in visual content.\n3. When gather_evidence returns text mentioning 'see Figure X' or 'shown in Table Y',\n   you should call this tool to examine that specific visual reference.\n4. Only call this tool after directly inspecting relevant text with read_text\n   to confirm the document likely contains the visual you need.\n5. Don't use this tool in a broad-spectrum way (don't call on many documents\n   just to see what might be relevant).\n6. Never call this tool in parallel with itself.\n7. Users like visual evidence, so call this tool at least once before answering so you\n   can provide some image citations in the answer. Add this to your plan so you do not forget.\n   For images to be presented to the user, they must be cited in the final answer after retrieval\n   by this tool. You may ignore this instruction if the request is for the question is asking\n   for a specific piece of information and is not an open-ended research question.\n8. NEVER cite full-page images in your final answer, unless they are full-page panels figures or\n   tables. Cite relevant cropped regions if available, otherwise consider calling this tool again\n   to find a smaller region that answers the query.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "query": {
+                        "description": "Query to search for visual content in the document. If you know the specific\nfigure/table/formula you are looking for, you can specify it here (e.g. \"find me\nFigure 3\" or \"extract the table on page 10\"). You can also request based on content\n(e.g. \"find me all volcano plots of gene X\" or \"I need the formula for the growth rate\").\nYou can even include explicit instructions for the LLM agent to follow (if helpful, not\nnecessarily required). The more specific and clear your query is here, the higher the\nchance of success.",
+                        "title": "Query",
+                        "type": "string"
+                      },
+                      "text_name": {
+                        "description": "Name of a text chunk (e.g., 'smith2023example pages 1-5').",
+                        "title": "Text Name",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "query",
+                      "text_name"
+                    ]
+                  }
+                }
+              },
+              {
+                "type": "function",
+                "info": {
+                  "name": "answer",
+                  "description": "Submit your final answer to the user. You MUST call this tool on your final answer.\nIf you mark all objectives as completed but have not yet called this tool, then\nthe answer will not be submitted. Note that this tool should only be called once, as it\nimmediately terminates the run and submits the answer.\n\nWrite an answer based on the evidence from gather_evidence results in message history.\nIf the context provides insufficient information, provide a partial answer and explain\nwhy it is partial (e.g. the question is currently an open question in the field,\nyou were unable to obtain certain papers, etc.).\n\nFor each part of your answer, indicate which sources most support it via citation IDs at\nthe end of sentences, like (pqac-0000ABCD).\nYou are only allowed to cite available context IDs, indicated in previous messages by \"Context IDs that may be cited:\".\n## Valid citation examples, only use comma/space delimited parentheticals:\n\n- (pqac-0000ABCD, pqac-0000EFGH)\n- (pqac-0000IJKL)\n\n## Invalid citation examples:\n\n- (pqac-0000ABCD and pqac-0000EFGH)\n- (pqac-0000ABCD;pqac-0000EFGH)\n- (pqac-0000ABCD-pqac-0000EFGH)\n- pqac-0000ABCD and pqac-0000EFGH\n- Example's work pqac-0000ABCD\n- (pages pqac-0000ABCD)\n- ![description](pqac-0000ABCD)\n- ()\n\nDo not concatenate citation ids, just use them as-is.\n\nWhen writing your answer, embed artifacts if relevant artifacts have been previously\ncreated by the `create_artifact` tool. To embed an artifact, simply include this in your\nanswer, on its own line and without any additional formatting (i.e. no backticks, code fences,\nquotes, additional tags, etc.).\nAlways provide at least some introductory sentence or paragraph before referring to an artifact,\nso that the artifact is properly contextualized.\nHere is an example reference to an artifact with ID \"artifact-XY\":\n<artifact id=\"artifact-XY\"/>\n\nValid artifact IDs are indicated in previous messages by 'Artifact IDs that may be injected into the answer:'.\n\n\nDouble-check your answer:\n\n1. Evidence Match: Re-read the specific evidence snippets you're citing. Does your\n   answer actually match what they say? Don't rely on memory from 20+ messages ago.\n\n2. For Comparative Questions (\"which X has greatest/maximum/highest Y\"):\n   - Did you examine ALL options mentioned in the evidence?\n   - Did you explicitly compare their values?\n   - Example: If evidence mentions \"Pancreatic: 0.92, Liver: 0.85, Lung: 0.78\",\n     verify you compared all three, not just two.\n\n3. For Specific Value Questions (\"How many\", \"What is the\", specific terms):\n   - Does the exact value you're stating appear in the evidence?\n   - Are you extracting from the right context (not noise like page numbers)?\n\n4. Sanity Check: Read your answer. Does it directly address what was asked?\n\nDon't use Markdown image syntax like ![...](...) to reference media in your answer,\nbecause media get automatically linked by the system based on your answer's citations.\n\nWrite in the style of a scientific article, with concise sentences and\ncoherent paragraphs. This answer will be used directly,\nso do not add any extraneous information.",
+                  "parameters": {
+                    "type": "object",
+                    "properties": {
+                      "answer": {
+                        "description": "valid answer, cited with citation IDs.",
+                        "title": "Answer",
+                        "type": "string"
+                      }
+                    },
+                    "required": [
+                      "answer"
+                    ]
+                  }
+                }
+              }
+            ],
+            "messages": [
+              {
+                "role": "user",
+                "content": "Use the tools to answer the question: How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).\n\nStart by making a plan, and update the plan as you go. Your answer will be returned to the user when all plan objectives are completed. Be thorough and ensure your evidence matches the user's question.",
+                "info": null
+              },
+              {
+                "role": "assistant",
+                "content": "\n\nI'll create a comprehensive plan to address this multi-faceted question about the derivation of SEM-EDS acquisition parameters.",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01LwY3zgz1Vt5ca3jNesx7YK",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_json\": \"{\\n  \\\"objectives\\\": [\\n    {\\n      \\\"id\\\": 1,\\n      \\\"objective\\\": \\\"Research the ionization cross-section physics (Bethe formulation, Green & Cosslett measurements) and overvoltage ratio optimization, including competing effects from electron range (Kanaya-Okayama) and phi(rho-z) models (Castaing)\\\",\\n      \\\"rationale\\\": \\\"Need to trace the physics basis for the U0 ~ 2-3 recommendation\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 2,\\n      \\\"objective\\\": \\\"Research dead-time models (paralyzable/non-paralyzable) and the derivation of the 20-40% dead-time guidance for optimal throughput\\\",\\n      \\\"rationale\\\": \\\"Need to explain the counting-rate optimization that yields the dead-time recommendation\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 3,\\n      \\\"objective\\\": \\\"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\\\",\\n      \\\"rationale\\\": \\\"Need to explain the detector electronics basis for process time recommendations\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 4,\\n      \\\"objective\\\": \\\"Research Poisson counting statistics for precision (10^4 counts \\u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\\\",\\n      \\\"rationale\\\": \\\"Need to trace the statistical foundations of count-time and detection-limit recommendations\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 5,\\n      \\\"objective\\\": \\\"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\\\",\\n      \\\"rationale\\\": \\\"Need to distinguish genuine optima from committee conventions\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 6,\\n      \\\"objective\\\": \\\"Research low-voltage microanalysis (\\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\\\",\\n      \\\"rationale\\\": \\\"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\\u03b1 in AlSi10Mg at 5 kV\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    },\\n    {\\n      \\\"id\\\": 7,\\n      \\\"objective\\\": \\\"Create summary artifacts and submit final answer\\\",\\n      \\\"rationale\\\": \\\"Synthesize all findings into a comprehensive answer with proper citations\\\",\\n      \\\"status\\\": \\\"pending\\\",\\n      \\\"result\\\": null,\\n      \\\"evaluation\\\": null\\n    }\\n  ]\\n}\"}",
+                      "name": "create_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Plan registered and formatted correctly, with some modifications:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research the ionization cross-section physics (Bethe formulation, Green & Cosslett measurements) and overvoltage ratio optimization, including competing effects from electron range (Kanaya-Okayama) and phi(rho-z) models (Castaing)\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models (paralyzable/non-paralyzable) and the derivation of the 20-40% dead-time guidance for optimal throughput\",\n      \"rationale\": \"Need to explain the counting-rate optimization that yields the dead-time recommendation\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\",\n      \"rationale\": \"Need to explain the detector electronics basis for process time recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "create_plan",
+                "tool_call_id": "toolu_01LwY3zgz1Vt5ca3jNesx7YK",
+                "info": {
+                  "start_ts": 2536.116590445,
+                  "end_ts": 2536.119787929
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+              {
+                "role": "assistant",
+                "content": null,
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01MNW17Avg6HRHVjWYkr5euV",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"plan_objective_id\": 1, \"updated_plan_objective_json\": \"{\\\"id\\\": 1, \\\"objective\\\": \\\"Research ionization cross-section physics and overvoltage ratio optimization\\\", \\\"rationale\\\": \\\"Need to trace the physics basis for the U0 ~ 2-3 recommendation\\\", \\\"status\\\": \\\"in-progress\\\", \\\"result\\\": null, \\\"evaluation\\\": null}\"}",
+                      "name": "update_plan"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"in-progress\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models (paralyzable/non-paralyzable) and the derivation of the 20-40% dead-time guidance for optimal throughput\",\n      \"rationale\": \"Need to explain the counting-rate optimization that yields the dead-time recommendation\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\",\n      \"rationale\": \"Need to explain the detector electronics basis for process time recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01MNW17Avg6HRHVjWYkr5euV",
+                "info": {
+                  "start_ts": 2544.693267786,
+                  "end_ts": 2544.694202496
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Let me launch multiple parallel searches to efficiently gather evidence on all the key topics:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_011mGuD8hMcrUFocjkLDpN6U",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Bethe ionization cross-section overvoltage ratio electron probe microanalysis\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_01WewFbrkPCiA6LqG8T7fbrT",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Green Cosslett ionization cross-section electron bombardment X-ray production\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_01F9PtJgwBy482vzc38PHvS6",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Kanaya Okayama electron range penetration depth microanalysis\"}",
+                      "name": "paper_search"
+                    }
+                  },
+                  {
+                    "id": "toolu_01JTZVfeVBDWDe4iq2ZzHCdN",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"Castaing phi rho z depth distribution X-ray microanalysis tracer experiments\"}",
+                      "name": "paper_search"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Electron Probe Microanalysis: A Review of the Past, Present, and Future\nValid Text Names:\n'rinaldi2015electronprobemicroanalysis pages 1-2', 'rinaldi2015electronprobemicroanalysis pages 2-4', 'rinaldi2015electronprobemicroanalysis pages 4-5', 'rinaldi2015electronprobemicroanalysis pages 5-7', 'rinaldi2015electronprobemicroanalysis pages 7-8', 'rinaldi2015electronprobemicroanalysis pages 8-10', 'rinaldi2015electronprobemicroanalysis pages 10-12', 'rinaldi2015electronprobemicroanalysis pages 12-13', 'rinaldi2015electronprobemicroanalysis pages 13-14', 'rinaldi2015electronprobemicroanalysis pages 14-15', 'rinaldi2015electronprobemicroanalysis pages 15-16', 'rinaldi2015electronprobemicroanalysis pages 16-17'\n\nBibTex:\n@article{rinaldi2015electronprobemicroanalysis,\n    author = \"Rinaldi, Romano and Llovet, Xavier\",\n    title = \"Electron Probe Microanalysis: A Review of the Past, Present, and Future\",\n    year = \"2015\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"21\",\n    pages = \"1053-1069\",\n    month = \"May\",\n    doi = \"10.1017/s1431927615000409\",\n    url = \"https://doi.org/10.1017/s1431927615000409\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"5\",\n    issn = \"1431-9276\"\n}\n\n\nRelevant Snippet:\n\u2026 As an example, the effective ionization range of 20 keV electrons incident on a light matrix \u2026 the analysis at low over-voltage is the low count rates and peak-to-background ratios, which \u2026\n\n\nUnobtainable Papers:\nRod Packwood. A comprehensive theory of electron probe microanalysis. ArXiv, pages 83-104, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_6, doi:10.1007/978-1-4899-2617-3\\_6.\nKFJ Heinrich and D Newbury. Electron probe quantitation. ArXiv, Jan 2013. URL: https://doi.org/10.1007/978-1-4899-2617-3, doi:10.1007/978-1-4899-2617-3.\nKenji Murata, Masatoshi Kotera, and Koichi Nagami. Quantitative electron microprobe analysis of thin films on substrates with a new monte carlo simulation. Journal of Applied Physics, 54:1110-1114, Feb 1983. URL: https://doi.org/10.1063/1.332127, doi:10.1063/1.332127.\nPeter Duncumb. Quantitative analysis with the electron microprobe. the first 50 years and beyond. Journal of Analytical Atomic Spectrometry, 14:357-366, Jan 1999. URL: https://doi.org/10.1039/a807315e, doi:10.1039/a807315e.\nS.J.B reed. The present state of quantitative electron probe microanalysis. Reviews of Physics in Technology, 2:92-115, Oct 1971. URL: https://doi.org/10.1088/0034-6683/2/2/i02, doi:10.1088/0034-6683/2/2/i02.\nPeter Rez. Electron ionization cross sections for atomic subshells. Microscopy and Microanalysis, 9:42-53, Jan 2003. URL: https://doi.org/10.1017/s1431927603030083, doi:10.1017/s1431927603030083.\nC. J. Powell. Cross sections for ionization of inner-shell electrons by electrons. Reviews of Modern Physics, 48:33-47, Jan 1976. URL: https://doi.org/10.1103/revmodphys.48.33, doi:10.1103/revmodphys.48.33.\nG Love, M G Cox, and V D Scott. A versatile atomic number correction for electron-probe microanalysis. Journal of Physics D: Applied Physics, 11:7-21, Jan 1978. URL: https://doi.org/10.1088/0022-3727/11/1/004, doi:10.1088/0022-3727/11/1/004.\nH. Yakowitz. Methods of quantitative x-ray analysis used in electron probe microanalysis and scanning electron microscopy. ArXiv, pages 327-372, Jan 1975. URL: https://doi.org/10.1007/978-1-4613-4422-3\\_9, doi:10.1007/978-1-4613-4422-3\\_9.\nCedric J. Powell, Xavier Llovet, and Francesc Salvat. Use of the bethe equation for inner-shell ionization by electron impact. Journal of applied physics, May 2016. URL: https://doi.org/10.1063/1.4948700, doi:10.1063/1.4948700.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=4 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_011mGuD8hMcrUFocjkLDpN6U",
+                "info": {
+                  "start_ts": 2555.194194733,
+                  "end_ts": 2588.119970315
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nV Horvat and R L Watson. Target-atom k-shell ionization by binary-encounter electrons. Journal of Physics B: Atomic, Molecular and Optical Physics, 34:777-786, Feb 2001. URL: https://doi.org/10.1088/0953-4075/34/5/307, doi:10.1088/0953-4075/34/5/307.\nC. Hombourger. An empirical expression for k-shell ionization cross section by electron impact. Journal of Physics B, 31:3693-3702, Aug 1998. URL: https://doi.org/10.1088/0953-4075/31/16/020, doi:10.1088/0953-4075/31/16/020.\nM Green and V E Cosslett. The efficiency of production of characteristic x-radiation in thick targets of a pure element. ArXiv, 78:1206-1214, Dec 1961. URL: https://doi.org/10.1088/0370-1328/78/6/315, doi:10.1088/0370-1328/78/6/315.\nK. Shima, M. Okuda, E. Suzuki, T. Tsubota, and T. Mikumo. L\u03b1 x\u2010ray production efficiency from z=50\u201382 thick target elements by electron impacts from threshold energy to 30 kev. Journal of Applied Physics, 54:1202-1208, Mar 1983. URL: https://doi.org/10.1063/1.332200, doi:10.1063/1.332200.\nStephen M. Seltzer. Cross sections for bremsstrahlung production and electron-impact ionization. ArXiv, 38:81-114, Jan 1988. URL: https://doi.org/10.1007/978-1-4613-1059-4\\_4, doi:10.1007/978-1-4613-1059-4\\_4.\nD. B. Brown and R. E. Ogilvie. Efficiency of production of characteristic x radiation from pure elements bombarded by electrons. Journal of Applied Physics, 35:309-314, Feb 1964. URL: https://doi.org/10.1063/1.1713305, doi:10.1063/1.1713305.\nH. V. Rahangdale, M. Guerra, P. K. Das, S. De, J. P. Santos, D. Mitra, and S. Saha. Determination of subshell-resolved l-shell-ionization cross sections of gold induced by 15-40-kev electrons. Physical Review A, 89:052708, May 2014. URL: https://doi.org/10.1103/physreva.89.052708, doi:10.1103/physreva.89.052708.\nChanghuan Tang, Zhengming Luo, Zhu An, Fuqing He, Xiufeng Peng, and Xianguan Long. The atomic k- and l-shell ionization cross-sections by electron impact. ArXiv, pages 233-236, Jan 2002. URL: https://doi.org/10.1007/978-1-4419-8696-2\\_41, doi:10.1007/978-1-4419-8696-2\\_41.\nM. Green. A monte carlo calculation of the spatial distribution of characteristic x-ray production in a solid target. ArXiv, 82:204-215, Aug 1963. URL: https://doi.org/10.1088/0370-1328/82/2/307, doi:10.1088/0370-1328/82/2/307.\nChanghuan Tang, Zhu An, Zhengming Luo, and Mantian Liu. Measurements of germanium <i>k</i>-shell ionization cross sections and tin <i>l</i>-shell x-ray production cross sections by electron impact. May 2002. URL: https://doi.org/10.1063/1.1470248, doi:10.1063/1.1470248.\nXavier Llovet, Cedric J. Powell, Francesc Salvat, and Aleksander Jablonski. Cross sections for inner-shell ionization by electron impact. Journal of Physical and Chemical Reference Data, 43:013102, Jan 2014. URL: https://doi.org/10.1063/1.4832851, doi:10.1063/1.4832851.\nChang-huan Tang, Zheng-ming Luo, Zhu An, and Tai-hua Li. Measurement of zinc k-shell ionization cross sections by electron impact. Chinese Physics Letters, 16:505-507, Jul 1999. URL: https://doi.org/10.1088/0256-307x/16/7/013, doi:10.1088/0256-307x/16/7/013.\nR. Akselsson and T. B. Johansson. X-ray production by 1.5\u201311 mev protons. Zeitschrift f\u00fcr Physik, 266:245-255, Aug 1974. URL: https://doi.org/10.1007/bf01668816, doi:10.1007/bf01668816.\nM Green and V E Cosslett. Measurements of k, l and m shell x-ray production efficiencies. Journal of Physics D: Applied Physics, 1:425-436, Apr 1968. URL: https://doi.org/10.1088/0022-3727/1/4/303, doi:10.1088/0022-3727/1/4/303.\nSilvina P. Limandri, M. A. Z. Vasconcellos, Ruth Hinrichs, and Jorge C. Trincavelli. Experimental determination of cross sections for k-shell ionization by electron impact for c, o, al, si, and ti. Physical Review A, 86:042701, Oct 2012. URL: https://doi.org/10.1103/physreva.86.042701, doi:10.1103/physreva.86.042701.\nN A Dyson. The production of characteristic x-rays by proton bombardment, and the ratio of characteristic to continuous radiation. Journal of Physics B, 6:562-572, Mar 1973. URL: https://doi.org/10.1088/0022-3700/6/3/025, doi:10.1088/0022-3700/6/3/025.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=4 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_01WewFbrkPCiA6LqG8T7fbrT",
+                "info": {
+                  "start_ts": 2555.227472424,
+                  "end_ts": 2587.414488138
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nSusumu Imashuku and Issei Narita. Effect of secondary fluorescence in thin\u2010film thickness on compositional determination using electron probe microanalysis. X-Ray Spectrometry, 55:184-189, Sep 2026. URL: https://doi.org/10.1002/xrs.70040, doi:10.1002/xrs.70040.\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Backscattered Electrons, pages 15-28. Springer New York, Nov 2017. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_2, doi:10.1007/978-1-4939-6676-9\\_2.\nYugo Kubo and Kotaro Hamada. Combination of high spatial resolution and low minimum detection limit using thinned specimens in cutting-edge electron probe microanalysis. Ultramicroscopy, 157:48-56, Oct 2015. URL: https://doi.org/10.1016/j.ultramic.2015.05.019, doi:10.1016/j.ultramic.2015.05.019.\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Low beam energy sem. ArXiv, pages 165-172, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_11, doi:10.1007/978-1-4939-6676-9\\_11.\nK. Kanaya and S. Ono. The energy dependence of a diffusion model of an electron probe into solid targets. Journal of Physics D, 11:1495-1498, Aug 1978. URL: https://doi.org/10.1088/0022-3727/11/11/008, doi:10.1088/0022-3727/11/11/008.\nTakahiro Nishihata, Mayuka Osaki, Maki Tanaka, Takuma Yamamoto, Akira Hamaguchi, Chihiro Ida, and Yusaku Suzuki. Depth measurement technique for extremely deep holes using back-scattered electron images with high voltage cd-sem. Metrology, Inspection, and Process Control for Microlithography XXXIII, 10959:109591B-109591B-9, Mar 2019. URL: https://doi.org/10.1117/12.2514799, doi:10.1117/12.2514799.\nMakoto Suzuki, Kazuhiro Kumagai, Takashi Sekiguchi, Alan M. Cassell, Tsutomu Saito, and Cary Y. Yang. Secondary electron emission from freely supported nanowires. Journal of Applied Physics, 104:114306, Dec 2008. URL: https://doi.org/10.1063/1.3032910, doi:10.1063/1.3032910.\nLai Chin Yung and Cheong Choke Fei. Verification of the thin film metal layer thickness by energy dispersive x-ray. 2015 IEEE Regional Symposium on Micro and Nanoelectronics (RSM), pages 1-4, Dec 2015. URL: https://doi.org/10.1109/rsm.2015.7355004, doi:10.1109/rsm.2015.7355004.\nJ. Seiter, Erich A. M\u00fcller, H. Blank, Helge Gehrke, Doris Marko, and D. Gerthsen. Backscattered electron sem imaging of cells and determination of the information depth. Journal of Microscopy, 254:75-83, May 2014. URL: https://doi.org/10.1111/jmi.12120, doi:10.1111/jmi.12120.\nMakoto Suzuki. Image formation mechanisms of scanning electron microscopy for characterization of nanoscale materials. Jan 2009. URL: https://doi.org/10.13140/2.1.1120.5765, doi:10.13140/2.1.1120.5765.\nMitsuo Suga and Yusuke Hirabayashi. Physical basics of scanning electron microscopy in volume electron microscopy. Microscopy, 74:201-214, Mar 2025. URL: https://doi.org/10.1093/jmicro/dfaf016, doi:10.1093/jmicro/dfaf016.\nK. Fleischer, M. Toth, M. Phillips, Jin Zou, Guoliang Li, and S. Chua. Depth profiling of gan by cathodoluminescence microanalysis. Feb 1999. URL: https://doi.org/10.1063/1.123460, doi:10.1063/1.123460.\nYuji Tanaka, Takako Yamashita, and Masayasu Nagoshi. Quantitative fe-epma measurement of formation and inhibition of carbon contamination on fe for trace carbon analysis. Microscopy, 66 2:68-77, Nov 2017. URL: https://doi.org/10.1093/jmicro/dfw102, doi:10.1093/jmicro/dfw102.\nK. Kanaya and S. Okayama. Penetration and energy-loss theory of electrons in solid targets. Journal of Physics D, 5:43-58, Jan 1972. URL: https://doi.org/10.1088/0022-3727/5/1/308, doi:10.1088/0022-3727/5/1/308.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=4 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_01F9PtJgwBy482vzc38PHvS6",
+                "info": {
+                  "start_ts": 2555.259600847,
+                  "end_ts": 2587.619946758
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Quantitative Measurement of Iron-Silicides by EPMA Using the Fe L\u03b1 and L\u03b2 X-ray Lines: A New Twist to an Old Approach\nValid Text Names:\n'moy2019quantitativemeasurementof pages 1-2', 'moy2019quantitativemeasurementof pages 2-3', 'moy2019quantitativemeasurementof pages 3-4', 'moy2019quantitativemeasurementof pages 4-5', 'moy2019quantitativemeasurementof pages 5-6', 'moy2019quantitativemeasurementof pages 6-7', 'moy2019quantitativemeasurementof pages 7-9', 'moy2019quantitativemeasurementof pages 9-10', 'moy2019quantitativemeasurementof pages 10-11', 'moy2019quantitativemeasurementof pages 10-10'\n\nBibTex:\n@article{moy2019quantitativemeasurementof,\n    author = \"Moy, Aur\u00e9lien and Fournelle, John and von der Handt, Anette\",\n    title = \"Quantitative Measurement of Iron-Silicides by EPMA Using the Fe L\u03b1 and L\u03b2 X-ray Lines: A New Twist to an Old Approach\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"664-674\",\n    month = \"Apr\",\n    doi = \"10.1017/s1431927619000436\",\n    url = \"https://doi.org/10.1017/s1431927619000436\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"3\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nAbstract The recent availability of Schottky-type field emission electron microprobes provides incentive to consider analyzing micrometer-sized features. Yet, to quantify sub-micrometer-sized features, the electron interaction volume must be reduced by decreasing accelerating voltage. However, the K lines of the transition elements (e.g., Fe) then cannot be excited, and the L lines must be used. The Fe L\u03b11,2 line is the most intense of the L series but bonding effects change its atomic parameters because it involves a valence band electron transition. For successful traditional electron probe microanalysis, the mass absorption coefficient (MAC) must be accurately known, but the MAC of Fe L\u03b11,2 radiation by Fe atoms varies from one Fe-compound to another and is not well known. We show that the conventional method of measuring the MAC by an electron probe cannot be used in close proximity to absorption edges, making its accurate determination impossible. Fortunately, we demonstrate, using a set of Fe\u2013silicide compounds, that it is possible to derive an accurate calibration curve, for a given accelerating voltage and takeoff angle, which can be used to quantify Fe in Fe\u2013silicide compounds. The calibration curve can be applied to any spectrometer without calibration and gives accurate quantification results.\n\nRelevant Snippet:\n\u2026 -called phi-rho-Z function that represents the ionization depth \u2026 by Castaing mainly consists of measuring the X-ray intensity \u2026 and for a given experimental setup. The concentration of the \u2026\n\n\n---\n\n## 2. Quantitative Speciation of Heavy Metals in Soils and Sediments by Synchrotron X-ray Techniques\nValid Text Names:\n'manceau2002quantitativespeciationof pages 6-9', 'manceau2002quantitativespeciationof pages 9-11', 'manceau2002quantitativespeciationof pages 15-18', 'manceau2002quantitativespeciationof pages 18-20', 'manceau2002quantitativespeciationof pages 20-23', 'manceau2002quantitativespeciationof pages 23-25', 'manceau2002quantitativespeciationof pages 25-27', 'manceau2002quantitativespeciationof pages 31-31', 'manceau2002quantitativespeciationof pages 33-36', 'manceau2002quantitativespeciationof pages 36-39', 'manceau2002quantitativespeciationof pages 39-42', 'manceau2002quantitativespeciationof pages 42-44', 'manceau2002quantitativespeciationof pages 47-49', 'manceau2002quantitativespeciationof pages 52-55', 'manceau2002quantitativespeciationof pages 57-59', 'manceau2002quantitativespeciationof pages 59-61', 'manceau2002quantitativespeciationof pages 66-68', 'manceau2002quantitativespeciationof pages 68-70', 'manceau2002quantitativespeciationof pages 75-76', 'manceau2002quantitativespeciationof pages 79-81', 'manceau2002quantitativespeciationof pages 81-83', 'manceau2002quantitativespeciationof pages 83-84', 'manceau2002quantitativespeciationof pages 84-86', 'manceau2002quantitativespeciationof pages 86-88', 'manceau2002quantitativespeciationof pages 88-88'\n\nBibTex:\n@article{manceau2002quantitativespeciationof,\n    author = \"Manceau, A. and Marcus, M. A. and Tamura, N.\",\n    title = \"Quantitative Speciation of Heavy Metals in Soils and Sediments by Synchrotron X-ray Techniques\",\n    year = \"2002\",\n    journal = \"Reviews in Mineralogy \\& Geochemistry\",\n    volume = \"49\",\n    pages = \"341-428\",\n    doi = \"10.2138/gsrmg.49.1.341\",\n    url = \"https://doi.org/10.2138/gsrmg.49.1.341\",\n    month = \"Jan\",\n    publisher = \"Mineralogical Society of America\",\n    issue = \"1\",\n    issn = \"1529-6466\"\n}\n\n\nRelevant Snippet:\n\u2026 at the molecular level how trace metals interact and are sequestered \u2026 X-ray microdiffraction to study the mineral composition and \u2026 experiment measures the variation of a material\u2019s X-ray \u2026\n\n\n---\n\n## 3. Petrographic Microscopy with Ray Tracing and Segmentation from Multi-Angle Polarisation Whole-Slide Images\nValid Text Names:\n'zamora2023petrographicmicroscopywith pages 1-2', 'zamora2023petrographicmicroscopywith pages 2-3', 'zamora2023petrographicmicroscopywith pages 3-6', 'zamora2023petrographicmicroscopywith pages 6-9', 'zamora2023petrographicmicroscopywith pages 9-11', 'zamora2023petrographicmicroscopywith pages 11-12', 'zamora2023petrographicmicroscopywith pages 12-17', 'zamora2023petrographicmicroscopywith pages 17-19', 'zamora2023petrographicmicroscopywith pages 19-22', 'zamora2023petrographicmicroscopywith pages 22-25', 'zamora2023petrographicmicroscopywith pages 25-27', 'zamora2023petrographicmicroscopywith pages 27-29', 'zamora2023petrographicmicroscopywith pages 29-31', 'zamora2023petrographicmicroscopywith pages 31-33', 'zamora2023petrographicmicroscopywith pages 33-35', 'zamora2023petrographicmicroscopywith pages 35-36', 'zamora2023petrographicmicroscopywith pages 36-37'\n\nBibTex:\n@article{zamora2023petrographicmicroscopywith,\n    author = \"Zamora, Marco Andres Acevedo and Kamber, Balz Samuel\",\n    title = \"Petrographic Microscopy with Ray Tracing and Segmentation from Multi-Angle Polarisation Whole-Slide Images\",\n    year = \"2023\",\n    journal = \"Minerals\",\n    month = \"Jan\",\n    doi = \"10.3390/min13020156\",\n    url = \"https://doi.org/10.3390/min13020156\",\n    volume = \"13\",\n    pages = \"156\",\n    publisher = \"MDPI AG\",\n    issue = \"2\",\n    issn = \"2075-163X\"\n}\n\n\nAbstract:\n\u2018Slide scanners\u2019 are rapid optical microscopes equipped with automated and accurate x-y travel stages with virtual z-motion that cannot be rotated. In biomedical microscopic imaging, they are widely deployed to generate whole-slide images (WSI) of tissue samples in various modes of illumination. The availability of WSI has motivated the development of instrument-agnostic advanced image analysis software, helping drug development, pathology, and many other areas of research. Slide scanners are now being modified to enable polarised petrographic microscopy by simulating stage rotation with the acquisition of multiple rotation angles of the polariser\u2013analyser pair for observing randomly oriented anisotropic materials. Here we report on the calibration strategy of one repurposed slide scanner and describe a pilot image analysis pipeline designed to introduce the wider audience to the complexity of performing computer-assisted feature recognition on mineral groups. The repurposed biological scanner produces transmitted light plane- and cross-polarised (TL-PPL and XPL) and unpolarised reflected light (RL) WSI from polished thin sections or slim epoxy mounts at various magnifications, yielding pixel dimensions from ca. 2.7 \u00d7 2.7 to 0.14 \u00d7 0.14 \u00b5m. A data tree of 14 WSI is regularly obtained, containing two RL and six of each PPL and XPL WSI (at 18\u00b0 rotation increments). This pyramidal image stack is stitched and built into a local server database simultaneously with acquisition. The pyramids (multi-resolution \u2018cubes\u2019) can be viewed with freeware locally deployed for teaching petrography and collaborative research. The main progress reported here concerns image analysis with a pilot open-source software pipeline enabling semantic segmentation on petrographic imagery. For this purpose, all WSI are post-processed and aligned to a \u2018fixed\u2019 reflective surface (RL), and the PPL and XPL stacks are then summarised in one image, each with ray tracing that describes visible light reflection, absorption, and O- and E-wave interference phenomena. The maximum red-green-blue values were found to best overcome the limitation of refractive index anisotropy for segmentation based on pixel-neighbouring feature maps. This strongly reduces the variation in dichroism in PPL and interference colour in XPL. The synthetic ray trace WSI is then combined with one RL to estimate modal mineralogy with multi-scale algorithms originally designed for object-based cell segmentation in pathological tissues. This requires generating a small number of polygonal expert annotations that inform a training dataset, enabling on-the-fly machine learning classification into mineral classes. The accuracy of the approach was tested by comparison with modal mineralogy obtained by energy-dispersive spectroscopy scanning electron microscopy (SEM-EDX) for a suite of rocks of simple mineralogy (granulites and peridotite). The strengths and limitations of the pixel-based classification approach are described, and phenomena from sample preparation imperfections to semantic segmentation artefacts around fine-grained minerals and/or of indiscriminate optical properties are discussed. Finally, we provide an outlook on image analysis strategies that will improve the status quo by using the first-pass mineralogy identification from optical WSI to generate a location grid to obtain targeted chemical data (e.g., by SEM-EDX) and by considering the rock texture.\n\nRelevant Snippet:\n\u2026 The synthetic ray trace WSI is then combined with one RL to \u2026 methods and energy-dispersive X-ray analysis with electron \u2026 The aim of this study was to conduct experiments to improve \u2026\n\n\nUnobtainable Papers:\nDing Ze-jun and Wu Zi-qin. Monte carlo calculation of x-ray depth profiles in si substrate coated with films. Journal of Physics D, 27:387-392, Feb 1994. URL: https://doi.org/10.1088/0022-3727/27/2/031, doi:10.1088/0022-3727/27/2/031.\nG Love, M G C Cox, and V D Scott. A simple monte carlo method for simulating electron-solid interactions and its application to electron probe microanalysis. Journal of Physics D, 10:7-23, Jan 1977. URL: https://doi.org/10.1088/0022-3727/10/1/002, doi:10.1088/0022-3727/10/1/002.\nP Van Espen. Electron Probe X-ray Microanalysis, pages 247-274. Routledge, Jul 2017. URL: https://doi.org/10.1201/9780203741528-11, doi:10.1201/9780203741528-11.\nKaustubh N. Kulkarni, Aparna Tripathi, Abhinav Varshney, Jyoti Chandra, Siva Kumar, Sandeep Sangal, Debajyoti Paul, and Kallol Mondal. Electron probe micro-analyzer: an equipment for accurate and precise micro-composition analysis. Electron Microscopy in Science and Engineering, pages 71-93, Jan 2022. URL: https://doi.org/10.1007/978-981-16-5101-4\\_6, doi:10.1007/978-981-16-5101-4\\_6.\nPeter Karduck and Werner Rehbach. The use of tracer experiments and monte carlo calculations in the \u03c6(\u03c1z) determination for electron probe microanalysis. ArXiv, pages 191-217, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_11, doi:10.1007/978-1-4899-2617-3\\_11.\nXavier Llovet and Claude Merlet. Electron probe microanalysis of thin films and multilayers using the computer program xfilm. Microscopy and Microanalysis, 16:21-32, Dec 2010. URL: https://doi.org/10.1017/s1431927609991218, doi:10.1017/s1431927609991218.\nJean-Louis Pouchou. X-ray microanalysis of stratified specimens. Analytica Chimica Acta, 283:81-97, Nov 1993. URL: https://doi.org/10.1016/0003-2670(93)85212-3, doi:10.1016/0003-2670(93)85212-3.\nJohn J. Friel and Charles E. Lyman. Tutorial review: x-ray mapping in electron-beam instruments. Microscopy and Microanalysis, 12:2-25, Jan 2006. URL: https://doi.org/10.1017/s1431927606060211, doi:10.1017/s1431927606060211.\nH. Demers and R. Gauvin. Evaluation of analytical models and monte carlo programs with experimental phi-rho-z depth distribution for quantitative microanalysis. Microscopy and Microanalysis, 18:1050-1051, Jul 2012. URL: https://doi.org/10.1017/s1431927612007106, doi:10.1017/s1431927612007106.\nD. A. Sewell, G. Love, and V. Scott. Universal correction procedure for electron-probe microanalysis. i. measurement of x-ray depth distributions in solids. Journal of Physics D, 18:1233-1243, Jul 1985. URL: https://doi.org/10.1088/0022-3727/18/7/010, doi:10.1088/0022-3727/18/7/010.\nKurt F. J. Heinrich. Strategies of electron probe data reduction. ArXiv, pages 9-18, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_2, doi:10.1007/978-1-4899-2617-3\\_2.\nEric Lifshin. In the beginning \u2013 a quick look at the origins of quantitative electron microprobe analysis and the need for monte carlo modeling. Microscopy and Microanalysis, 29:478-479, Jul 2023. URL: https://doi.org/10.1093/micmic/ozad067.226, doi:10.1093/micmic/ozad067.226.\nDing Ze-Jun and Wu Ziqin. A comparison of monte carlo simulations of electron scattering and x-ray production in solids. Journal of Physics D: Applied Physics, 26:507-516, Apr 1993. URL: https://doi.org/10.1088/0022-3727/26/4/001, doi:10.1088/0022-3727/26/4/001.\nIan McNulty, Barry Lai, J\u00f6rg Maser, David J. Paterson, Paul Evans, Steve M. Heald, Gene E. Ice, Eric D. Isaacs, Mark L. Rivers, and Stephen R. Sutton. X\u2010ray microscopy at the advanced photon source. Synchrotron Radiation News, 16:34-42, Jul 2003. URL: https://doi.org/10.1080/08940880308603031, doi:10.1080/08940880308603031.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=4 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Now let me search for the remaining topics in parallel:",
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+                      "arguments": "{\"query\": \"Currie 1968 detection limit decision limit determination limit counting statistics hypothesis testing\"}",
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+                      "arguments": "{\"query\": \"Newbury Ritchie low voltage SEM EDS microanalysis silicon drift detector standardless quantification\"}",
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+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nP. Zambon, J. J. P. Peters, and L. Jones. The dynamic retrigger concept: enhancing count rate performance in nonparalyzable x-ray and electron counting detectors. IEEE Transactions on Nuclear Science, 73(3):745-753, Mar 2026. URL: https://doi.org/10.1109/tns.2026.3659949, doi:10.1109/tns.2026.3659949.\nB. A. Sobott, Ch. Broennimann, B. Schmitt, P. Trueb, M. Schneebeli, V. Lee, D. J. Peake, S. Elbracht-Leong, A. Schubert, N. Kirby, M. J. Boland, C. T. Chantler, Z. Barnea, and R. P. Rassool. Success and failure of dead-time models as applied to hybrid pixel detectors in high-flux applications. Journal of Synchrotron Radiation, 20:347-354, Jan 2013. URL: https://doi.org/10.1107/s0909049513000411, doi:10.1107/s0909049513000411.\nMohamed S. El_Tokhy, Sergey Rozovs, Alexey Lubashevskiy, H. Kasban, and Elsayed H. Ali. Optimization of dead time correction for digital gamma ray spectroscopy based on social spider algorithm. Sep 2025. URL: https://doi.org/10.1016/j.nucana.2025.100183, doi:10.1016/j.nucana.2025.100183.\nWilliam C. Barber, Einar Nygard, Jan S. Iwanczyk, Mengxi Zhang, Eric C. Frey, Benjamin M. W. Tsui, Jan C. Wessel, Nail Malakhov, Gregor Wawrzyniak, Neal E. Hartsough, Thulasi Gandhi, and Katsuyuki Taguchi. Characterization of a novel photon counting detector for clinical ct: count rate, energy resolution, and noise performance. SPIE Proceedings, Feb 2009. URL: https://doi.org/10.1117/12.813915, doi:10.1117/12.813915.\nRasool Safari, Mohammadreza Parishan, Zahra Rakeb, and Reza Faghihi. Two sequential compton scatters method: a new method for radiation detector dead-time measurement. Jul 2026. URL: https://doi.org/10.1016/j.radmeas.2026.107705, doi:10.1016/j.radmeas.2026.107705.\nPeter Kappen, Jeremy Wykes, and Bernt Johannessen. Nonlinearities in solid-state fluorescence detectors, pages 528-536. International Union of Crystallography, Nov 2024. URL: https://doi.org/10.1107/s1574870720012240, doi:10.1107/s1574870720012240.\nRasool Safari, Mohammadreza Parishan, Zahra Rakeb, and reza faghihi. Double compton method: a new method for radiation detector dead time measurement using double compton scattering. Unknown journal, Jan 2025. URL: https://doi.org/10.2139/ssrn.5703276, doi:10.2139/ssrn.5703276.\nCinzia De cesare. FPGA-based algorithms for the stability improvement of high-flux X-ray spectrometric imaging detectors. PhD thesis, Agence Bibliographique de l\u2019Enseignement Sup\u00e9rieur, Oct 2018. URL: https://doi.org/10.70675/5c4e73f7z5331z43fczb765z54dfa912e395, doi:10.70675/5c4e73f7z5331z43fczb765z54dfa912e395.\nP. Zambon. Dead time model for x-ray photon counting detectors with retrigger capability. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 994:165087, Apr 2021. URL: https://doi.org/10.1016/j.nima.2021.165087, doi:10.1016/j.nima.2021.165087.\nLei Pan, Yihui He, Vladislav V. Klepov, Michael C. De Siena, and Mercouri G. Kanatzidis. Perovskite cspbbr<sub>3</sub> single crystal detector for high flux x-ray photon counting. Nov 2022. URL: https://doi.org/10.1109/tmi.2022.3176801, doi:10.1109/tmi.2022.3176801.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=16 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Detection and quantification limits: origins and historical overview1Adapted from the Proceedings of the 1996 Joint Statistical Meetings (American Statistical Association, 1997). Original title: \u201cFoundations and future of detection and quantification limits\u201d. Contribution of the National Institute of Standards and Technology; not subject to copyright.1\nValid Text Names:\n'currie1999detectionandquantification pages 1-2', 'currie1999detectionandquantification pages 2-4', 'currie1999detectionandquantification pages 4-6', 'currie1999detectionandquantification pages 6-7', 'currie1999detectionandquantification pages 7-8'\n\nBibTex:\n@misc{currie1999detectionandquantification,\n    author = \"Currie, Lloyd A.\",\n    title = \"Detection and quantification limits: origins and historical overview1Adapted from the Proceedings of the 1996 Joint Statistical Meetings (American Statistical Association, 1997). Original title: \u201cFoundations and future of detection and quantification limits\u201d. Contribution of the National Institute of Standards and Technology; not subject to copyright.1\",\n    year = \"1999\",\n    journal = \"Analytica Chimica Acta\",\n    volume = \"391\",\n    pages = \"127-134\",\n    month = \"May\",\n    doi = \"10.1016/s0003-2670(99)00105-1\",\n    url = \"https://doi.org/10.1016/s0003-2670(99)00105-1\",\n    publisher = \"Elsevier BV\",\n    issue = \"2\",\n    issn = \"0003-2670\"\n}\n\n\nRelevant Snippet:\n\u2026 hypothesis testing approach to detection decisions and limits \u2026 attached to the expression \u201cdetection limit\u201d led to numerical \u2026 detection test, \u03c3 0 is required to calculate the detection limit. \u2026\n\n\nUnobtainable Papers:\nL.A. Currie. Lower limit of detection: definition and elaboration of a proposed position for radiological effluent and environmental measurements. ArXiv, Sep 1984. URL: https://doi.org/10.2172/6411049, doi:10.2172/6411049.\nL. A. Currie. Nomenclature in evaluation of analytical methods including detection and quantification capabilities (iupac recommendations 1995). Pure and Applied Chemistry, 67:1699-1723, Jan 1995. URL: https://doi.org/10.1351/pac199567101699, doi:10.1351/pac199567101699.\nLloyd A. Currie. Detection capabilities: some historical footnotes. Journal of Radioanalytical and Nuclear Chemistry, 311:1099-1109, Feb 2017. URL: https://doi.org/10.1007/s10967-016-4925-z, doi:10.1007/s10967-016-4925-z.\nLloyd A. Currie. Detection: overview of historical, societal, and technical issues. ArXiv, pages 1-62, Dec 1988. URL: https://doi.org/10.1021/bk-1988-0361.ch001, doi:10.1021/bk-1988-0361.ch001.\nThomas M. Semkow, Xin Li, and Liang T. Chu. Overview of signal detection theory and detection limits. Detection Limits in Air Quality and Environmental Measurements, pages 60-77, Nov 2019. URL: https://doi.org/10.1520/stp161820180061, doi:10.1520/stp161820180061.\nL. A. Currie. On the detection of rare, and moderately rare, nuclear events. Journal of Radioanalytical and Nuclear Chemistry, 276:285-297, May 2008. URL: https://doi.org/10.1007/s10967-008-0501-5, doi:10.1007/s10967-008-0501-5.\nLloyd A. Currie and Robert M. Parr. Perspectives on detection limits: for nuclear measurements in selected national and international programs. ArXiv, pages 171-193, Dec 1987. URL: https://doi.org/10.1021/bk-1988-0361.ch009, doi:10.1021/bk-1988-0361.ch009.\nLloyd A. Currie. Limits for qualitative detection and quantitative determination. application to radiochemistry. Analytical Chemistry, 40:586-593, Mar 1968. URL: https://doi.org/10.1021/ac60259a007, doi:10.1021/ac60259a007.\nDonald A. Chambless, Stephanie S. Dubose, and Edwin L. Sensintaffar. Detection limit concepts: foundations, myths, and utilization. Health Physics, 63:338\u2013340, Sep 1992. URL: https://doi.org/10.1097/00004032-199209000-00010, doi:10.1097/00004032-199209000-00010.\nJ.M. Kirkpatrick, W. Russ, R. Venkataraman, and B.M. Young. Calculation of the detection limit in radiation measurements with systematic uncertainties. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 784:306-310, Jun 2015. URL: https://doi.org/10.1016/j.nima.2015.01.005, doi:10.1016/j.nima.2015.01.005.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=16 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Exploring the limits of EDS microanalysis: rare earth element analyses\nValid Text Names:\n'ritchie2018exploringthelimits pages 1-4', 'ritchie2018exploringthelimits pages 4-5', 'ritchie2018exploringthelimits pages 5-7', 'ritchie2018exploringthelimits pages 7-9', 'ritchie2018exploringthelimits pages 9-11', 'ritchie2018exploringthelimits pages 11-11'\n\nBibTex:\n@article{ritchie2018exploringthelimits,\n    author = \"Ritchie, N W M and Newbury, D E and Lowers, H and Mengason, M\",\n    title = \"Exploring the limits of EDS microanalysis: rare earth element analyses\",\n    year = \"2018\",\n    journal = \"IOP Conference Series: Materials Science and Engineering\",\n    volume = \"304\",\n    pages = \"012013\",\n    month = \"Aug\",\n    doi = \"10.1088/1757-899x/304/1/012013\",\n    url = \"https://doi.org/10.1088/1757-899x/304/1/012013\",\n    publisher = \"IOP Publishing\",\n    issn = \"1757-8981\"\n}\n\n\nAbstract:\nIt is a great time to be a microanalyst. After a few decades of incremental progress in energy-dispersive X-ray spectrometry (EDS), the last decade has seen the accuracy and precision surge forward. Today, the question is not whether EDS is generally useful but to identify the types of problems for which wavelength-dispersive X-ray spectrometry remains the better choice. The full extent of EDS\u2019s capabilities has surprised many. Low Z, low energy, and trace element detection have been demonstrated even in the presence of extreme peak interferences. In this paper, we will summarise the state-of-the-art and investigate a challenging problem domain, the analysis of minerals bearing multiple rare-earth elements.\n\nRelevant Snippet:\n\u2026 The latest revolution, the silicon drift detector (SDD), has brought \u2026 SEM stages often have rotate and tilt axis that hinder \u2026 with large error bars (\u201dstandardless analysis\u201d). Accurate electron \u2026\n\n\n---\n\n## 2. Chemical characterisation is rough: the impact of topography and measurement parameters on energy-dispersive X-ray spectroscopy in biominerals\nValid Text Names:\n'shirley2022chemicalcharacterisationis pages 1-2', 'shirley2022chemicalcharacterisationis pages 2-5', 'shirley2022chemicalcharacterisationis pages 5-7', 'shirley2022chemicalcharacterisationis pages 7-9', 'shirley2022chemicalcharacterisationis pages 9-12', 'shirley2022chemicalcharacterisationis pages 12-14', 'shirley2022chemicalcharacterisationis pages 14-15', 'shirley2022chemicalcharacterisationis pages 15-15'\n\nBibTex:\n@article{shirley2022chemicalcharacterisationis,\n    author = \"Shirley, Bryan and Jarochowska, Emilia\",\n    title = \"Chemical characterisation is rough: the impact of topography and measurement parameters on energy-dispersive X-ray spectroscopy in biominerals\",\n    year = \"2022\",\n    journal = \"Facies\",\n    volume = \"68\",\n    month = \"Mar\",\n    doi = \"10.1007/s10347-022-00645-4\",\n    url = \"https://doi.org/10.1007/s10347-022-00645-4\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"2\",\n    issn = \"0172-9179\"\n}\n\n\nAbstract:\nEnergy dispersive X-ray microscopy (EDX) is a widely available, inexpensive method of characterizing the in-situ elemental composition of samples in Earth and life sciences. Common protocols and textbooks focussing on material sciences address EDX analysis of metallic samples that can be polished perfectly, whereas geoscientists often investigate specimens with prominent topography and composed of light, difficult to resolve elements. This is further compounded by the scarcity of literature surrounding the methodology of SEM\u2013EDX in the field of palaeontology, leading to common misinterpretations and artefacts during data acquisition. Here, the common errors in elemental composition obtained with EDX arising from surface topography and from parameters subject to user decisions are quantified. As a model, fossil bioapatite (conodonts) and abiotic Durango apatite are used. It is shown that even microscale topography can distort measured composition by up to 34%, whereas topographic features such as tilt with respect to the electron beam lead to differences of up to 85%. Working distance was not the most important parameter affecting the results and led to differences in composition of up to 13%, whereas the choice of standard and its levelling with the sample surface led to inaccuracy reaching 33%. EDX results can be also affected by beam damage and the effects of acceleration voltage on sample acquisition and resolution are quantified. An estimate is provided of the severity of errors associated with samples which cannot satisfy preparation requirements for EDX fully, such as holotypes, and with user decisions. Using a palaeontological example, recommendations are offered for the best parameters and the relative importance of error sources are assessed.\n\nRelevant Snippet:\n\u2026 The first step in this analysis is to define the SEM parameters (detector type, \u2026 Ritchie NWM, Newbury DE, Davis JM (2012) EDS \u2026 accuracy using a silicon drift detector. In: Microscopy and \u2026\n\n\n---\n\n## 3. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (SEM/EDS) quantitative? Effect of specimen shape\nValid Text Names:\n'newbury2011isscanningelectron pages 1-2', 'newbury2011isscanningelectron pages 2-3', 'newbury2011isscanningelectron pages 3-7', 'newbury2011isscanningelectron pages 7-10', 'newbury2011isscanningelectron pages 10-13', 'newbury2011isscanningelectron pages 13-16', 'newbury2011isscanningelectron pages 16-16'\n\nBibTex:\n@article{newbury2011isscanningelectron,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Is scanning electron microscopy/energy dispersive x-ray spectroscopy (SEM/EDS) quantitative? Effect of specimen shape\",\n    year = \"2011\",\n    journal = \"SPIE Proceedings\",\n    volume = \"8036\",\n    pages = \"803602\",\n    month = \"May\",\n    doi = \"10.1117/12.881040\",\n    url = \"https://doi.org/10.1117/12.881040\",\n    publisher = \"SPIE\",\n    issn = \"0277-786X\"\n}\n\n\nRelevant Snippet:\n\u2026 The extraordinary throughput of the silicon drift detector energy dispersive x-ray \u2026 -standards standardless\u201d analysis procedure available in most commercial x-ray microanalysis software \u2026\n\n\n---\n\n## 4. Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\nValid Text Names:\n'newbury2019electronexcitedxraymicroanalysis pages 1-2', 'newbury2019electronexcitedxraymicroanalysis pages 2-3', 'newbury2019electronexcitedxraymicroanalysis pages 3-4', 'newbury2019electronexcitedxraymicroanalysis pages 4-5', 'newbury2019electronexcitedxraymicroanalysis pages 5-6', 'newbury2019electronexcitedxraymicroanalysis pages 6-8', 'newbury2019electronexcitedxraymicroanalysis pages 8-10', 'newbury2019electronexcitedxraymicroanalysis pages 10-13', 'newbury2019electronexcitedxraymicroanalysis pages 13-15', 'newbury2019electronexcitedxraymicroanalysis pages 15-16', 'newbury2019electronexcitedxraymicroanalysis pages 16-18', 'newbury2019electronexcitedxraymicroanalysis pages 18-20', 'newbury2019electronexcitedxraymicroanalysis pages 20-22', 'newbury2019electronexcitedxraymicroanalysis pages 22-26', 'newbury2019electronexcitedxraymicroanalysis pages 26-28', 'newbury2019electronexcitedxraymicroanalysis pages 28-29', 'newbury2019electronexcitedxraymicroanalysis pages 29-30', 'newbury2019electronexcitedxraymicroanalysis pages 29-29', 'newbury2019electronexcitedxraymicroanalysis pages 30-31'\n\nBibTex:\n@article{newbury2019electronexcitedxraymicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W.M.\",\n    title = \"Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"1075-1105\",\n    month = \"Oct\",\n    doi = \"10.1017/s143192761901482x\",\n    url = \"https://doi.org/10.1017/s143192761901482x\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"05\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nAbstract 2018 marked the 50th anniversary of the introduction of energy dispersive X-ray spectrometry (EDS) with semiconductor detectors to electron-excited X-ray microanalysis. Initially useful for qualitative analysis, EDS has developed into a fully quantitative analytical tool that can match wavelength dispersive spectrometry for accuracy in the determination of major (mass concentration C > 0.1) and minor (0.01 \u2264 C \u2264 0.1) constituents, and useful accuracy can extend well into the trace (0.001 < C < 0.01) constituent range even when severe peak interference occurs. Accurate analysis is possible for low atomic number elements (B, C, N, O, and F), and at low beam energy, which can optimize lateral and depth spatial resolution. By recording a full EDS spectrum at each picture element of a scan, comprehensive quantitative compositional mapping can also be performed.\n\nRelevant Snippet:\n\u2026 spectrometry (EDS) with semiconductor detectors to electron-excited X-ray microanalysis. Initially useful for qualitative analysis, EDS has developed into a fully quantitative analytical \u2026\n\n\n---\n\n## 5. Measurement uncertainties of energy dispersive X-ray spectroscopy in the scanning electron microscope (SEM-EDX/EDS)\nValid Text Names:\n'tong2026measurementuncertaintiesof pages 1-8', 'tong2026measurementuncertaintiesof pages 8-11', 'tong2026measurementuncertaintiesof pages 11-12', 'tong2026measurementuncertaintiesof pages 12-15', 'tong2026measurementuncertaintiesof pages 15-18', 'tong2026measurementuncertaintiesof pages 18-21', 'tong2026measurementuncertaintiesof pages 21-24', 'tong2026measurementuncertaintiesof pages 24-26'\n\nBibTex:\n@article{tong2026measurementuncertaintiesof,\n    author = \"Tong, V. and Mingard, K.\",\n    title = \"Measurement uncertainties of energy dispersive X-ray spectroscopy in the scanning electron microscope (SEM-EDX/EDS)\",\n    year = \"2026\",\n    journal = \"Unknown journal\",\n    month = \"Mar\",\n    doi = \"10.47120/npl.mat135\",\n    url = \"https://doi.org/10.47120/npl.mat135\",\n    publisher = \"National Physical Laboratory\"\n}\n\n\nRelevant Snippet:\n\u2026 using the un-normalised standardless quantification method. All spectra (\u2026 microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector \u2026\n\n\n---\n\n## 6. EDS with Low-Voltage SEM: Possibilities and limitations of lithium detection and quantification\nValid Text Names:\n'gollaschindler2026edswithlowvoltage pages 1-3', 'gollaschindler2026edswithlowvoltage pages 3-6', 'gollaschindler2026edswithlowvoltage pages 6-8', 'gollaschindler2026edswithlowvoltage pages 8-13', 'gollaschindler2026edswithlowvoltage pages 13-14', 'gollaschindler2026edswithlowvoltage pages 14-17', 'gollaschindler2026edswithlowvoltage pages 17-17'\n\nBibTex:\n@article{gollaschindler2026edswithlowvoltage,\n    author = \"Golla-Schindler, Ute and Schneider, Gerhard\",\n    title = \"EDS with Low-Voltage SEM: Possibilities and limitations of lithium detection and quantification\",\n    year = \"2026\",\n    journal = \"EPJ Web of Conferences\",\n    volume = \"349\",\n    pages = \"01004\",\n    month = \"Jan\",\n    doi = \"10.1051/epjconf/202634901004\",\n    url = \"https://doi.org/10.1051/epjconf/202634901004\",\n    publisher = \"EDP Sciences\",\n    issn = \"2100-014X\"\n}\n\n\nAbstract:\n<jats:p>Achieving reliable detection and quantification of lithium (Li) with high spatial resolution down to the nanometer (nm) range is a major challenge on the path to fully understanding lithium-ion batteries throughout their life span. This paper presents possible influencing factors, such as contamination, radiation damage and charging effects, on EDS analysis, as well as methods for detecting and avoiding these effects. A windowless EDS detector specialising in the detection of low-energy X-rays enables Li content analysis. Even in Li compounds with overlapping edges, the lithium content can be clarified. The systematic investigation of the detection of lithium in lithium metal and lithium compounds, lithium batteries, and the influence of sample preparation and storage is presented. The reliability and accuracy of EDS quantification on samples under non-ideal testing conditions is also investigated. A new method of quantifying lithium, 'Li by difference', is introduced, whereby the lithium content is calculated as the missing element fraction of a non-normalised EDS quantification.</jats:p>\n\nRelevant Snippet:\n\u2026 EDS analysis, as well as methods for detecting and avoiding these effects. A windowless EDS detector specialising in the detection of low\u2026 The next setting is standard-less and, therefore\u2026\n\n\nUnobtainable Papers:\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W.M. Ritchie, John Henry J. Scott, and David C. Joy. Scanning electron microscopy and x-ray microanalysis. Scanning Electron Microscopy and X-Ray Microanalysis, Jan 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9, doi:10.1007/978-1-4939-6676-9.\nDale E. Newbury and Nicholas W. M. Ritchie. Rigorous quantitative elemental microanalysis by scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds) with spectrum processing by nist dtsa-ii. SPIE Proceedings, 9236:92360H, Sep 2014. URL: https://doi.org/10.1117/12.2065842, doi:10.1117/12.2065842.\nDale E. Newbury. Developments in instrumentation for microanalysis in low-voltage scanning electron microscopy. ArXiv, pages 263-303, 2008. URL: https://doi.org/10.1007/978-0-387-72972-5\\_11, doi:10.1007/978-0-387-72972-5\\_11.\nDale E. Newbury* and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds) quantitative? Scanning, 35 3:141-68, May 2013. URL: https://doi.org/10.1002/sca.21041, doi:10.1002/sca.21041.\nDale E. Newbury and Nicholas W. M. Ritchie. Measurement of trace constituents by electron-excited x-ray microanalysis with energy-dispersive spectrometry. Microscopy and Microanalysis, 22:520-535, May 2016. URL: https://doi.org/10.1017/s1431927616000738, doi:10.1017/s1431927616000738.\nRobert A. Fletcher, Nicholas W. M. Ritchie, Ian M. Anderson, and John A. Small. Microscopy and microanalysis of individual collected particles. Aerosol Measurement, pages 179-232, Jun 2011. URL: https://doi.org/10.1002/9781118001684.ch10, doi:10.1002/9781118001684.ch10.\nDale E. Newbury and Nicholas W. M. Ritchie. Faults and foibles of quantitative scanning electron microscopy/energy dispersive x-ray spectrometry (sem/eds). SPIE Proceedings, 8378:837803, May 2012. URL: https://doi.org/10.1117/12.912770, doi:10.1117/12.912770.\nDale E. Newbury and Nicholas W. M. Ritchie. Elemental mapping of microstructures by scanning electron microscopy-energy dispersive x-ray spectrometry (sem-eds): extraordinary advances with the silicon drift detector (sdd). Journal of Analytical Atomic Spectrometry, 28:973-988, Jun 2013. URL: https://doi.org/10.1039/c3ja50026h, doi:10.1039/c3ja50026h.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=16 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)\nValid Text Names:\n'newbury2015performingelementalmicroanalysis pages 1-2', 'newbury2015performingelementalmicroanalysis pages 2-4', 'newbury2015performingelementalmicroanalysis pages 4-5', 'newbury2015performingelementalmicroanalysis pages 5-6', 'newbury2015performingelementalmicroanalysis pages 6-7', 'newbury2015performingelementalmicroanalysis pages 7-9', 'newbury2015performingelementalmicroanalysis pages 9-11', 'newbury2015performingelementalmicroanalysis pages 11-13', 'newbury2015performingelementalmicroanalysis pages 13-15', 'newbury2015performingelementalmicroanalysis pages 15-17', 'newbury2015performingelementalmicroanalysis pages 17-20', 'newbury2015performingelementalmicroanalysis pages 20-21', 'newbury2015performingelementalmicroanalysis pages 21-23', 'newbury2015performingelementalmicroanalysis pages 23-25', 'newbury2015performingelementalmicroanalysis pages 25-26', 'newbury2015performingelementalmicroanalysis pages 26-26'\n\nBibTex:\n@article{newbury2015performingelementalmicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W. M.\",\n    title = \"Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)\",\n    year = \"2015\",\n    journal = \"Journal of Materials Science\",\n    volume = \"50\",\n    pages = \"493-518\",\n    month = \"Nov\",\n    doi = \"10.1007/s10853-014-8685-2\",\n    url = \"https://doi.org/10.1007/s10853-014-8685-2\",\n    publisher = \"Springer Science and Business Media LLC\",\n    issue = \"2\",\n    issn = \"0022-2461\"\n}\n\n\nAbstract:\nElectron-excited X-ray microanalysis performed in the scanning electron microscope with energy-dispersive X-ray spectrometry (EDS) is a core technique for characterization of the microstructure of materials. The recent advances in EDS performance with the silicon drift detector (SDD) enable accuracy and precision equivalent to that of the high spectral resolution wavelength-dispersive spectrometer employed on the electron probe microanalyzer platform. SDD-EDS throughput, resolution, and stability provide practical operating conditions for measurement of high-count spectra that form the basis for peak fitting procedures that recover the characteristic peak intensities even for elemental combination where severe peak overlaps occur, such PbS, MoS2, BaTiO3, SrWO4, and WSi2. Accurate analyses are also demonstrated for interferences involving large concentration ratios: a major constituent on a minor constituent (Ba at 0.4299 mass fraction on Ti at 0.0180) and a major constituent on a trace constituent (Ba at 0.2194 on Ce at 0.00407; Si at 0.1145 on Ta at 0.0041). Accurate analyses of low atomic number elements, C, N, O, and F, are demonstrated. Measurement of trace constituents with limits of detection below 0.001 mass fraction (1000\u00a0ppm) is possible within a practical measurement time of 500\u00a0s.\n\nRelevant Snippet:\n\u2026 quantitative EDS microanalysis that employed the whole spectrum. The so-called \u2018\u2018standardless analysis\u2019\u2019 method requires only the EDS \u2026 \u2018\u2018Standardless analysis\u2019\u2019 seeks to provide the \u2026\n\n\n---\n\n## 2. Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\nValid Text Names:\n'goldstein2018energydispersivexray pages 1-2', 'goldstein2018energydispersivexray pages 2-4', 'goldstein2018energydispersivexray pages 4-6', 'goldstein2018energydispersivexray pages 6-7', 'goldstein2018energydispersivexray pages 7-9', 'goldstein2018energydispersivexray pages 9-10', 'goldstein2018energydispersivexray pages 10-11', 'goldstein2018energydispersivexray pages 11-14', 'goldstein2018energydispersivexray pages 14-15', 'goldstein2018energydispersivexray pages 15-16', 'goldstein2018energydispersivexray pages 16-18', 'goldstein2018energydispersivexray pages 18-20', 'goldstein2018energydispersivexray pages 20-22', 'goldstein2018energydispersivexray pages 22-25', 'goldstein2018energydispersivexray pages 25-26'\n\nBibTex:\n@article{goldstein2018energydispersivexray,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"209-234\",\n    doi = \"10.1007/978-1-4939-6676-9\\_16\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_16\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nAs illustrated in Fig. 16.1, the physical basis of energy dispersive X-ray spectrometry (EDS) with a semiconductor detector begins with photoelectric absorption of an X-ray photon in the active volume of the semiconductor (Si). The entire energy of the photon is transferred to a bound inner shell atomic electron, which is ejected with kinetic energy equal to the photon energy minus the shell ionization energy (binding energy), 1.838 keV for the Si K-shell and 0.098 keV for the Si L-shell. The ejected photoelectron undergoes inelastic scattering within the Si crystal. One of the consequences of the energy loss is the promotion of bound outer shell valence electrons to the conduction band of the semiconductor, leaving behind positively charged \u201choles\u201d in the valence band. In the conduction band, the free electrons can move in response to a potential applied between the entrance surface electrode and the back surface electrode across the thickness of the Si crystal, while the positive holes in the conduction band drift in the opposite direction, resulting in the collection of electrons at the anode on the back surface of the EDS detector. This charge generation process requires approximately 3.6 eV per electron hole pair, so that the number of charge carriers is proportional to the original photon energy, Ep: \n \n$$ n={E}_p/3.6\\ eV $$ \n \nFor a Mn K-L3 photon with an energy of 5.895 keV, approximately 1638 electron\u2013hole pairs are created, comprising a charge of 2.6 \u00d7 10\u221216 coulombs. Because the detector can respond to any photon energy from a threshold of approximately 50 eV to 30 keV or more, the process has been named \u201cenergy dispersive,\u201d although in the spectrometry sense there is no actual dispersion such as occurs in a diffraction element spectrometer.\n\nRelevant Snippet:\n\u2026 Over the last 10 years, the Si(Li)-EDS has been replaced by the silicon drift detector design (SDD-EDS), illustrated in . Fig. \u2026 performance of the detector is three-way trade-off between \u2026\n\n\n---\n\n## 3. Optimal Pulse Processing, Pile-Up Decomposition, and Applications of Silicon Drift Detectors at LCLS\nValid Text Names:\n'blaj2017optimalpulseprocessing pages 1-2', 'blaj2017optimalpulseprocessing pages 2-2', 'blaj2017optimalpulseprocessing pages 2-4', 'blaj2017optimalpulseprocessing pages 4-5', 'blaj2017optimalpulseprocessing pages 5-6', 'blaj2017optimalpulseprocessing pages 6-7', 'blaj2017optimalpulseprocessing pages 7-8', 'blaj2017optimalpulseprocessing pages 8-9', 'blaj2017optimalpulseprocessing pages 9-10', 'blaj2017optimalpulseprocessing pages 10-12', 'blaj2017optimalpulseprocessing pages 12-13', 'blaj2017optimalpulseprocessing pages 13-14', 'blaj2017optimalpulseprocessing pages 14-15', 'blaj2017optimalpulseprocessing pages 15-15'\n\nBibTex:\n@article{blaj2017optimalpulseprocessing,\n    author = \"Blaj, G. and Kenney, C. J. and Dragone, A. and Carini, G. and Herrmann, S. and Hart, P. and Tomada, A. and Koglin, J. and Haller, G. and Boutet, S. and Messerschmidt, M. and Williams, G. and Chollet, M. and Dakovski, G. and Nelson, S. and Pines, J. and Song, S. and Thayer, J.\",\n    title = \"Optimal Pulse Processing, Pile-Up Decomposition, and Applications of Silicon Drift Detectors at LCLS\",\n    year = \"2017\",\n    journal = \"IEEE Transactions on Nuclear Science\",\n    volume = \"64\",\n    pages = \"2854-2868\",\n    month = \"Jun\",\n    doi = \"10.48550/arxiv.1706.01211\",\n    url = \"https://doi.org/10.48550/arxiv.1706.01211\",\n    publisher = \"arXiv\"\n}\n\n\nAbstract:\nSilicon drift detectors (SDDs) revolutionized spectroscopy in fields as diverse as geology and dentistry. For a subset of experiments at ultrafast, X-ray free-electron lasers (FELs), SDDs can make substantial contributions. Often the unknown spectrum is interesting, carrying science data, or the background measurement is useful to identify unexpected signals. Many measurements involve only several discrete photon energies known a priori, allowing single-event decomposition of pile-up and spectroscopic photon counting. We designed a pulse function and demonstrated that the signal amplitude (i.e., proportional to the detected energy and obtained from fitting with the pulse function), rise time, and pulse height are interrelated, and at short peaking times, the pulse height and pulse area are not optimal estimators for detected energy; instead, the signal amplitude and rise time are obtained for each pulse by fitting, thus removing the need for pulse shaping. By avoiding pulse shaping, rise times of tens of nanoseconds resulted in reduced pulse pile-up and allowed decomposition of remaining pulse pile-up at photon separation times down to hundreds of nanoseconds while yielding time-of-arrival information with the precision of 10 ns. Waveform fitting yields simultaneously high energy resolution and high counting rates (two orders of magnitude higher than current digital pulse processors). At pulsed sources or high photon rates, photon pile-up still occurs. We showed that pile-up spectrum fitting is relatively simple and preferable to pile-up spectrum deconvolution. We developed a photon pile-up statistical model for constant intensity sources, extended it to variable intensity sources (typical for FELs), and used it to fit a complex pile-up spectrum. We subsequently developed a Bayesian pile-up decomposition method that allows decomposing pile-up of single events with up to six photons from six monochromatic lines with 99% accuracy. The usefulness of SDDs will continue into the X-ray FEL era of science. Their successors, the ePixS hybrid pixel detectors, already offer hundreds of pixels, each with a similar performance to an SDD, in a compact, robust and affordable package.\n\nRelevant Snippet:\n\u2026 We investigate the performance of SDDs at X-ray FELs. In particular, we study the ability to \u2026 fit for optimal energy resolution in the absence of pulse shaping. With this approach, \u2026\n\n\n---\n\n## 4. Optimized readout methods of silicon drift detectors for high-resolution X-ray spectroscopy\nValid Text Names:\n'niculae2006optimizedreadoutmethods pages 1-2', 'niculae2006optimizedreadoutmethods pages 2-3', 'niculae2006optimizedreadoutmethods pages 3-6', 'niculae2006optimizedreadoutmethods pages 6-7'\n\nBibTex:\n@article{niculae2006optimizedreadoutmethods,\n    author = \"Niculae, A. and Lechner, P. and Soltau, H. and Lutz, G. and Str\u00fcder, L. and Fiorini, C. and Longoni, A.\",\n    title = \"Optimized readout methods of silicon drift detectors for high-resolution X-ray spectroscopy\",\n    year = \"2006\",\n    journal = \"Nuclear Instruments \\& Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment\",\n    volume = \"568\",\n    pages = \"336-342\",\n    month = \"Nov\",\n    doi = \"10.1016/j.nima.2006.06.025\",\n    url = \"https://doi.org/10.1016/j.nima.2006.06.025\",\n    publisher = \"Elsevier BV\",\n    issue = \"1\",\n    issn = \"0168-9002\"\n}\n\n\nRelevant Snippet:\n\u2026 rates and constant energy resolution, pulsed-reset operation of the \u2026 reset pulses to a reset structure integrated on the detector \u2026 The performance of the 30 mm 2 SDD showing an energy \u2026\n\n\n---\n\n## 5. X-Ray Silicon Drift Detector\u2013CMOS Front-End System with High Energy Resolution at Room Temperature\nValid Text Names:\n'bertuccio2016xraysilicondrift pages 1-3', 'bertuccio2016xraysilicondrift pages 3-4', 'bertuccio2016xraysilicondrift pages 4-5', 'bertuccio2016xraysilicondrift pages 5-7', 'bertuccio2016xraysilicondrift pages 7-8', 'bertuccio2016xraysilicondrift pages 8-8'\n\nBibTex:\n@article{bertuccio2016xraysilicondrift,\n    author = \"Bertuccio, G. and Ahangarianabhari, M. and Graziani, C. and Macera, D. and Shi, Y. and Gandola, M. and Rachevski, A. and Rashevskaya, I. and Vacchi, A. and Zampa, G. and Zampa, N. and Bellutti, P. and Giacomini, G. and Picciotto, A. and Piemonte, C. and Zorzi, N.\",\n    title = \"X-Ray Silicon Drift Detector\u2013CMOS Front-End System with High Energy Resolution at Room Temperature\",\n    year = \"2016\",\n    journal = \"IEEE Transactions on Nuclear Science\",\n    volume = \"63\",\n    pages = \"400-406\",\n    month = \"Feb\",\n    doi = \"10.48550/arxiv.2201.01698\",\n    url = \"https://doi.org/10.48550/arxiv.2201.01698\",\n    publisher = \"Institute of Electrical and Electronics Engineers (IEEE)\",\n    issue = \"1\",\n    issn = \"0018-9499\"\n}\n\n\nAbstract:\nWe present a spectroscopic system constituted by a Silicon Drift Detector (SDD) coupled to a CMOS charge sensitive preamplifier, named SIRIO, specifically designed to reach ultimate low noise levels. The SDD, with an active area of 13 mm<sup>2</sup>, has been manufactured by optimizing the production processes in order to reduce the anode current, successfully reaching current densities between 17 pA/cm<sup>2</sup> and 25 pA/cm<sup>2</sup> at + 20 <sup>\u00b0</sup> C for drift fields ranging from 100 V/cm to 500 V/cm. The preamplifier shows minimum intrinsic noise levels of 1.27 and 1.0 electrons r.m.s. at +20 <sup>\u00b0</sup>C and -30 <sup>\u00b0</sup>C, respectively. At room temperature (+ 20<sup>\u00b0</sup> C) the <sup>55</sup>Fe 5.9 keV and the pulser lines have 136 eV and 64 eV FWHM, respectively, corresponding to an equivalent noise charge of 7.4 electrons r.m.s.; the noise threshold is at 165 eV. The energy resolution, as measured on the pulser line, ranges from 82 eV FWHM (9.4 electrons r.m.s.) at + 30 <sup>\u00b0</sup> C down to 29 eV FWHM (3.3 electrons r.m.s.) at - 30 <sup>\u00b0</sup> C.\n\nRelevant Snippet:\n\u2026 to traditional detectors for which a tradeoff between large \u2026 as function of the peaking time of a triangular pulse shaping. \u2026 spectroscopic performance of a matrix of silicon drift diodes,\u201d \u2026\n\n\nUnobtainable Papers:\nPeter D. Olcott and Craig S. Levin. Pulse width modulation: a novel readout scheme for high energy photon detection. 2008 IEEE Nuclear Science Symposium Conference Record, pages 4530-4535, Oct 2008. URL: https://doi.org/10.1109/nssmic.2008.4774297, doi:10.1109/nssmic.2008.4774297.\nFlorian Rettenmeier and Linus Maurer. Utilization of adaptive flattop time with large area silicon drift detectors. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 998:165192, May 2021. URL: https://doi.org/10.1016/j.nima.2021.165192, doi:10.1016/j.nima.2021.165192.\nW. Metzger, J. Engdahl, W. Rossner, O. Boslau, and J. Kemmer. Large-area silicon drift detectors for new applications in nuclear medicine imaging. IEEE Transactions on Nuclear Science, 51:1631-1635, Aug 2004. URL: https://doi.org/10.1109/nssmic.2003.1351952, doi:10.1109/nssmic.2003.1351952.\nR. B. Mott and J. J. Friel. Improving eds performance with digital pulse processing. ArXiv, pages 127-157, Jan 1995. URL: https://doi.org/10.1007/978-1-4615-1825-9\\_9, doi:10.1007/978-1-4615-1825-9\\_9.\nNicholas W.M. Ritchie, Dale E. Newbury, and Jeffrey M. Davis. Eds measurements of x-ray intensity at wds precision and accuracy using a silicon drift detector. Microscopy and Microanalysis, 18:892-904, Jul 2012. URL: https://doi.org/10.1017/s1431927612001109, doi:10.1017/s1431927612001109.\nGrazia Laricchiuta, Wilfried Vandervorst, Ivan Zyulkov, Silvia Armini, and Johan Meersschaut. High sensitivity rutherford backscattering spectrometry using multidetector digital pulse processing. Journal of Vacuum Science and Technology, Feb 2018. URL: https://doi.org/10.1116/1.5016033, doi:10.1116/1.5016033.\nJinghui Wang, Linchuan Chen, Mats Persson, Paurakh L. Rajbhandary, Praneeth Kandlakunta, Gabriella Carini, and Rebecca Fahrig. Pulse pileup analysis for a double-sided silicon strip detector using variable pulse shapes. Jun 2019. URL: https://doi.org/10.1109/tns.2019.2917144, doi:10.1109/tns.2019.2917144.\nFlorian Rettenmeier and Linus Maurer. Design of optimum filters for signal processing with silicon drift detectors. X-Ray Spectrometry, 50:501-513, Feb 2021. URL: https://doi.org/10.1002/xrs.3227, doi:10.1002/xrs.3227.\nG. Gramegna, P. O'Connor, P. Rehak, and S. Hart. Low-noise cmos preamplifier-shaper for silicon drift detectors. Jun 1997. URL: https://doi.org/10.1109/23.603676, doi:10.1109/23.603676.\nL. Bombelli, R. Quaglia, C. Fiorini, A. Tocchio, R. Alberti, and T. Frizzi. A multichannel integrated readout circuit for high throughput x-ray spectroscopy with silicon drift detectors. IEEE Transactions on Nuclear Science, 60:430-436, Oct 2013. URL: https://doi.org/10.1109/nssmic.2011.6154300, doi:10.1109/nssmic.2011.6154300.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=16 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0000 | Disease-Target Evidence=0",
+                "name": "paper_search",
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+                "role": "assistant",
+                "content": "Good, I have papers retrieved. Now let me gather evidence from these papers and search for more specific topics:",
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+                    "id": "toolu_0168UJXG33iQ2XaeLK1eefrm",
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+                      "arguments": "{\"question\": \"How is the overvoltage ratio U0 of 2-3 for accelerating voltage in SEM-EDS derived from ionization cross-section physics (Bethe equation), and what is the trade-off with electron range and interaction volume?\"}",
+                      "name": "gather_evidence"
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+                    "id": "toolu_012wLpkY7s5q8ZTdPqRt9A1b",
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+                      "arguments": "{\"query\": \"Goldstein scanning electron microscopy X-ray microanalysis overvoltage accelerating voltage selection criteria\"}",
+                      "name": "paper_search"
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+                    "id": "toolu_01HJKVHJA7DE6q3m7Yy2WBFB",
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+                      "arguments": "{\"query\": \"dead time correction EDS detector output count rate optimization paralyzable model SEM microanalysis\"}",
+                      "name": "paper_search"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "No relevant evidence found for your question.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=16 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0408 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
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+                "content": "Retrieved Papers:\n## 1. Low voltage imaging and X-ray microanalysis in the SEM: challenges and opportunities\nValid Text Names:\n'wuhrer2016lowvoltageimaging pages 1-4', 'wuhrer2016lowvoltageimaging pages 4-7', 'wuhrer2016lowvoltageimaging pages 7-10', 'wuhrer2016lowvoltageimaging pages 10-12', 'wuhrer2016lowvoltageimaging pages 12-14', 'wuhrer2016lowvoltageimaging pages 14-15'\n\nBibTex:\n@article{wuhrer2016lowvoltageimaging,\n    author = \"Wuhrer, Richard and Moran, K.\",\n    title = \"Low voltage imaging and X-ray microanalysis in the SEM: challenges and opportunities\",\n    year = \"2016\",\n    journal = \"IOP Conference Series: Materials Science and Engineering\",\n    volume = \"109\",\n    pages = \"012019\",\n    month = \"Feb\",\n    doi = \"10.1088/1757-899x/109/1/012019\",\n    url = \"https://doi.org/10.1088/1757-899x/109/1/012019\",\n    publisher = \"IOP Publishing\",\n    issn = \"1757-8981\"\n}\n\n\nRelevant Snippet:\n\u2026 Operating the SEM at lower accelerating voltage allows for \u2026 scale lateral X-ray spatial resolution and nanoscale X-ray depth \u2026 of scanning electron microscope (SEM), X-ray microanalysis, \u2026\n\n\nUnobtainable Papers:\nM. David Frey. Low kv scanning electron microscopy. ArXiv, pages 101-119, Jan 2007. URL: https://doi.org/10.1007/978-0-387-39620-0\\_4, doi:10.1007/978-0-387-39620-0\\_4.\nDale E Newbury. Diagnostics for assessing spectral quality for x-ray microanalysis in low voltage and variable pressure scanning electron microscopy. Microscopy and Microanalysis, 7:702-703, Aug 2001. URL: https://doi.org/10.1017/s1431927600029585, doi:10.1017/s1431927600029585.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, Charles E. Lyman, Eric Lifshin, Linda Sawyer, and Joseph R. Michael. Special topics in scanning electron microscopy. ArXiv, pages 195-270, Jan 2003. URL: https://doi.org/10.1007/978-1-4615-0215-9\\_5, doi:10.1007/978-1-4615-0215-9\\_5.\nDale E. Newbury, David C. Joy, Patrick Echlin, Charles E. Fiori, and Joseph I. Goldstein. Advanced scanning electron microscopy and x-ray microanalysis. In Springer US. Mar 2013. URL: https://doi.org/10.1007/978-1-4757-9027-6, doi:10.1007/978-1-4757-9027-6.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, A. D. Romig, Charles E. Lyman, Charles Fiori, and Eric Lifshin. Coating and conductivity techniques for sem and microanalysis. ArXiv, pages 671-740, Jan 1992. URL: https://doi.org/10.1007/978-1-4613-0491-3\\_13, doi:10.1007/978-1-4613-0491-3\\_13.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, Charles Fiori, and Eric Lifshin. Coating techniques for sem and microanalysis. ArXiv, pages 461-494, Jan 1981. URL: https://doi.org/10.1007/978-1-4613-3273-2\\_10, doi:10.1007/978-1-4613-3273-2\\_10.\nEdward D. Boyes. Analytical potential of eds at low voltages. Microchimica Acta, 138:225-234, May 2002. URL: https://doi.org/10.1007/s006040200026, doi:10.1007/s006040200026.\nE.D. Boyes. On low voltage scanning electron microscopy and chemical microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 6 4:307-316, Jul 2000. URL: https://doi.org/10.1017/s1431927602000545, doi:10.1017/s1431927602000545.\nD. B. Williams and J. I. Goldstein. Quantitative x-ray microanalysis in the analytical electron microscope. ArXiv, pages 371-398, Jan 1991. URL: https://doi.org/10.1007/978-1-4899-2617-3\\_18, doi:10.1007/978-1-4899-2617-3\\_18.\nR.F. Egerton. Choice of operating voltage for a transmission electron microscope. Ultramicroscopy, 145:85-93, Oct 2014. URL: https://doi.org/10.1016/j.ultramic.2013.10.019, doi:10.1016/j.ultramic.2013.10.019.\nJ. I. Goldstein. Principles of thin film x-ray microanalysis. ArXiv, pages 83-120, Jan 1979. URL: https://doi.org/10.1007/978-1-4757-5581-7\\_3, doi:10.1007/978-1-4757-5581-7\\_3.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=20 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0408 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\nValid Text Names:\n'goldstein2018quantitativeanalysisthe pages 1-4', 'goldstein2018quantitativeanalysisthe pages 4-6', 'goldstein2018quantitativeanalysisthe pages 6-8', 'goldstein2018quantitativeanalysisthe pages 8-9', 'goldstein2018quantitativeanalysisthe pages 9-11', 'goldstein2018quantitativeanalysisthe pages 11-12', 'goldstein2018quantitativeanalysisthe pages 12-14', 'goldstein2018quantitativeanalysisthe pages 14-16', 'goldstein2018quantitativeanalysisthe pages 16-18', 'goldstein2018quantitativeanalysisthe pages 18-18', 'goldstein2018quantitativeanalysisthe pages 18-22', 'goldstein2018quantitativeanalysisthe pages 22-23', 'goldstein2018quantitativeanalysisthe pages 23-24', 'goldstein2018quantitativeanalysisthe pages 24-26', 'goldstein2018quantitativeanalysisthe pages 26-28', 'goldstein2018quantitativeanalysisthe pages 28-29', 'goldstein2018quantitativeanalysisthe pages 29-30', 'goldstein2018quantitativeanalysisthe pages 30-31', 'goldstein2018quantitativeanalysisthe pages 31-31'\n\nBibTex:\n@article{goldstein2018quantitativeanalysisthe,\n    author = \"Goldstein, Joseph I. and Newbury, Dale E. and Michael, Joseph R. and Ritchie, Nicholas W. M. and Scott, John Henry J. and Joy, David C.\",\n    title = \"Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\",\n    year = \"2018\",\n    journal = \"ArXiv\",\n    pages = \"309-339\",\n    doi = \"10.1007/978-1-4939-6676-9\\_20\",\n    url = \"https://doi.org/10.1007/978-1-4939-6676-9\\_20\",\n    month = \"Nov\",\n    publisher = \"Springer New York\"\n}\n\n\nAbstract:\nThis module discusses the procedure used to perform a rigorous quantitative elemental microanalysis by SEM/EDS following the k-ratio/matrix correction protocol using the NIST DTSA-II software engine for bulk specimens. Bulk specimens have dimensions that are sufficiently large to contain the full range of the direct electron-excited X-ray production (typically 0.5\u201310 \u03bcm) as well as the range of secondary X-ray fluorescence induced by the propagation of the characteristic and continuum X-rays (typically 10\u2013100 \u03bcm).\n\nRelevant Snippet:\n\u2026 following the k-ratio/matrix correction protocol using the NIST \u2026 , eventually falling to zero (\u201cparalyzable dead-time\u201d). A useful \u2026 of coincidence peaks above a deadtime of 10 % from highly \u2026\n\n\n---\n\n## 2. A New Method for Dead Time Calibration and a New Expression for Correction of WDS Intensities for Microanalysis.\nValid Text Names:\n'donovan2023anewmethod pages 1-2', 'donovan2023anewmethod pages 1-1', 'donovan2023anewmethod pages 2-3', 'donovan2023anewmethod pages 3-3', 'donovan2023anewmethod pages 3-4', 'donovan2023anewmethod pages 4-5', 'donovan2023anewmethod pages 5-6', 'donovan2023anewmethod pages 6-7', 'donovan2023anewmethod pages 7-8', 'donovan2023anewmethod pages 8-8', 'donovan2023anewmethod pages 8-9', 'donovan2023anewmethod pages 9-10', 'donovan2023anewmethod pages 10-11', 'donovan2023anewmethod pages 11-12', 'donovan2023anewmethod pages 11-11', 'donovan2023anewmethod pages 12-13', 'donovan2023anewmethod pages 13-14', 'donovan2023anewmethod pages 14-14', 'donovan2023anewmethod pages 14-15', 'donovan2023anewmethod pages 15-15'\n\nBibTex:\n@article{donovan2023anewmethod,\n    author = \"Donovan, John J and Moy, Aur\u00e9lien and von der Handt, Anette and Gainsforth, Zack and Maner, James L and Nachlas, William and Fournelle, John\",\n    title = \"A New Method for Dead Time Calibration and a New Expression for Correction of WDS Intensities for Microanalysis.\",\n    year = \"2023\",\n    journal = \"Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada\",\n    volume = \"29 3\",\n    pages = \"1096-1110\",\n    month = \"May\",\n    doi = \"10.1093/micmic/ozad050\",\n    url = \"https://doi.org/10.1093/micmic/ozad050\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"3\",\n    issn = \"1431-9276\"\n}\n\n\nAbstract:\nObserved photon count rates must be corrected for detector dead time effects for accurate quantification, especially at high count rates. We present the \"constant k-ratio\" method, a new approach for calibrating dead time for wavelength dispersive spectrometers by measuring k-ratios as a function of beam current. The method is based on the observation that for a given emission line at a specific take-off angle and electron beam energy, the intensity ratio from two materials containing the element should remain constant as a function of beam current, if the dead time calibration is accurate. The method has the advantage that it does not rely on the linearity of the beam current picoammeter, yet also allows the analyst to evaluate the picoammeter linearity, another critical parameter in EPMA calibration. By simultaneously comparing k-ratios for all spectrometers, one can also ascertain k-ratio consensus, essential for inter-laboratory comparisons. We also introduce improved dead time expressions and provide best practices on how to perform these instrument calibrations using this new \"constant k-ratio\" method. These improvements enable quantitative analysis of major and minor elements with high accuracy at high beam currents, simultaneously with trace elements with high sensitivity, for point analyses and X-ray mapping.\n\nRelevant Snippet:\n\u2026 for energy dispersive spectrometry (EDS) systems, which \u2026 sub-optimal for determining the exact dead time constants with \u2026 the detector and electronics, which as we will see breaks down \u2026\n\n\n---\n\n## 3. Optimizing SEM-EDX for Fast, High-Quality and Non-Destructive Elemental Analysis of Glass\nValid Text Names:\n'guyett2024optimizingsemedxfor pages 1-2', 'guyett2024optimizingsemedxfor pages 2-3', 'guyett2024optimizingsemedxfor pages 3-4', 'guyett2024optimizingsemedxfor pages 4-6', 'guyett2024optimizingsemedxfor pages 4-4', 'guyett2024optimizingsemedxfor pages 6-7', 'guyett2024optimizingsemedxfor pages 6-6', 'guyett2024optimizingsemedxfor pages 7-8', 'guyett2024optimizingsemedxfor pages 8-9', 'guyett2024optimizingsemedxfor pages 9-10', 'guyett2024optimizingsemedxfor pages 10-12', 'guyett2024optimizingsemedxfor pages 12-13', 'guyett2024optimizingsemedxfor pages 13-14', 'guyett2024optimizingsemedxfor pages 14-15', 'guyett2024optimizingsemedxfor pages 15-15'\n\nBibTex:\n@article{guyett2024optimizingsemedxfor,\n    author = \"Guyett, Paul C. and Chew, David and Azevedo, Vitor and Blennerhassett, Lucy C. and Rosca, Carolina and Tomlinson, Emma\",\n    title = \"Optimizing SEM-EDX for Fast, High-Quality and Non-Destructive Elemental Analysis of Glass\",\n    year = \"2024\",\n    journal = \"Journal of Analytical Atomic Spectrometry\",\n    volume = \"39\",\n    pages = \"2565-2579\",\n    month = \"Jan\",\n    doi = \"10.1039/d4ja00212a\",\n    url = \"https://doi.org/10.1039/d4ja00212a\",\n    publisher = \"Royal Society of Chemistry (RSC)\",\n    issue = \"10\",\n    issn = \"0267-9477\"\n}\n\n\nAbstract:\nAdvancements in scanning electron microscopy and energy dispersive x-ray analysis (SEM-EDX) technologies have reached the point where rapid, fully quantitative, non-destructive and high-resolution acquisition of effectively all major element chemical...\n\nRelevant Snippet:\n\u2026 investigated with electron probe micro-analysis (EPMA). \u2026 resolution and detection limit between SEM-EDX and EPMA. \u2026 per second, and has a dead time of c. 15%, each analysis took \u2026\n\n\nUnobtainable Papers:\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, A. D. Romig, Charles E. Lyman, Charles Fiori, and Eric Lifshin. Compositional Imaging, pages 525-545. Springer US, Jan 1992. URL: https://doi.org/10.1007/978-1-4613-0491-3\\_10, doi:10.1007/978-1-4613-0491-3\\_10.\nCharles Lyman. 2023 microscopy today innovation awards. Microscopy Today, 31:12-16, Sep 2023. URL: https://doi.org/10.1093/mictod/qaad069, doi:10.1093/mictod/qaad069.\nDivyadeep Harbola and George Mathew. Mapex: a tool for x-ray map analysis. Applied Computing and Geosciences, 28:100300, Dec 2025. URL: https://doi.org/10.1016/j.acags.2025.100300, doi:10.1016/j.acags.2025.100300.\nYueyun Chen and Matthew Mecklenburg. Corrected paralyzable detector model for post-acquisition pile-up correction in energy dispersive x-ray spectroscopy. Jul 2026. URL: https://doi.org/10.1093/mam/ozag053.176, doi:10.1093/mam/ozag053.176.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, Charles E. Lyman, Eric Lifshin, Linda Sawyer, and Joseph R. Michael. Special topics in electron beam x-ray microanalysis. ArXiv, pages 453-536, Jan 2003. URL: https://doi.org/10.1007/978-1-4615-0215-9\\_10, doi:10.1007/978-1-4615-0215-9\\_10.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=20 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0408 | Disease-Target Evidence=0",
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+                "role": "assistant",
+                "content": "Good, I have many relevant papers now. Let me gather evidence from these papers and continue searching for remaining topics:",
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+                "tool_calls": [
+                  {
+                    "id": "toolu_01N5Kh9Z7F25JaJsXarBfAD4",
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+                      "arguments": "{\"question\": \"What is the physics behind overvoltage ratio U0=2-3 recommendation? How does Bethe ionization cross-section formula relate to optimal accelerating voltage? How does the Kanaya-Okayama electron range and phi(rho-z) depth distribution compete with ionization efficiency?\"}",
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+                      "arguments": "{\"query\": \"Poisson statistics counting precision relative standard deviation X-ray microanalysis 10000 counts\"}",
+                      "name": "paper_search"
+                    }
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+                      "arguments": "{\"query\": \"ISO 22309 ASTM E1508 SEM EDS microanalysis standard parameters round-robin interlaboratory\"}",
+                      "name": "paper_search"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "No relevant evidence found for your question.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=20 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0763 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
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+                "role": "tool",
+                "content": "Retrieved Papers:\n## 1. Saving the photons: mapping X\u2010rays by position\u2010tagged spectrometry\nValid Text Names:\n'mott1999savingthephotons pages 1-2', 'mott1999savingthephotons pages 2-4', 'mott1999savingthephotons pages 4-5', 'mott1999savingthephotons pages 5-6', 'mott1999savingthephotons pages 6-10', 'mott1999savingthephotons pages 10-12', 'mott1999savingthephotons pages 12-13'\n\nBibTex:\n@article{mott1999savingthephotons,\n    author = \"MOTT, R. B. and FRIEL, J. J.\",\n    title = \"Saving the photons: mapping X\u2010rays by position\u2010tagged spectrometry\",\n    year = \"1999\",\n    journal = \"Journal of Microscopy\",\n    volume = \"193\",\n    month = \"Jan\",\n    doi = \"10.1046/j.1365-2818.1999.00437.x\",\n    url = \"https://doi.org/10.1046/j.1365-2818.1999.00437.x\",\n    pages = \"2-14\",\n    publisher = \"Wiley\",\n    issue = \"1\",\n    issn = \"0022-2720\"\n}\n\n\nRelevant Snippet:\n\u2026 relative to traditional X-ray mapping, photons are counted in a \u2026 3% relative standard deviation for only those elements of at \u2026 with the average count rate according to Poisson statistics. \u2026\n\n\nUnobtainable Papers:\nEric Lifshin and Raynald Gauvin. Minimizing errors in electron microprobe analysis. Mar 2001. URL: https://doi.org/10.1007/s100050010084, doi:10.1007/s100050010084.\nShinya Yamada, Magnus Axelsson, Yoshitaka Ishisaki, Saori Konami, Nozomi Takemura, Richard L Kelley, Caroline A Kilbourne, Maurice A Leutenegger, F Scott Porter, Megan E Eckart, and Andrew Szymkowiak. Poisson vs. gaussian statistics for sparse x-ray data: application to the soft x-ray spectrometer. Publications of the Astronomical Society of Japan, Aug 2019. URL: https://doi.org/10.1093/pasj/psz053, doi:10.1093/pasj/psz053.\nHenry Shuman, Avril V. Somlyo, and Andrew P. Somlyo. Quantitative electron probe microanalysis of biological thin sections: methods and validity. Ultramicroscopy, 1 4:317-39, Jan 1976. URL: https://doi.org/10.1016/0304-3991(76)90049-8, doi:10.1016/0304-3991(76)90049-8.\nJoseph I. Goldstein, Dale E. Newbury, Patrick Echlin, David C. Joy, Charles E. Lyman, Eric Lifshin, Linda Sawyer, and Joseph R. Michael. Quantitative X-Ray Analysis: The Basics, pages 391-451. Springer US, Jan 2003. URL: https://doi.org/10.1007/978-1-4615-0215-9\\_9, doi:10.1007/978-1-4615-0215-9\\_9.\nThomas O. Ziebold. Precision and sensitivity in electron microprobe analysis. Analytical Chemistry, 39:858-861, Jul 1967. URL: https://doi.org/10.1021/ac60252a028, doi:10.1021/ac60252a028.\nJ. Pyle, F. Spear, D. Wark, C. Daniel, and L. Storm. Contributions to precision and accuracy of monazite microprobe ages. American Mineralogist, 90:547-577, Apr 2005. URL: https://doi.org/10.2138/am.2005.1340, doi:10.2138/am.2005.1340.\nR. C. Stanley. Counting statistics in x-ray spectroscopy. British Journal of Applied Physics, 12:503-506, Sep 1961. URL: https://doi.org/10.1088/0508-3443/12/9/314, doi:10.1088/0508-3443/12/9/314.\nJ. M. Pyle, F. S. Spear, and D. A. Wark. Electron microprobe analysis of ree in apatite, monazite and xenotime: protocols and pitfalls. Reviews in Mineralogy & Geochemistry, 48:337-362, Jan 2002. URL: https://doi.org/10.2138/rmg.2002.48.8, doi:10.2138/rmg.2002.48.8.\nP. J. Statham. Quantifying benefits of resolution and count rate in edx microanalysis. ArXiv, pages 101-126, Jan 1995. URL: https://doi.org/10.1007/978-1-4615-1825-9\\_8, doi:10.1007/978-1-4615-1825-9\\_8.\nMark A. Rodriguez, Paul G. Kotula, James J. M. Griego, Jason E. Heath, Stephen J. Bauer, and Daniel E. Wesolowski. Multivariate statistical analysis of micro-x-ray fluorescence spectral images. Powder Diffraction, 27:108-113, Jun 2012. URL: https://doi.org/10.1017/s0885715612000243, doi:10.1017/s0885715612000243.\nA.V. Somlyo, H. Shuman, and A.P. Somlyo. Electron probe x-ray microanalysis of ca2+, mg2+, and other ions in rapidly frozen cells. Methods in enzymology, 172:203-29, Jan 1989. URL: https://doi.org/10.1016/s0076-6879(89)72016-4, doi:10.1016/s0076-6879(89)72016-4.\nDC Bell and AJ Garratt-Reed. Energy dispersive x-ray analysis in the electron microscope. ArXiv, Jul 2003. URL: https://doi.org/10.4324/9780203483428, doi:10.4324/9780203483428.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=21 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0763 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_018zPp22Aox3aKeNQkUGzTLj",
+                "info": {
+                  "start_ts": 2695.580510598,
+                  "end_ts": 2725.784912099
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nS\u00e9bastien Charles, Thierry Dodier, Monika Kaindl, Alain Kast\u00e9ropoulos, Alwin Knijnenberg, Marcus Larsson, Sandrine Lauper, Nadine Merat, Ludwig Niewoehner, Thomas Scholz, and Laurence Simon. Conduction of a round-robin test on a real sample for the identification of gunshot residues by sem/edx. Apr 2020. URL: https://doi.org/10.1016/j.forsciint.2020.110183, doi:10.1016/j.forsciint.2020.110183.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: []\n\nStatus: Paper Count=20 | Relevant Papers=0 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=0 | Current Cost=$0.0763 | Disease-Target Evidence=0",
+                "name": "paper_search",
+                "tool_call_id": "toolu_01JFSkowyEXcmvsUK26aPtGC",
+                "info": {
+                  "start_ts": 2695.58127313,
+                  "end_ts": 2714.911551988
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Let me try to read the key texts directly since evidence gathering isn't matching. The Goldstein textbook chapters should have the core information:",
+                "function_call": null,
+                "tool_calls": [
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+                    "id": "toolu_01Ux3jYFNfYmU8LNiYAmAgM9",
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+                      "arguments": "{\"text_name_list\": [\"goldstein2018energydispersivexray pages 11-14\", \"goldstein2018energydispersivexray pages 14-15\", \"goldstein2018energydispersivexray pages 15-16\", \"goldstein2018energydispersivexray pages 16-18\", \"goldstein2018energydispersivexray pages 18-20\", \"goldstein2018energydispersivexray pages 20-22\"]}",
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+                      "arguments": "{\"text_name_list\": [\"goldstein2018quantitativeanalysisthe pages 1-4\", \"goldstein2018quantitativeanalysisthe pages 4-6\", \"goldstein2018quantitativeanalysisthe pages 6-8\", \"goldstein2018quantitativeanalysisthe pages 8-9\", \"goldstein2018quantitativeanalysisthe pages 9-11\"]}",
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+                "content": "## 1. goldstein2018energydispersivexray pages 18-20 (Context ID: pqac-00000000)\n\n   current. Measure and record the probe current using the\n                                                                    Faraday cup and the picoammeter.\n                                                                                    4. Collect a 60 live-time second spectrum from the copper\n                                                                        sample.\n                                                                                    5. Increase the probe current through a sequence of\n      . .\u200a\u200a\u200aFig. 16.21\u2003 The spectrum image was collected on a 128 by 128          approximately 10\u201320 steps from the initial probe current\n             pixel grid representing 4\u2009\u00d7 4 mm. After data rotation to view the x-y         to approximately 2 times the optimal probe current.\n             plane, the first energy slice, 1 out of 1024, is shown. It appears black         Collect a 60 live-time second spectrum at each probe\n           because it contains no counts                                       current and measure and record the probe current using\n                                                                         the Faraday cup. A plot of such a measurement sequence\n                                                                                                  is shown in .\u2003 Fig. 16.23 (upper).\n                                                                                    6. Integrate the total number of counts in the range of\n                                                                      channels representing the Cu K-L2,3 characteristic peak.\n16                                                              (You don\u2019t need to background correct the integral.) Plot\n                                                                         the measured intensity divided by the probe current\n                                                                            against the measured probe current. The result should\n                                                                 be a horizontal line, as shown in .\u2003 Fig. 16.23 (lower).\n                                                                                       1.  If the line is not horizontal, the problem may be in the\n                                                                              detector or in the probe current measurement.\n                                                                                       2. The probe current measurement could be non-linear\n                                                                meaning the plot of the measured probe current to\n                                                                              true probe current is not a straight line.\n                                                                                       3.  Alternatively, the probe current may have a zero\n                                                                                              offset. The zero offset can be measured by blanking\n                                                                            the beam and recording the measured current at zero\n      . .\u200a\u200a\u200aFig. 16.22\u2003  Extracting the Cu L-family lines from the spectrum              true current. Subsequent probe current measurement\n            planes 89 to 97                                                can be offset by this value.\n\n         probe current, due to the loss of useful electrons during the\n          dead-time.                                                   16.3.6\u2002 Energy Calibration Linearity\n                   It is very important for accurate quantitative analysis that\n          the measured X-ray intensity is linear with respect to the   Consistent energy  calibration  is  critically important  for\n            effective probe dose. Twice the effective probe dose should   reproducible quantitative analysis. Pick a nominal channel\n         produce twice the measured  intensity. Not only  is  this  width (5-eV/channel will work fine in almost all cases) and                                                                                                        227                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n. .\u200a\u200a\u200aFig. 16.23\u2003 The number of\nX-rays recorded in the spectrum             3,000,000\nshould scale linearly with the                                      f(x) = 35876.1202787172x\ndose (the product of live-time                          R2 = 0.9999923818\nand probe current)                         2,500,000\n\n                                         2,000,000\n\n\n                                         1,500,000                                                                                        Counts                                                                   Det 2\n                                         1,000,000                                                                   Linear (Det 2)\n\n\n                                         500,000\n\n\n                                           0\n                                            0    10   20   30   40   50   60   70   80   90\n                                                              Probe dose (nA.s)\n\n\n                                      36,050\n\n                                      36,000\n                                      35,950\n\n                                      35,900\n\n                                      35,850                                                                                      (nA.s)\n              / 35,800\n                                      35,750                                                                Det 2                                                                                      Counts\n                                      35,700\n\n                                      35,650\n                                      35,600\n\n                                      35,550\n                                         0        0.2       0.4        0.6       0.8       1        1.2       1.4\n                                                                 Probe current (nA)\n\n\n\nuse this value for all your data acquisition. Before each day\u2019s   energy. Two points are sufficient to unambiguously calibrate\nmeasurements ensure that the detector is calibrated consis-   a linear function. The calibration (peak position) and resolu-\ntently by following the same protocol to check and, if neces-   tion (peak shape) should be constant with input count rate\nsary, recalibrate your detector.                                 (or dead-time), as shown in .\u2003 Fig. 16.24.\n  On a modern pulse processor, calibration is usually per-     To a very high degree, modern EDS detectors are linear.\nformed using the EDS vendor\u2019s software. The software will  However if you look carefully in the mid-range of energies,\nprompt you to collect a spectrum from an established mate-  you many notice the KLM markers may be misaligned by a\nrial. The software will examine the spectrum and extract the   channel or two. This is evidence that your detector is not per-\npositions of various characteristic X-ray features. The soft-   fectly linear but this need not represent a true performance\nware will then perform an internal adjustment to center these   problem.\nfeatures in the correct channels. Most modern pulse proces-      Since energy calibration is so critical but is also one of\nsors perform a continuous zero offset calibration using a  many parameters that should be measured as part of a com-\n\u201czero strobe pulse\u201d the pulse processor adds to the signal   plete EDS Quality Control (QC) program, the validation will\nstream for diagnostic purposes. Thus the only parameter  be discussed in a later section.\nthey usually adjust when performing a calibration is an elec-\ntronic gain. Usually, this involves identifying a single high\nenergy characteristic line (like the Mn K-L2,3 or the Cu K-L2,3)   16.3.7  Other Items\nand adjusting the gain until this feature is centered on the\nappropriate channel. The calibration is thus a two-point cali-   zz  Light Transparency and IR Cameras\nbration\u2014either a low energy characteristic line or the zero  Most (but not all) modern EDS detectors have a vacuum\nstrobe at low energy and a second characteristic line at high   tight window that is opaque to infrared and visible light.          228    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.24\u2003 The position and\n           widths of the characteristic peaks\n           should not vary with probe cur-\n             rent                               15 000\n\n                                                                                                                 Counts 10 000\n\n                                             5 000\n\n\n\n                                                0\n                  \n\n## 2. goldstein2018energydispersivexray pages 16-18 (Context ID: pqac-00000001)\n\n                                                                   \u201cImport \u2192 Raw\u201d tools to create a \u201cstack\u201d as shown in                   Detector                                                       .\u2003 Fig. 16.18.\n                                                                                        3. As imported, the orientation of the stack will depend\n                                                               upon how the data in the RAW file is organized.\n                                                                              Regardless of the original orientation, you will need to\n                                                                                 pivot the data a couple times using the \u201cImage \u2192\n                                        0.0                                                    Stack \u2192 Reslice\u201d tool. First, to identify the range of\n                                                                           channels that represent the Cu L-family and Cu K-L2,3\n                                                                                             intensities. Second, to align the spectrum data with           4\n               mm                                              the Z dimension so that the \u201cImage \u2192 Stack \u2192\n                                                                                Z-project\u201d tool can be used to create plots representing\n                                                                              the intensities in the Cu L-family and Cu K-L2,3\n                             4mm                       channels.\n                                                                                        4. The initial view of the imported spectrum will\n      . .\u200a\u200a\u200aFig. 16.16\u2003 A 3D rendering of the intensity in the Cu K line over a            usually show the data as shown in .\u2003 Fig. 16.19. In16\n           4 mm by 4 mm mapped area. Created using ImageJ-Fiji                          this view it is possible to identify the range of\n\n      . .\u200a\u200a\u200aFig. 16.17\u2003 A plot of two diag\u00ad\n            onal traverses extracted from the          300\n         3D rendering. The blue dots are                                                                                    Perp\n            perpendicular to the detector axis                                                                                                        Parallel\n                                             250          and red are parallel. Created using\n             ImageJ-Fiji\n                                             200\n\n\n                                             150                                                                                                                                                                        Intensity\n                                             100\n\n\n                                              50\n\n\n                                               0\n                                                 0           1           2           3           4           5           6\n\n                                                  mm                                                                                                       225                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n      channels to sum together for the Cu L-family and Cu   16.3.5  Count Rate Linearity\n       K-L2,3 lines. The Cu K-L2,3 lines are often quite dim.\n    5.  Using the \u201cImage \u2192 Stack \u2192 Reslice\u201d tool (see       One of the most important circuits in an X-ray pulse proces-\n       .\u2003 Fig. 16.20) rotate the stack until it looks like          sor accounts for the time during which the pulse processor is\n       .\u2003 Fig. 16.21                                       busy processing X-ray events. When the pulse processor is\n    6. Use the \u201cImage \u2192 Stack \u2192 Z-project\u201d twice            processing an X-ray, it is unavailable to process new incoming\n       (.\u2003 Fig. 16.22) to extract the range of channels           X-rays. This time is called \u201cdead-time.\u201d In contrast, the time\n       identified in .\u2003 Fig. 16.19 as associated with the Cu     during which the processor is not busy and is available is called\n       L-family and Cu K-L2,3 lines.                              \u201clive-time.\u201d The sum of \u201clive-time\u201d and \u201cdead-time\u201d is called\n    7. Convert the gray-scale image to a thermal scale using   \u201creal-time\u201d \u2013 the time you would measure using a wall clock.\n      \u201cImage \u2192 Lookup Tables \u2192 Thermal.\u201d                   For calculating the effective probe dose, live-time is the\n    8. Convert the image to a plot using \u201cAnalyze \u2192            critical parameter. The effective probe dose consists of those\n       Surface Plot\u201d                                           electrons which could produce measurable X-rays. So the\n    9.  Extract traverses from the image using the straight      effective probe dose equals the live-time times the probe cur-\n        line tool to define the traverse and then the \u201cAnalyze    rent. The effective probe dose is always less than the real\n   \u2192 Plot Profile\u201d tool to extract and plot the data.       probe dose, which is the product of the real time and the\n\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.18\u2003  Importing a RAW formatted spectrum image into\nImageJ-Fiji                                . .\u200a\u200aFig. 16.20\u2003  \u201cReslice\u201d tool used to rotate the stack\n\n\n\n\n       Cu L-family                                                               Cu K-L2,3\n\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.19\u2003 The spectrum image perspective as imported into ImageJ-Fiji. The bright strip is the Cu L-family while the much fainter band is\nCu K-L2,3           226    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                                                                  important because it is often hard to replicate the identical\n                                                                probe current but it is also important because different mate-\n                                                                                       rials measured with the same probe current will produce dif-\n                                                                            ferent dead times.\n                                                                    There really is no excuse for a modern X-ray detector not\n                                                                         to be linear. However, it is worth checking because the test\n                                                               can expose other potential problems like a non-linear or off-\n                                                                                set probe current meter.\n\n                                                                                           zz  Check 5: Count Rate Linearity with Effective Probe\n                                                                    Current\n                                                                  Equipment:\n                                   55 Faraday cup\n                                   55 Picoammeter\n                                   55 Flat, polished copper sample\n                                                                       Procedure:\n                                                                                       1. Mount the Faraday cup and the polished copper\n                                                                     sample on the stage at the same nominal working\n                                                                                   distance.\n                                                                                       2. Image the sample at the optimal working distance\n                                                               and a beam energy selected in the 15\u201325 keV\n                                                                            range.\n                                                                                    3.  Start a factor of 10 or more below the optimal probe\n                                                                              current. Measure and record the probe current using the\n                                                                    Faraday cup and the picoammeter.\n                                                                                    4. Collect a 60 live-time second spectrum from the copper\n                                                                        sample.\n                                                                                    5. Increase the probe current through a sequence of\n      . .\u200a\u200a\u200aFig. 16.21\u2003 The spectrum image was collected on a 128 by 128          approximately 10\u201320 steps from the initial probe current\n             pixel grid representing 4\u2009\u00d7 4 mm. After data rotation to view the x-y         to\n\n## 3. goldstein2018energydispersivexray pages 14-15 (Context ID: pqac-00000002)\n\n\n                              Y                                    distance\n                                                                                      \u03c8:\n                                                                                                    Elevation angle                                                         Actual\n                                  Z                     working                                                   Sample                                                                         distance\n\n\n\n\n                                                                                                 Sample tilt          222    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                                                                 per unit time. By spectral resolution we mean the width of\n                                                                   a characteristic peak, usually taken to be the Mn K-L2,3\n                                                             (K\u03b1) peak.\n                                                                  Higher throughput is desirable because it allows you to\n                                                                   use higher probe currents to produce more X-rays and pro-\n                                                              duce measured spectra with a larger number of measured\n                                                                         X-rays. Higher resolution is desirable because  it becomes\n                                                                             easier to distinguish characteristic peaks of similar energy.\n                                                             Both are virtues but one is achieved at the expense of the\n                                                                             other.\n                                                              The task of selecting a process time is the task of balanc-\n                                                                      ing good throughput with adequate resolution. At the best\n                                                                         resolution settings, throughput  is seriously compromised\n                                                           and as a result the precision of quantitative analysis is also\n                                                              compromised. At the highest throughput settings, resolution\n      . .\u200a\u200a\u200aFig. 16.14\u2003  Using a cell phone inclinometer to measure the eleva-                                                                                              is compromised and it becomes much more difficult to dis-             tion angle\n                                                                        tinguish interfering peaks.\n                                                                              Fortunately, resolution degrades relatively slowly while\n           correction. The elevation angle (usually sloppily called the  throughput increases quickly. Moderate pulse process times\n           \u201ctake-off angle\u201d) is often a configuration option that may be   tend to degrade the ultimate resolution by a few percent,\n           available to you to modify or may require a service engineer.   while increasing throughput by much larger factors. Every\n          Usually you can check the elevation angle by opening a spec-  vendor is different but typically a moderate pulse process\n         trum data file in a text editor. Most spectrum files are ASCII   time will produce both adequate resolution and excellent\n            text files and the vendors write a line containing the elevation   throughput.\n          or nominal take-off angle.                                 While some modern SDD are capable of ultimate resolu-\n           Compare the value produced by the software with the   tions of 122\u2013128 eV, compromising the resolution to 130\u2013\n           physical position of your detector relative to the beam axis.  135 eV  will produce an excellent compromise between\n          Sometimes, the correct instrument specific value of the take-\u00ad  resolution and throughput. Even a resolution of 140\u2013150 eV\n            off angle will be handwritten in the EDS vendor\u2019s documenta-   at high throughputs can produce  excellent  quantitative\n            tion. Other times, you can extract the angle from instrument   results because the precision of spectrum fitting is more\n            specific schematic diagrams from the SEM or EDS vendors.  determined by the number of measured X-rays than the\n           Regardless, it is a good idea to verify the elevation angle using   spectral resolution.\n          a protractor or a smart phone. Many smart phones contain\n          inclinometers which are accurate to within a degree and \u201cbub-                                                                                           zz  Check 2: Selecting a Process Time\n           ble level apps\u201d are available to turn the phone into a digital                                   55 Ensure that your EDS detector electronics are set to a           inclinometer. First, test the accuracy of the cell phone incli-                                                                    moderate process time that produces a good         nometer using a 30-60-90 triangle or similar reference shape.16                                                                    throughput with a resolution within 5 eV of the best         Then use the cell phone to measure the angle of the snout rela-                                                                                   resolution. Record this parameter in your electronic            tive to the angle of the column and calculate the elevation                                                                    notebook for future reference.           angle. .\u2003 Figure 16.14 shows that a cell phone measures the                                   55 Do not use an \u201cadaptive process time\u201d for           elevation angle of this detector to within half a degree (90\u00b0\u2013                                                                           standards-based quantitative analysis. Adaptive           54.5\u00b0 = 35.5\u00b0 ~ 35\u00b0 nominal value). Achieving similar accu-                                                                             process times allow the resolution to change with          racy with a protractor and a bubble level is difficult.                                                                       throughput making spectrum fitting challenging and\n                                                                                            less accurate.\n          16.3.2  Process Time\n                                                           The optimization of throughput is also confounded by an\n         The \u201cprocess time\u201d (also called the \u201cthroughput setting,\u201d   another practical limitation\u2014coincident X-rays or pulse-\u00ad\n          the \u201cdetector time constant,\u201d the \u201cresolution setting\u201d or  pileup\u2014and will be addressed in a later section.\n          other names) determines how much time the detector elec-\n           tronics dedicates to processing each incoming X-ray. A\n          longer  \u201cprocess  time\u201d  tends  to produce  lower X-ray   16.3.3  Optimal Working Distance\n         throughput but higher spectral resolution. Shorter \u201cpro-\n           cess times\u201d tend to produce higher X-ray throughput but   Nominally, the optimal working distance should be specified\n          lower spectral resolution. By throughput, we mean the   in instrument schematics. However,  it is worth checking\n       maximum number of X-rays that the detector can measure   because it may vary slightly or there may be a mistake in                                                                                                       223                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\ndesign or manufacturing. From the detector geometry sec-   detector element there is usually a window and an electron\ntion, we know that the optimal working distance is the dis-   trap. Most windows are ultrathin layers of polymer or sili-\ntance at which the axis along the detector snout intersects  con nitride mounted on a grid for mechanical strength.\nwith the electron beam axis (see .\u2003 Fig. 16.13). This working  Examples of two support grids are given in .\u2003 Fig. 16.15.\ndistance should also produce the largest flux of X-rays and be  While the grid may have an open area fraction of 75\u201380\u2009%,\nthe distance which is least sensitive to slight errors in vertical   the  silicon or carbon  grid  bars  are  often very  thick\npositioning.                                                  (0.38 mm) to enhance mechanical rigidity under the strain\n                                     \n\n## 4. goldstein2018energydispersivexray pages 11-14 (Context ID: pqac-00000003)\n\n                  the crystal mounted at the end of the snout and the face of\n 6. Use your vendor\u2019s software (or NIST DTSA-II) to         the active detector element perpendicular to the principle\n     integrate the background-corrected intensity in the Al     axis of the snout. The principal axis of the snout is oriented in\n   K peak (E\u2009=\u20091.486 keV).                                 the instrument such that it intersects with the electron beam\n 7. Use your vendor\u2019s software (or NIST DTSA-II) to look     axis at the \u201coptimal working distance.\u201d This geometry is illus-\n     for and integrate the background-corrected intensity in    trated in .\u2003 Fig. 16.11.\n    the Al K\u2009+\u2009Al K coincidence peak (E\u2009=\u20092.972 keV).           Often the detector is mounted on the flange on a sliding\n 8. Determine the ratio of the integrated intensity I(Al      mechanism that allows the position of the detector to trans-\n    K\u2009+\u2009Al K)/I(Al K). We desire this ratio to be smaller         late (move in and out) along the axis of the snout. The eleva-\n    than 0.01 (1\u2009%). In some trace analysis situations, it may   tion angle is nominally held fixed during the translation but\n     desirable to have this ratio less than 0.001 (0.1\u2009%).         the distance from the detector crystal changes and along with\n     Setting this limit too low will limit throughput but            it the solid angle (\u03a9) subtended by the detector. The solid          220    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.11\u2003 The elevation\n            angle is a fixed property of the\n                                                                        C            instrument/detector                                                                                         L\n\n\n\n                                                                                                Objective\n                                                                                                        lens\n\n                                                                                                         snout\n                                                                                                                     detector\n                                                Axes     X                               EDS\n\n                                       Y\n\n                                                                           Optimal\n                                           Z                        working           \u03c8:\n                                                                                  distance                Elevation angle\n\n                                                           Sample\n\n\n\n\n\n      . .\u200a\u200a\u200aFig. 16.12\u2003 The solid angle is a\n            function of sample-to-detector\n            distance and the active detector                                                           CL\n            area\n\n\n\n                                                                                                  Objective\n                                                                                                          lens\n\n16\n\n\n\n\n                                                                                                         Detector\n                                                           W      crystal\n\n\n\n                                                            Sample                                                                                                     Sample-to\n                                                                                                                 -detector\n                                                                                                               distance\n\n\n\n\n\n          angle is illustrated in the .\u2003 Fig. 16.12. Moving the detector        It is important to be able to maintain a reproducible solid\n         away from the sample is designed to decrease the solid angle   angle through consistent repositioning of the detector. Some\n          but does not change the elevation angle or the optimal work-   slide mechanisms are motorized. Motorized mechanisms\n          ing distance.                                             should  define an  \u201cinserted\u201d  position and a  \u201cretracted\u201d                                                                                                          221                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\nposition, which you should test to ensure that the positioning       4.  Test the reproducibility of the insertion point by\nis reproducible between insertions. Manual mechanisms usu-          extracting and inserting the detector and collecting a\nally provide a threaded screw with a manual crank to pull the           series of spectra. If the characteristic peak intensities\ndetector in and out. The threaded screw will usually have a          are reproducible (to much better than a fraction of a\npair of interlocking nuts which can be positioned to define a          percent) between insertions, the precision is adequate.\nconsistent insertion position. The procedure in the sidebar\nbelow will allow you to set and maintain a constant solid  The take-off angle is the angle at which X-rays exit a flat sam-\nangle and thus also a consistent detector collection efficiency.   ple in the direction of the detector. For a flat sample mounted\n                                                          perpendicular to the electron beam at the optimal working\n                                                                 distance, the take-off angle equals the elevation angle. If the\nzz  Sidebar: Setting a Constant Detector-to-Sample        sample is tilted or the sample surface is at a slightly different\n   Distance to Maintain Solid Angle                     working distance, then the take-off angle can be computed\n    1.  Locate the pair of lock nuts on the screw mechanism.  from the sample tilt, the working distance and the sample-to-\n     Move the lock nuts to the inner most position on the   detector distance. This is shown in .\u2003 Fig. 16.13. Often you\n       treaded rod.                                                will hear the terms elevation angle and take-off angle used\n    2.  Insert the detector as close to the sample as possible.    interchangeably. It is more precise however to think of the\n      Ensure that the detector does not touch the interior     elevation angle as being a fixed property of the instrument/\n       of the microscope. The detector snout must be          detector geometry and the take-off angle being dependent\n        electrically isolated (no conductive path) from the     upon instrument-specimen configuration.\n       interior of the chamber to eliminate noise caused by\n        electrical ground loops.                                        zz  Check 1: Verify the Elevation Angle\n    3.  Twist the upper lock nut to limit the motion of the        It is critical that your quantitative analysis software has the\n       detector towards the sample. Tighten the lower nut     correct elevation/take-off angle. Matrix correction \u00adalgorithms\n       to lock the upper nut into position.                   use the take-off angle to calculate the correct absorption\n\n. .\u200a\u200a\u200aFig. 16.13\u2003 The take-off angle\nis a function of the elevation angle,\nthe sample tilt and the actual                                               C                                                                                  L\nworking distance\n\n\n\n                                                                                        Objective\n                                                                                               lens\n\n\n                                                                                                 snout\n                                                                                                           detector                                                     Optimal                       EDS\n                                      Axes      X           working\n                              Y                                    distance\n                                                                                      \u03c8:\n                                                                                                    Elevation angle                                                         Actual\n                                  Z                     working                                                   Sample                                                                         distance\n\n\n\n\n                                                                                                 Sample tilt          222    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and\n\n## 5. goldstein2018energydispersivexray pages 15-16 (Context ID: pqac-00000004)\n\nat the optimal working distance is the dis-   trap. Most windows are ultrathin layers of polymer or sili-\ntance at which the axis along the detector snout intersects  con nitride mounted on a grid for mechanical strength.\nwith the electron beam axis (see .\u2003 Fig. 16.13). This working  Examples of two support grids are given in .\u2003 Fig. 16.15.\ndistance should also produce the largest flux of X-rays and be  While the grid may have an open area fraction of 75\u201380\u2009%,\nthe distance which is least sensitive to slight errors in vertical   the  silicon or carbon  grid  bars  are  often very  thick\npositioning.                                                  (0.38 mm) to enhance mechanical rigidity under the strain\n                                                               of up to one atmosphere of differential pressure. Off-axis\nzz  Check 3: Measuring the Optimal Working Distance       the grid bars can occlude the direct transmission of X-rays\n    1.  Select a sample like a piece of copper and mount it     from the sample to the detector element. Furthermore, the\n       perpendicular to the electron beam axis.             magnetic electron trap can also occlude X-rays from off-\n    2.  Select a beam energy of 15\u201325 keV and a moderate      axis. As a result, an EDS detector is more sensitive to X-rays\n      probe current to produce\u2009~\u200920% dead time.           produced on the snout axis than slightly off the axis. The\n    3. Move the stage\u2019s vertical axis to place the sample        result is a position dependent efficiency which peaks on\n       close to the objective lens pole piece. Be careful not     axis and decreases as the source of the X-rays is further\n       to run the sample into a detector.                  from axis.\n    4. Focus the image and record the working distance      A wide field-of-view X-ray spectrum image can demon-\n       reported by your SEM\u2019s software.                         strate the position sensitivity and can be used to ensure that\n    5.  Collect a 60 live-time second spectrum.                the detector snout and detector active element are oriented\n    6. Move the stage away from the objective lens pole        correctly.\n       piece in 1-mm steps.\n    7.  Repeat steps 4\u20136, taking the working distance             zz  Check 4: Collect a Wide Field X-ray Spectrum Image\n      through the nominal optimal working distance.              1. Mount a flat, polished piece of Cu in your SEM.\n    8.  Process the spectra. Extract the total number of              2. Image the Cu at the optimal working distance and at\n      counts in the energy range from about 100 eV to the         20\u201325 keV to excite both the K and L lines.\n     beam energy and plot this number against the                3. Find out how wide a field-of-view your SEM can\n      working distance.                                      image at the optimal working distance. The example\n    9. Determine the working distance which produces the           in .\u2003 Fig. 16.16 uses a 4-mm field-of-view.\n        largest number of counts. Since this working distance       4.  Collect a high count X-ray spectrum image from the\n       represents an inflection point, the slope will be              Cu. Acquiring at a moderate-to-high probe current\n     minimum and thus the sensitivity with respect to               for an hour or more at 256 \u00d7\u2009256-pixel image\n      working distance will also be minimized.                   dimensions should produce sufficiently high\n                                                                      signal-to-noise data.\n                                                                           5.  Process the data to extract and plot the raw\n16.3.4  Detector Orientation                                   intensities at each pixel in each of the Cu K-L2,3 and\n                                                Cu L-family lines.\nIn the previous section, we assumed that the principal axis of           1.  It is important to extract the raw intensities and\nthe detector snout is oriented to intersect with the electron            not the normalized intensities since we are\nbeam axis. In other words, the detector points towards the            looking for variation in the raw intensity as a\nsample. It is usually the EDS vendor\u2019s responsibility to ensure            function of position.\nthat the mounting flange has been designed to correctly ori-           2. The open source software ImageJ-Fiji (ImageJ\nent and position the detector. The next check will verify this.             plus additional tools) can be used to process\n   The active face of an EDS detector is a planar area that is           spectrum image data if it can be converted to a\nmounted perpendicular to the snout axis. In front of the       RAW format.\n\n\n\n                                AP3          AP5\n Thickness (\u00b5m)                      380           265\n Rib width (\u00b5m)                       59            45\n Opening width (\u00b5m)                  190           190             Thickness\n\n Open area %                    76%         78%\n                                                                                    Rib                     Opening\n Acceptance angle                     53\u00b0             72\u00b0                       width                    width\n\n. .\u200a\u200a\u200aFig. 16.15\u2003 Window support grid dimensions for two common window types (Source: MOXTEK)           224    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n                6.  Plot the data to demonstrate the variation of the                nished intensities leading to low analytical totals\n                   intensity as a function of position. .\u2003 Figure 16.16              and sub-optimal quantitative results.\n               shows the map from a well-oriented detector plotted            3.  Typically, the Cu L-family peak is more sensi\u00adtive\n                using a thermal color scheme in which red                   due to absorption by the vacuum window support\n                 represents the highest intensity and blue represents                 grid\u2019s Si ribs. .\u2003 Figure 16.15 (source: Moxtek)\n                 zero intensity. .\u2003 Figure 16.17 shows traverses                 shows the design of two recent Moxtek support\n                 extracted from the .\u2003 Fig. 16.16 data on diagonals                  grids. The vertical sensitivity is usually minimized\n                 representing parallel to the detector axis and                  by orienting the grid ribs vertically.\n                perpendicular to the detector axis. Verify that the\n              most intense region in the intensity plots is in the\n                 center of the image area.                                       zz  Sidebar: Processing a \u201cRAW\u201d Spectrum Image with\n                7. Note the extent of the region of uniform efficiency.         ImageJ-Fiji\n                 Variation from ideal uniform sensitivity has                  1. Convert the X-ray spectrum image data into a RAW\n                consequences.                                                                    file. A RAW file is large binary representation of the\n                    1. Low magnification X-ray spectrum images will            data in the spectrum image. Each pixel in the\n                       suffer from reduced intensity towards the edges.          spectrum image consists of a spectrum encode in an\n                    2. Point mode X-ray spectrum acquisitions collected          integer binary format. The pixels are organized in a\n                        off the optical axis will also suffer from dimi\u00ad             continuous array row-by-\u00adrow. The size of the file is\n                                                                                      typically equal to (channel depth)\u2009\u00d7\u2009(row\n                                                                         dimension)\u2009\u00d7\u2009(column dimensions)\u2009\u00d7\u2009(2 or 4 bytes\n                                                                         per integer value).\n                                   255.0                                                                                        2. Import the RAW data file into ImageJ using the\n                                                                      \u201cImport \u2192 Raw\u201d tools to create a \u201cstack\u201d as shown in                   Detector                                                       .\u2003 Fig. 16.18.\n                                                                                        3. As imported, the orientation of the stack will depend\n                                                               upon how the data in the RAW file is organized.\n                                                                              Regardless of the original orientation, you will need to\n                                                                                 pivot the data a couple times using the \u201cImage \u2192\n             \n\n## 6. goldstein2018energydispersivexray pages 20-22 (Context ID: pqac-00000005)\n\n line or the zero  Most (but not all) modern EDS detectors have a vacuum\nstrobe at low energy and a second characteristic line at high   tight window that is opaque to infrared and visible light.          228    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.24\u2003 The position and\n           widths of the characteristic peaks\n           should not vary with probe cur-\n             rent                               15 000\n\n                                                                                                                 Counts 10 000\n\n                                             5 000\n\n\n\n                                                0\n                                                               7.7        7.9        8.1        8.3        8.5        8.7        8.9        9.1\n                                                                                     Energy (keV)\n\n\n\n                                            150 000\n\n\n\n                                            100 000                                                                                                                 Counts\n\n\n                                             50 000\n\n\n\n                                                 0\n                                                          0.68                0.78                0.88               0.98                1.08\n                                                                                      Energy (keV)\n\n\n           Usually, the window is coated with a thin layer of aluminum   16.3.8  Setting Up a Quality Control Program\n           (or other metal) to keep light in the chamber from creating a\n          spurious signal on the EDS detector.                 An ongoing QC program is a valuable way to demonstrate\n              Regardless, it is worthwhile to test whether your detector   that your data and results can be trusted\u2014\u2014yesterday, today,\n              is sensitive to light. You may be surprised by a pinhole light  and tomorrow. If a client ever questions some data, it is useful\n           leak or a window without an adequate opaque layer.           to be able to go back to the day that data was collected and16                                                         show that your instrument and detector were performing\n             zz  Check 6: Check for SEM Light Sources                     adequately. A well-designed QC program need not take\n         The windows on some EDS detectors are not opaque to light  much time. A single spectrum from a consistent sample col-\n         and light in the chamber will produce noise counts particu-   lected under consistent conditions is sufficient to identify\n            larly in low channels.                                  most common failure modes and to document the long-term\n            1.  Enumerate the potential sources of light inside your      performance of your detector. A well-designed QC program\n           SEM. Sources to consider:                                          is likely to save time by eliminating the possibility of collect-\n                1. An IR camera                                        ing data when the detector is miscalibrated or otherwise\n                2.  Stage position sensors                               misbehaving.\n                3. The tungsten filament (essentially a light bulb)\n                4. Chamber windows                                              zz  Check 7: Implement a Quick QC Program\n                5. Cathodoluminescence from samples like zinc                1.  Maintain a sample consisting of a Faraday cup and a\n                  selenide or benitoite.                                         piece of Cu or Mn. Make use of this sample each day\n            2.  Collect a series of spectra and examine these spectra for        on which you intend on collecting quantitative EDS\n              anomalies.                                                     data to ensure that the detector is calibrated.\n                1. When possible collect the spectra without an electron       2.  Image the sample at a consistent working distance\n             beam so there should be no source of X-rays.                  (the \u201coptimal working distance\u201d), a consistent beam\n                2.  Collect a spectrum with the light source turned off            energy, and a consistent probe current.\n              and a spectrum with the source on. There should be         3.  Collect a spectrum from a sample for a consistent\n              no difference.                                                    live-time.                                                                                                       229                                      16\n16.3 \u00b7 Practical Aspects of Ensuring EDS Performance for a Quality Measurement Environment\n\n\n    4.  Process the spectrum to extract the raw intensities in           ideal because it is readily available, stable and has\n       the K-L2,3 and L-family lines, the resolution, the actual        both K-L2,3 (~8.04 keV) and L-family (~930 eV)\n       zero offset and gain, and the total number of counts.             lines.\n      Record and plot these values on a control chart.      55 The beam energy should be sufficient to adequately\n                                                                         excite (overvoltage\u2009>\u20092) all the lines of interest in the\nUsing the QC Tools Within DTSA-II                        sample.\nWhile it is possible to implement a QC program by combining   55 The nominal working distance should be the\nan EDS  vendor\u2019s  software  with  careful  record-keeping,          detector\u2019s optimal working distance. The sample\nDTSA-II provides tools specifically designed to implement a        should be brought into focus (using the stage Z-axis if\nbasic EDS detector QC program. The tools import spectra,         necessary) at this working distance before collecting a\nmake some basic sanity checks, process the spectrum to extract        spectrum.\nQC metrics, archive the metrics and report the metrics.      55 The nominal probe current is the probe current at\n                                                         which the spectra will be collected (to within a few\nCreating a QC Project                                          percent). Usually, the \u201cuse probe current\n5 5 A QC project is an archive of spectra collected from a           normalization\u201d will be selected so that all intensities\n    specified sample under similar conditions on a specified         are scaled relative to the probe current measured with\n   detector/instrument. The spectra are fitted with a               a in-lens cup or a Faraday cup.\n   modeled spectrum and the resulting quantities      55 After creating the project, you will need to go\n   recorded to track these values over the lifetime of the        through the QC tool additional times to add measured\n    detector.                                                      spectra.\n5 5 Creating a QC Project involves specifying a detector\n   and the conditions which are to be held consistent\n    (.\u2003 Fig. 16.25). If you use a single detector with different     zz  Adding Spectra to a QC Project\n   process times, either select a constant process time or,    55 To add spectra to a QC project, you first need to\n    better yet, create individual projects for each process              specify which project you will be adding the spectra.\n   time.                                              Once you select the project, the \u201cmaterial,\u201d \u201cbeam\n  5 5 The material may be simple or complex but                    energy,\u201d \u201cnominal working distance,\u201d and \u201cnominal\n      should be robust, durable and provide characteristic         probe current\u201d boxes will fill with the associated\n       lines over a large range of energies. Copper is                information (see .\u2003 Fig. 16.26).\n\n\n\n\n. .\u200a\u200a\u200aFig. 16.25\u2003 The panel in\nDTSA-II for creating QC projects.\nThis panel is accessed through\nthe \u201cTools \u2192 QC Alien\u201d menu item          230    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n      . .\u200a\u200a\u200aFig. 16.26\u2003  Panel for selection\n             of detector and material para\u00ad\n           meters\n\n\n\n\n\n      55 Once the project has been selected, you will need to      You will specify the detector and QC project along with\n                  specify a spectrum to add to the project. Needless to    the fit values that you wish to report. The report will be gen-\n                    say, the spectrum should have been collected on the    erated into a new HTML document and the result displayed\n                  correct detector under the conditions specified (see     in your system\u2019s default web browser. The report will look\n                  .\u2003 Fig. 16.27).                                               like .\u2003 Fig. 16.30, with h\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005]\n\nStatus: Paper Count=21 | Relevant Papers=1 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=6 | Current Cost=$0.0763 | Disease-Target Evidence=0",
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+                "content": "## 1. goldstein2018quantitativeanalysisthe pages 8-9 (Context ID: pqac-00000006)\n\nAnalysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n         20.3 Examples of the k-ratio/Matrix              the error budget. In this analysis and the analyses reported\n             Correction Protocol with DTSA II            below, the relative deviation from the expected value (RDEV)\n           (Newbury and Ritchie 2015b)                    (also referred to as \u201crelative error\u201d) is calculated with the\n                                                                       \u201cexpected\u201d value taken as the stoichiometric formula value or\n          20.3.1  Analysis of Major Constituents            the value obtained from an \u201cabsolute\u201d analytical method, just\n                 (C\u2009>\u20090.1 Mass Fraction) with                 as in gravimetric analysis:\n               Well-\u00adResolved Peaks                                                                                         \uf8ee ( Analyzed value \u2212 expected value ) \uf8f9\n                                                  RDEV = \uf8ef                                 \uf8fa \u00d7 100%    (20.3)\n         The EDS spectra of the minerals pyrite (FeS2) and troilite               \uf8f0         expected value         \uf8fb\n          (FeS) measured at E0\u2009=\u200920 keV with a dead-time of\u2009~\u200910\u2009% are\n        shown in .\u2003 Fig. 20.4 and feature well separated peaks for the  Optimizing Analysis Strategy\n         Fe K- and L- families and the S K-family. These spectra were                                                           The DTSA II analysis report includes for each analyzed ele-\n          analyzed with Fe and CuS serving both as peak-fitting refer-                                                         ment the ZAF factors and the estimated uncertainties in\n          ences and as standards. CuS is chosen for the S reference and                                                                        these factors as well as uncertainties due to the counting sta-\n          standard rather than elemental S since CuS is stable under                                                                                          tistics associated with the measurements of the unknown and\n           electron bombardment while elemental S is not stable. The                                                                           of the standard (Ritchie and Newbury 2012). Careful exami-\n         spectrum for FeS and the residual spectrum after peak-fitting                                                                     nation of these factors can be used to refine the analytical\n           are also shown in .\u2003 Fig. 20.4. The results for seven replicate                                                                           strategy to optimize the measurement. Reducing the uncer-\n           analyses are listed in .\u2003 Table 20.1 (FeS) and .\u2003 Table 20.2 (FeS2)   tainty due to the counting statistics requires increasing the\n          along with the ZAF correction factors and the \u00adcomponents of                                                                        dose. The absorption factor A is strongly influenced by the\n\n\n\n             a  180 000                                                                                                                                                FeS_20kV10n9%DT_50s\n                                                                                                                                                FeS_20kV10n9%DT_50s\n                160 000\n                                                                                     E0 = 20 KeV\n                140 000                                                                           FeS\n                120 000                                                      FeS2\n                                   Counts 10080 000000\n\n                 60 000\n\n                 40 000\n\n                 20 000\n\n                      0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                  Photon energy (keV)\n\n           b\n                 14 000                                                                                                            FeS_20kV10n9%DT_50s\n                                                                                                                                                 Residual_FeS_20kV10n9%DT_50s\n\n                 12 000\n                                                                           E0 = 20 KeV\n                 10 000                                          FeS\n                                                                                   Fitting residual\n                                   Counts   8 00020              6 000\n\n                  4 000\n\n                  2 000\n\n                      0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                  Photon energy (keV)\n\n\n      . .\u200a\u200a\u200aFig. 20.4\u2003  a SDD-EDS spectra of Pyrite (FeS2) (blue) and meteoritic Troilite (FeS (red) at E0\u2009=\u200920 keV. b NIST DTSA-II analysis of FeS using Fe and\n          CuS as peak-fitting references and as standards. The original spectrum (red) and the residual spectrum after peak-fitting (blue) are shown                                                                                                               317                                      20\n20.3 \u00b7 Examples of the k-ratio/Matrix Correction Protocol with DTSA II\n\n\n\n  . .\u200a\u200a\u200aTable 20.1\u2003  Analysis of FeS (meteoritic troilite) at E0\u2009=\u200920 keV     . .\u200a\u200a\u200aTable 20.3\u2003  Analysis of FeS at E0\u2009=\u200910 keV with CuS and Fe as\n    with CuS and Fe as fitting references and standards Integrated              fitting references and standards Integrated spectrum count,\n    spectrum count, 0.1\u201320 keV\u2009=\u20097,048,000; uncertainties expressed         0.1\u201310 keV\u2009=\u20095,630,000; uncertainties expressed in mass\n    in mass fraction. Analysis performed with Fe K-L2,3 and S K-L2,3              fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.5052        0.4948              Cav (atom frac)                     0.503           0.497\n\n    Z-correction                        0.977          0.95               Z-correction                       0.973           0.937\n\n    A-correction                        1.118          0.983              A-correction                      1.041           0.997\n\n    F-correction                        1.003         1                  F-correction                       1.001          1\n\n   \u03c3 (7 replicates)                     0.00075       0.00075         \u03c3 (7 replicates)                    0.00056         0.00056\n     \u03c3Rel (%)                             0.15\u2009%         0.15\u2009%                \u03c3Rel (%)                            0.11\u2009%           0.11\u2009%\n   RDEV (%)                           1.00\u2009%       \u22121.00\u2009%          RDEV (%)                          0.59\u2009%        \u22120.59\u2009%\n\n   C (mass frac, single analysis)         0.3699        0.6305          C (mass frac, single analysis)        0.3627          0.6257\n\n    Counting error, std                 0.00020       0.0003           Counting error, std                0.0002          0.0008\n\n    Counting error, unk                 0.00020       0.0007           Counting error, unk                0.0003          0.0018\n\n    A-factor error                       0.0017        0.0002             A-factor error                     0.0006          4.10E-05\n\n    Z-factor error                       2.20\u00d7105      4.10\u00d710\u20136           Z-factor error                      2.20\u00d710\u20135       1.30\u00d710\u20136\n\n   Combined errors                   0.0017        0.0008          Combined errors                  0.0007          0.0019\n\n\n\n  . .\u200a\u200a\u200aTable 20.2\u2003  Analysis of FeS2 (pyrite) at E0\u2009=\u200920 keV with CuS      . .\u200a\u200a\u200aTable 20.4\u2003  Analysis of FeS2 at E0\u2009=\u200910 keV with CuS and Fe as\n   and Fe as fitting references and standards Integrated spectrum             fitting references and standards Integrated spectrum count,\n    count, 0.1.\u201320 keV\u2009=\u20097,765,000; uncertainties expressed in mass          0.1\u201310 keV\u2009=\u20096,253,000); uncertainties expressed in mass\n     fraction. Analysis performed with Fe K-L2,3 and S K-L2,3                       fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.6726        0.3274              Cav (atom frac)                     0.671           0.329\n\n    Z-correction                        0.957          0.928              Z-correctio\n\n## 2. goldstein2018quantitativeanalysisthe pages 4-6 (Context ID: pqac-00000007)\n\n 20 000\n\n\n\n                     0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                 Photon energy (keV)\n\n                100 000\n                                                                                                                                         Mn_20kv10nA110kHz10DT\n\n\n                 80 000\n\n                                                                                            5 eV bin width\n                 60 000\n                                   Counts\n                                                                  FWHM = 126 eV                 40 000\n\n\n\n                 20 000\n\n\n\n                     0\n                         5.60      5.65      5.70      5.75      5.80      5.85      5.90      5.95      6.00      6.05      6.10      6.15      6.20\n                                                                 Photon energy (keV)\n\n\n      . .\u200a\u200a\u200aFig. 20.1\u2003 SDD-EDS spectrum of Mn (E0\u2009=\u200920 keV)\n\n          energy, E0. The energy span is given by the channel width   photoelectron to determine the photon energy, and incre-\n          multiplied by the number of channels. With a 5-eV chan-  menting the appropriate energy bin in the EDS histogram\n          nel width, a choice of 4096 channels will provide access to  by one count. The EDS time constant (also known as the\n         photon energies as high as 20.48 keV. For beam energy   shaping time, the processing time, the maximum through-\n         above 20 keV, the number of channels should be increased   put, or other terms in different vendor EDS systems) effec-\n           to retain the 5-eV channel width, or alternatively the chan-   tively  determines  the amount  of  time  spent on  the\n          nel width can be increased to 10 eV, but with the conse-  measurement cycle. A short time constant enables more\n20      quence that fewer channels will describe each characteristic  photons to be processed per unit of real (clock) time, but\n          peak.                                                      the trade-off of faster processing  is poorer accuracy in\n                                                                      assigning the photon energy. While the characteristic X-ray\n      EDS Time Constant (Resolution                   peak has a sharply defined energy, with a natural peak width\n       and Throughput)                                         of a few eV or less, the EDS measurement process inevitably\n         The EDS is only capable of processing one photon at a time.   substantially broadens the measured peak. For example,\n         The basic measurement cycle is the photoelectric absorp-  Mn K-L2,3 has a natural width of approximately 7 eV (deter-\n           tion of the photon in the detector active volume, measure-  mined as the FWHM) but as displayed in the EDS histo-\n        ment  of  the  charge  deposited  by  scattering  of  the  gram, the Mn K-L2,3 peak is broadened to 122\u2013150 eV                                                                                                               313                                      20\n20.2 \u00b7 Instrumentation Requirements\n\n\nFWHM or more, depending on the choice of time constant.   reproducible choice must be made for r since this value has\nFor the particular silicon drift detector (SDD)-EDS and  such a strong impact on \u03a9 and thus on the number of pho-\ntime constant shown in .\u2003 Fig. 20.1, the broadened EDS   tons detected per unit of dose.\npeak has a FWHM\u2009=\u2009126 eV. The peak width increases (i.e.,\nresolution becomes poorer) as the time constant decreases.\nThe shortest time constant, which gives the highest through-   20.2.2  Choosing the Beam Energy, E0\nput but the broadest peaks (poorest resolution), is typically\nchosen for analysis situations where it is important to max-  The choice of beam energy depends on the particular\nimize the total number of X-ray counts per unit of clock   aspects of the analysis that the analyst wishes to optimize.\n(real) time, such as elemental X-ray mapping. For quantita-  As a starting point, a useful general analysis strategy is to\ntive analysis, better peak resolution is desirable, and thus a  optimize the excitation of photon energies up to 12 keV\nlonger time constant should be chosen. Whichever time  by choosing an incident beam energy of 20 keV, which\nconstant strategy is selected, it is important for standards-   provides sufficient overvoltage (E0/Ec\u2009>\u20091.5) for K-shell\nbased quantitative analysis that this same time constant be   (to Br) and L-shell (elements to Bi) for reasonable excita-\nused for all measurements of unknowns and standards,   tion. The characteristic peaks of X-ray families that occur\nespecially if archived standards are used.                     in the photon energy range from 4 keV to 12 keV are gen-\n                                                                 erally sufficiently separated in energy to be resolved by\nEDS Calibration                                 EDS. When  it is important to measure those elements\nAssigning the proper energy bin for a photon measure-  whose characteristic peaks occur below 4 keV, and espe-\nment depends on the EDS being calibrated. The vendor for   cially for the low atomic number elements Be, B, C, N, O\na particular EDS system will have a recommended calibra-  and F, for which the characteristic peaks occur below\ntion procedure that should be followed on a regular basis  1 keV and suffer high absorption, then analysis with\nas part of establishing a quality measurement environ-  lower beam energy, 10 keV or lower, will be necessary to\nment, with full documentation of the measurements to  optimize the results.\nestablish the on-\u00adgoing calibration record. A typical cali-\nbration strategy is to choose a material such as Cu that\nprovides (with E0\u2009\u2265\u200915 keV) strongly excited peaks in the   20.2.3  Measuring the Beam Current\nlow photon energy range (Cu L3M5\u2009=\u20090.93 keV) and the\nhigh  photon  energy  range  (Cu  K-L2,3\u2009=\u20098.04  keV).  The SEM should be equipped for beam current measure-\nAlternatively, some EDS systems that provide a \u201czero  ment, ideally with an in-column Faraday cup which can be\nenergy reference\u201d signal will use this value with a single   selected periodically during the analysis procedure to\nhigh photon energy peak such as Cu K-L2,3 or Mn K-L2,3 to  determine the beam current. As an alternative, a picoam-\nperform calibration. A good quality assurance practice is  meter can be installed between the electrically isolated\nto begin each measurement campaign by measuring a  specimen stage and the electrical ground to measure the\nspectrum of Cu (or another element, e.g., Mn, Ni, etc., or a  absorbed (specimen) current that must flow to ground to\ncompound, e.g., CuS, FeS2, etc.) under the user-defined   avoid specimen charging. The specimen current is the dif-\nconditions. This Cu spectrum can be compared to the Cu   ference between the beam current and the loss of charge\nspectrum that is stored in the archive of standards to con-  due to BSE and SE emission, both of which vary with com-\nfirm that the current measurement conditions are identi-   position. To measure the true beam current, BSE and SE\ncal to those used to create the archive. This starting Cu  emission must be recaptured, which is accomplished by\nspectrum should always be saved as part of the quality   placing the beam within a Faraday cup, which is con-\nassurance plan.                                            structed as a blind hole in a conducting material (e.g.,\n                                                      metal or carbon) covered with a small entrance aperture\nEDS Solid Angle                                                   (e.g., an electron microscope aperture of 50 \u03bcm diameter\nThe solid angle of collection, \u03a9, is given by                  or less). This Faraday cup is then placed at a suitable loca-\n                                                            tion on the electrically isolated specimen stage. By locat-\n   \u2126= A / r 2                                           (20.1)   ing the beam in the center of the Faraday cup aperture\n                                                        opening, the primary beam electrons as well as all BSEs\nwhere A is the active area of the detector and r is the distance  and SEs generated at the inner surfaces are collected with\nfrom the X-ray source on the specimen to the detector. Some   very little loss through the small aperture, so that the cur-\nEDS  systems  are mounted on  a  retractable arm  that   rent flowing to the electrical ground is the total incident\nenables the analyst to choose the value of r. A consistent and  beam current.           314    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n          \n\n## 3. goldstein2018quantitativeanalysisthe pages 9-11 (Context ID: pqac-00000008)\n\ne as\n   and Fe as fitting references and standards Integrated spectrum             fitting references and standards Integrated spectrum count,\n    count, 0.1.\u201320 keV\u2009=\u20097,765,000; uncertainties expressed in mass          0.1\u201310 keV\u2009=\u20096,253,000); uncertainties expressed in mass\n     fraction. Analysis performed with Fe K-L2,3 and S K-L2,3                       fraction. Analysis performed with Fe K-L2,3 and S K-L2,3\n\n                                   S           Fe                                              S            Fe\n\n    Cav (atom frac)                      0.6726        0.3274              Cav (atom frac)                     0.671           0.329\n\n    Z-correction                        0.957          0.928              Z-correction                       0.95             0.91\n\n    A-correction                        1.181          0.975              A-correction                      1.061           0.995\n\n    F-correction                        1.003         1                  F-correction                       1.001          1\n\n   \u03c3 (7 replicates)                     0.000314      0.000314        \u03c3 (7 replicates)                    0.0007          0.0007\n     \u03c3Rel (%)                             0.05\u2009%         0.10\u2009%                \u03c3Rel (%)                            0.11\u2009%           0.21\u2009%\n   RDEV (%)                           0.88\u2009%       \u22121.80\u2009%          RDEV (%)                          0.65\u2009%        \u22121.30\u2009%\n\n   C (mass frac, single analysis)         0.5485        0.4657          C (mass frac, single analysis)        0.537           0.4618\n\n    Counting error, std                  0.0003        0.0002           Counting error, std                0.0003          0.0006\n\n    Counting error, unk                 0.0003        0.0006           Counting error, unk                0.0003          0.0016\n\n    A-factor error                       0.0023        0.0002             A-factor error                     0.0008          4.30E-05\n\n    Z-factor error                       3.30\u00d710\u20135      2.90\u00d710\u20136          Z-factor error                      3.20\u00d710\u20135       9.60\u00d710\u20137\n\n   Combined errors                   0.0023        0.0007          Combined errors                  0.0009          0.0017\n\n\nchoice of beam energy. If the beam energy can be decreased,  10 keV gives the results shown in .\u2003 Tables 20.3 and 20.4. The\nconsidering also the constraints imposed by having sufficient   absorption factor A from is reduced from 1.118 to 1.04 for S\novervoltage for all elements to be analyzed, the absorption   in FeS and from 1.18 to 1.06 for S in FeS2, and the relative\ncorrection factor and its uncertainty can also be reduced. For   errors are also reduced slightly, from 1 to 0.59\u2009% for S in FeS\nthe Fe-S examples, lowering the beam energy from 20 to  and from 0.88 to 0.65\u2009% for S in FeS2.           318    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n          20.3.2  Analysis of Major Constituents            separated by 36 eV, as shown in .\u2003 Fig. 20.5. Analysis of PbS\n                 (C\u2009>\u20090.1 Mass Fraction) with Severely    with DTSA II using CuS and PbSe as peak-fitting references\n             Overlapping Peaks                       and as standards yields the results in .\u2003 Table 20.5. Despite\n                                                                      the severe peak interference, the relative error based on the\n                                                                 formula stoichiometry is only \u00b11.2\u2009% for S and Pb.\n       PbS                                                                Note that an alternative analytical approach would be to\n         The throughput and the peak stability (calibration and reso-   select the beam energy such that E0\u2009\u2265\u200920 keV so that the Pb\n           lution) of SDD-EDS spectrometry enable collection of high   L-family is excited (LIII\u2009=\u200913.04 keV). With this choice of exci-\n          count, high quality spectra (>5 million counts) within mod-   tation, the Pb L3-M4,5 peak at 10.55 keV, which does not suffer\n            est measurement time, 100 s or less. High count spectra   interference, could be chosen to measure Pb. Of course, the S\n          enable measurements of minor and trace constituents with  K still must be deconvoluted from the interference from the\n          high precision. High counts and stable peak structures are  Pb M-family since there is no alternate peak to measure for S.\n             critical for successful peak intensity measurements by peak-\u00ad\n             fitting methods, which is especially important for situations  MoS2\n         where two or more peaks are so close in photon energy that  MoS2 represents an even greater analytical challenge because\n          the EDS resolution function convolves the peaks into mutual   the peaks that must be used for analysis, S K-L2 (2.307 keV)\n           interference. Despite extreme peak interference, quantitative  and Mo L3-M4,5 (2.293 keV), are separated by only 14 eV, as\n          X-ray microanalysis can be achieved with RDEV values of  shown in .\u2003 Fig. 20.6. Analysis of MoS2 with DTSA II using\n          5\u2009% relative or less (Newbury and Ritchie 2015a).          CuS and Mo as peak-fitting references and as standards yields\n           PbS (galena) represents a challenging analysis situation   the results in .\u2003 Table 20.6. Despite the severe peak interfer-\n           for EDS because of the severe interference between the S   ence, the relative error based on the formula stoichiometry is\n         K-L2 (2.307 keV) and Pb M5-N6,7 (2.343 keV), which are   only \u22120.34\u2009% for S and 0.7\u2009% for Mo.\n\n\n             a 120 000                                                                                                                    PbS_10kV20nA\n                                                                                                                                                           Residual_PbS_10kV20nA\n\n                100 000                                                                                                   E0 = 10 KeV\n                                                                                PbS\n                 80 000                                                                                Fitting residual\n\n\n                 60 000                                   Counts\n\n                 40 000\n\n\n                 20 000\n\n\n                     0\n                            1.5          1.7          1.9          2.1          2.3          2.5          2.7          2.9          3.1          3.3\n                                                                   Photon energy (keV)\n\n           b                                                                                                                             PbS_10kV20nA\n                 14 000                                                                                                                            Residual_PbS_10kV20nA\n\n                 12 000\n\n                 10 000\n\n                  8 00020                         Counts\n                  6 000\n\n                  4 000\n\n                  2 000\n\n                     0\n                            1.5          1.7          1.9          2.1          2.3          2.5          2.7          2.9          3.1          3.3\n                                                                   Photon energy (keV)\n\n\n      . .\u200a\u200a\u200aFig. 20.5\u2003  a SDD-EDS spectrum of PbS (red) and residual (blue) after DTSA II analysis using CuS and PbSe as fitting references and standards.\n         b Expanded view                                                                                                              319                                      20\n20.4 \u00b7 The Need for an Iterative Qualitative and Quantitative Analysis Strategy\n\n\n                                                                    analysis, O has been directly analyzed with the k-ratio/matrix\n  . .\u200a\u200a\u200aTable 20.5\u2003  Analysis of PbS at E0\u2009=\u200910 keV with CuS and PbSe                                                              corrections protocol and not by the method of assumed stoi-    as fitting references and standards; Integrated spectrum count,\n    0.1\u201310 keV\u2009=\u20095,482,000; uncertainties expressed in mass fraction.     chiometry. The analytical results are seen to closely match the\n    Analysis performed with Pb M5-N6,7 and S K-L2,3                  stoichiometry of the ideal mineral formula.\n\n                                  S           Pb\n                                                         20.3.5  Ba-Ti Interference: Major/Minor    Cav (atom frac)                       0.4938        0.5062                                                  Constituent Interference in K2496\n    Z-correction                          1.31          0.983            Microanalysis Glass\n    A-correction                         1.028         1.05\n\n## 4. goldstein2018quantitativeanalysisthe pages 6-8 (Context ID: pqac-00000009)\n\nin the center of the Faraday cup aperture\n                                                        opening, the primary beam electrons as well as all BSEs\nwhere A is the active area of the detector and r is the distance  and SEs generated at the inner surfaces are collected with\nfrom the X-ray source on the specimen to the detector. Some   very little loss through the small aperture, so that the cur-\nEDS  systems  are mounted on  a  retractable arm  that   rent flowing to the electrical ground is the total incident\nenables the analyst to choose the value of r. A consistent and  beam current.           314    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n          20.2.4  Choosing the Beam Current            SDD-EDS, a more conservative counting strategy is sug-\n                                                                          gested, such that the beam current is chosen so that the\n           After the analyst has chosen the EDS time constant, the   dead-\u00adtime on the most highly excited standard of interest,\n           detector solid angle (for a retractable detector), and the beam   for example, Al or Si, is less than 10\u2009%. Despite the opera-\n           energy, the beam current should be chosen so as to give a   tion of the anti-coincidence function, SDD-EDS systems\n          reasonable detector throughput, as expressed by the system   typically show evidence of coincidence peaks above a dead-\n          dead-time. .\u2003 Figure 20.2 shows the relationship between the  time of 10\u2009% from highly excited parent peaks, as illustrated\n          input count rate (ICR) of X-rays that arrive at the detector   in .\u2003 Fig. 20.3, which shows the in-growth of an extensive\n         and the output count rate (OCR) of photons that are actually   set of coincidence peaks from several parent peaks. If it is\n           stored in the measured spectrum. The OCR initially rises lin-  important to measure low intensity X-ray peaks that cor-\n           early with the ICR, but as photons arrive at a progressively  respond to minor or trace constituents that occur in spec-\n           greater rate at the detector, photon coincidence begins to   tral regions affected by coincidence peaks, then choosing\n          occur and the anti-coincidence function begins to reject   the low dead-\u00adtime to minimize coincidence will be an\n           these coincidence events, reducing the OCR. Eventually a  important issue in selecting the general analytical condi-\n       maximum OCR value is reached beyond which the OCR   tions. If there is no interest in measuring X-ray peaks of\n          decreases with increasing ICR, eventually falling to zero   possible constituents that occur in the region of coinci-\n           (\u201cparalyzable dead-time\u201d). A useful measure of the activity  dence peaks, then these regions can be ignored and a\n            state of the EDS detector is the system \u201cdead-time\u201d which is  counting strategy that involves higher dead-time operation\n          defined as                                             can be used.\n                                                          Once the analytical conditions (EDS time constant, solid\n                                               100    (20.2)   angle, beam energy, and beam current appropriate to the                Dead-time ( % ) = \uf8ee\uf8f0 (                           ICR \u2212 OCR ) / ICR \uf8f9\uf8fb\u2217\n                                                                 complete suite of standards) have been chosen, these condi-\n      A classic strategy with the low throughput Si(Li)-EDS is to   tions should be used for all standards and unknowns to\n           select a beam current on a highly excited pure element such   achieve the basic measurement consistency required for the\n           as Al or Si that produces a dead-time of 30\u2009% or less. With   k-ratio/matrix corrections protocol.\n\n\n\n      . .\u200a\u200a\u200aFig. 20.2\u2003  Output count rate\n           (OCR) vs. input count rate for an\n          SDD-EDS array of four 10-mm2                                  30 mm2 SDD at medium throughtput\n            detectors\n                                                  200,000\n                                                                                                                        Ideal response\n                                                                                                         (no deadtime)\n\n                                                  160,000\n                                                                                                                                                                                                    (counts/s)\n                                                  120,000\n                                                                              Rate\n                                                                                                  Count\n                                                    80,000\n                                                                                                                      Output\n\n                                                    40,000\n20\n\n                                                   0\n                                                     0          40,000        80,000       120,000       160,000      200,000\n                                                                                     Input Count Rate (counts/s)                                                                                                               315                                      20\n20.2 \u00b7 Instrumentation Requirements\n\n\n\n\n   a\n     3 500 000                                                                                                    K412_20kV5nAMED5eV40kHz3DT_5ks\n\n     3 000 000                                  SRM470 Glass K412\n                                                           E0 = 20 keV\n                                                  Deadtime = 3%\n     2 500 000\n\n\n     2 000 000       Counts\n     1 500 000\n\n\n     1 000 000\n\n     5 000 000\n\n\n            0\n                0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                       Photon energy (keV)\n\n  b\n                                                                                                                     K412_20kV5nAMED5eV40kHz3DT_5ks\n\n      100 000\n\n\n       80 000\n\n\n       60 000       Counts\n\n\n       40 000\n\n\n       20 000\n\n\n            0\n               0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                       Photon energy (keV)\n\n   c                                                                                                                       K412_20kV5nA40kHz_3DT\n                                                                                      Al+Al                                                                        K412_20kV50nA387kHz_29DT\n\n                                                                         SRM470 Glass K412                                                      Si+O                Si+Mg;      Si+Si                                           E0 = 20 keV\n                                                                                Deadtime = 3%\n                                                                                Deadtime = 29%         Counts\n                                                                                                                                     Mg+Ca      Si+Ca\n\n\n\n\n\n       0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0         10.0\n                                                      Photon energy (keV)\n\n\n. .\u200a\u200a\u200aFig. 20.3\u2003 SDD-EDS spectra of NIST SRM (glass K412, E0\u2009=\u200920 keV: a, b at 3\u2009% dead-time (red); c 3\u2009% (red) and 29\u2009% dead-time (blue), showing\nin-growth of coincidence peaks           316    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n         20.3 Examples of the k-ratio/Matrix              the error budget. In this analysis and the analyses reported\n             Correction Protocol with DTSA II            below, the relative deviation from the expected value (RDEV)\n           (Newbury and Ritchie 2015b)                    (also referred to as \u201crelative error\u201d) is calculated with the\n                                                                       \u201cexpected\u201d value taken as the stoichiometric formula value or\n          20.3.1  Analysis of Major Constituents            the value obtained from an \u201cabsolute\u201d analytical method, just\n                 (C\u2009>\u20090.1 Mass Fraction\n\n## 5. goldstein2018quantitativeanalysisthe pages 1-4 (Context ID: pqac-00000010)\n\n                                                                               309                              20\n\nQuantitative Analysis:\nThe SEM/EDS Elemental\nMicroanalysis k-ratio Procedure\nfor Bulk Specimens,\nStep-by-Step\n\n\n20.1   Requirements Imposed on the Specimen\n      and Standards \u2013 311\n\n20.2   Instrumentation Requirements \u2013 311\n20.2.1   Choosing the EDS Parameters \u2013 311\n20.2.2   Choosing the Beam Energy, E0 \u2013 313\n20.2.3   Measuring the Beam Current \u2013 313\n20.2.4   Choosing the Beam Current \u2013 314\n\n20.3   Examples of the k-ratio/Matrix Correction\n        Protocol with DTSA II \u2013 316\n20.3.1   Analysis of Major Constituents (C\u2009>\u20090.1 Mass Fraction)\n        with Well-\u00adResolved Peaks \u2013 316\n20.3.2   Analysis of Major Constituents (C\u2009>\u20090.1 Mass Fraction)\n        with Severely Overlapping Peaks \u2013 318\n20.3.3   Analysis of a Minor Constituent with Peak Overlap\n       From a Major Constituent \u2013 319\n20.3.4   Ba-Ti Interference in BaTiSi3O9 \u2013 319\n20.3.5   Ba-Ti Interference: Major/Minor Constituent Interference\n          in K2496 Microanalysis Glass \u2013 319\n\n20.4   The Need for an Iterative Qualitative and\n        Quantitative Analysis Strategy \u2013 319\n20.4.1   Analysis of a Complex Metal Alloy, IN100 \u2013 320\n20.4.2   Analysis of a Stainless Steel \u2013 323\n20.4.3   Progressive Discovery: Repeated Qualitative\u2013Quantitative Analysis\n        Sequences \u2013 324\n\n20.5     Is the Specimen Homogeneous? \u2013 326\n\n\n\n\n\n\u00a9 Springer Science+Business Media LLC 2018\nJ. Goldstein et al., Scanning Electron Microscopy and X-Ray Microanalysis,\nhttps://doi.org/10.1007/978-1-4939-6676-9_2020.6   Beam-Sensitive Specimens \u2013 331\n20.6.1   Alkali Element Migration \u2013 331\n20.6.2   Materials Subject to Mass Loss During Electron\n       Bombardment\u2014the Marshall-Hall Method \u2013 334\n\n       References \u2013 339                                                                                                                 311                                      20\n20.2 \u00b7 Instrumentation Requirements\n\n\nThis chapter discusses the procedure used to perform a rig-      grinding and polishing. \u201cChemical polishing\u201d should\norous quantitative elemental microanalysis by SEM/EDS     be avoided since chemical reactions may induce shal-\nfollowing the k-ratio/matrix correction protocol using the      low, near-surface compositional changes that affect\nNIST DTSA-II software engine for bulk specimens. Bulk      the very shallow region that is excited and sampled\nspecimens have dimensions that are sufficiently large to     by the electron beam. Ion beam milling can be used\ncontain the full range of the direct electron-excited X-ray      to shape and finish the specimen, but it must be\nproduction (typically 0.5\u201310 \u03bcm) as well as the range of      recognized that implantation of the primary ion and\nsecondary X-ray fluorescence induced by the propagation       differential material removal caused by differences in\nof  the  characteristic and continuum X-rays  (typically      the sputtering rates of the elements can modify the\n10\u2013100 \u03bcm).                                             composition of a shallow surface layer.\n\n20.1  Requirements Imposed                     20.2  Instrumentation Requirements\n    on the Specimen and Standards\n                                                   The basis of the k-ratio/matrix corrections protocol is mea-\nThe k-ratio/matrix correction protocol for the analysis of  surement of the X-ray spectra of the specimen and standard\nbulk specimens has two basic underlying assumptions:        (s) under identical conditions of beam energy, known elec-\n1. The composition is homogeneous throughout the entire   tron dose (the product of beam current and EDS live-time,\n   volume of the specimen in which primary characteristic   with  accurate  dead-time  correction), EDS  parameters\n   X-rays are directly excited by the incident electron beam   (detector solid angle, time constant, calibration, and window\n   and in which secondary X-ray fluorescence is induced      efficiency), target orientation (tilt angle, ideally 0\u00b0 tilt, i.e.,\n   during the propagation of the primary characteristic    beam perpendicular to the target surface), and EDS take-off\n   and continuum X-rays. A compositionally heteroge-     angle (i.e., the detector elevation angle above the flat sample\n   neous specimen which does not satisfy this requirement   surface).\n   cannot be analyzed by the conventional k-ratio/matrix\n   correction protocol. Examples of such heterogeneous\n   specimens include a horizontally layered specimen such   20.2.1  Choosing the EDS Parameters\n    as a thin film on a substrate or an inclusion with dimen-\n   sions similar to the interaction volume embedded in a     Consistency in the choice of the EDS parameters is critical\n   matrix. Such specimens must be analyzed with protocols   for establishing a robust analytical measurement environ-\n    that account for the effects of the particular specimen     ment, and this is especially important when archived stan-\n   geometry.                                           dard spectra are used.\n2. The X-ray intensities measured on the location of\n                                     EDS Spectrum Channel Energy Width    interest on the specimen and on the standard(s) differ\n   only because the compositions are different. No other  and Spectrum Energy Span\n    factors modify the measured intensities. In particular,   As shown in .\u2003 Fig. 20.1, when the energy axis is expanded\n   geometric effects that arise from physical surface         sufficiently, the EDS spectrum is seen to be a histogram of\n    defects, such as scratches, pits, and so on, can modify   energy channels of a specific width (e.g., 5 eV, 10 eV,\n   the interaction of the electron beam (electron back-     20 eV) and number (e.g., 1024, 2048, 4096). For accurate\n    scattering, beam penetration) with the specimen and     peak-\u00adfitting purposes, it is desirable to have an adequate\n   can alter the subsequent X-ray absorption path length  number of channels spanning the characteristic X-ray\n   to the detector compared to an ideal flat bulk speci-     peaks. Because the EDS resolution is a function of photon\n   men. This requirement places strict conditions on the   energy, low photon energy peaks below 1 keV are substan-\n   surface condition of the specimen and standards. A       tially narrower than higher energy peaks. A choice of 5 eV\n   highly polished, flat surface must be created following   for the channel energy width will provide a sufficient num-\n   the appropriate metallographic preparation proto-      ber of channels to adequately span all of the peaks of ana-\n   col for each particular material. The surface should       lytical  interest, including the peaks that occur below\n   be finished to a surface roughness below 100 nm       1 keV. C K-L2,3 is broadened in EDS to approximately\n   root mean square (rms) with a typical final polish      50 eV full width at half-maximum (FWHM), so a choice of\n   performed with 100-nm diamond, alumina, ceria       5-eV/channel will provide at least 10 channels to span the\n   or other polishing compound as appropriate. When     low photon energy peaks, which is important for accurate\n   the analysis involves measuring low energy photons     peak fitting. It is also desirable for the measured spectrum\n   below 1 keV (e.g., for the elements Be, B, C, N, O,        to span the full range of the excited X-ray energy, from an\n   and F), the surface finish should be better than 50 nm    effective threshold of approximately 100 eV to the Duane\u2013\n   rms. The preparation protocol should utilize physical   Hunt  limit, which corresponds to the incident beam           312    Chapter 20 \u00b7 Quantitative Analysis: The SEM/EDS Elemental Microanalysis k-ratio Procedure for Bulk Specimens, Step-by-Step\n\n\n\n\n                100 000\n                                                                                                                                         Mn_20kv10nA110kHz10DT\n\n\n                 80 000\n                                    Mn\n                                                         E0 = 20 keV\n\n                 60 000\n                                   Counts\n                 40 000\n\n\n\n                 20 000\n\n\n\n                     0\n                            0.0          1.0          2.0          3.0          4.0          5.0          6.0          7.0          8.0          9.0        10.0\n                                                                 Photon energy (keV)\n\n                100 000\n                                                                                                                                         Mn_20kv10nA110kHz10DT\n\n\n                 80 000\n\n                                                                                            5 eV bin width\n                 60 000\n                                   Counts\n                                                                  FWHM = 126 eV       \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010]\n\nStatus: Paper Count=21 | Relevant Papers=2 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=11 | Current Cost=$0.0763 | Disease-Target Evidence=0",
+                "name": "read_text",
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+                "role": "assistant",
+                "content": "Excellent, I'm getting key information from the Goldstein textbook. Now let me gather more evidence on specific topics and read more texts:",
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+                  {
+                    "id": "toolu_013vVvegTrjexARbtxRSSCnE",
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+                    "function": {
+                      "arguments": "{\"question\": \"What is the dead-time model for EDS detectors? How does output count rate relate to input count rate? What is paralyzable dead-time and why does dead-time of 20-40% or 10% give optimal throughput? What is the anti-coincidence function?\"}",
+                      "name": "gather_evidence"
+                    }
+                  },
+                  {
+                    "id": "toolu_01J2ypPovB8SRU9gXMtXVnSM",
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+                      "arguments": "{\"question\": \"What is the relationship between pulse process time (shaping time) and energy resolution vs throughput in SDD-EDS detectors? How does electronic noise and series noise trade-off determine optimal shaping time?\"}",
+                      "name": "gather_evidence"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000011\n\nFrom text 'goldstein2018energydispersivexray pages 9-10'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\nThe excerpt describes EDS dead-time characteristics. X-rays arrive randomly, but the EDS system can only measure one photon at a time, becoming unavailable during measurement. The dead-time percentage is calculated as (ICR - OCR)/ICR \u00d7 100%, where ICR is input count rate and OCR is output count rate, shown graphically in Fig. 16.9. The anti-coincidence function excludes photons arriving during busy periods, though if the first photon measurement isn't sufficiently advanced, both photons may be excluded and lost. An automatic dead-time correction adds additional measurement time to maintain constant \"live-time\" for quantitative measurements. Dead-time increases with beam current, and the correction circuit can compensate across the full dead-time range to 80% or higher.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011]\n\nStatus: Paper Count=21 | Relevant Papers=2 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=12 | Current Cost=$0.1104 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
+                "tool_call_id": "toolu_013vVvegTrjexARbtxRSSCnE",
+                "info": {
+                  "start_ts": 2768.050388711,
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+                }
+              },
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+                "role": "tool",
+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000012\n\nFrom text 'blaj2017optimalpulseprocessing pages 2-2'.\n\nG. Blaj, C. J. Kenney, A. Dragone, G. Carini, S. Herrmann, P. Hart, A. Tomada, J. Koglin, G. Haller, S. Boutet, M. Messerschmidt, G. Williams, M. Chollet, G. Dakovski, S. Nelson, J. Pines, S. Song, and J. Thayer. Optimal pulse processing, pile-up decomposition, and applications of silicon drift detectors at lcls. IEEE Transactions on Nuclear Science, 64:2854-2868, Jun 2017. URL: https://doi.org/10.48550/arxiv.1706.01211, doi:10.48550/arxiv.1706.01211. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses the trade-off between pulse shaping time and detector performance in silicon drift detectors (SDDs). Longer pulse shaping and decay times increase pile-up probability, while shorter peaking times increase noise hyperbolically. The document indicates that without pulse shaping, rise time variations become significant and must be accounted for in fitting procedures to maintain optimal energy resolution. The authors demonstrate an approach eliminating pulse shaping altogether, where signal amplitude is obtained through fitting with the pulse function while accounting for variable rise times, achieving approximately 730 ns pulse separation without requiring pulse rejection.\n\n\n---\n\n## pqac-00000013\n\nFrom text 'blaj2017optimalpulseprocessing pages 13-14'.\n\nG. Blaj, C. J. Kenney, A. Dragone, G. Carini, S. Herrmann, P. Hart, A. Tomada, J. Koglin, G. Haller, S. Boutet, M. Messerschmidt, G. Williams, M. Chollet, G. Dakovski, S. Nelson, J. Pines, S. Song, and J. Thayer. Optimal pulse processing, pile-up decomposition, and applications of silicon drift detectors at lcls. IEEE Transactions on Nuclear Science, 64:2854-2868, Jun 2017. URL: https://doi.org/10.48550/arxiv.1706.01211, doi:10.48550/arxiv.1706.01211. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses the tradeoff between pulse processing parameters and detector performance. It describes a fundamental compromise in typical pulse processing between counting rate (achieved with short rise times) and energy resolution (requiring long rise times through pulse shaping), necessitating selection of an appropriate peaking time. However, the authors present an alternative approach using pulse waveform fitting with pulse functions rather than traditional pulse shaping. This fitting method eliminates the need for pulse shaping while achieving fast pulse onset, improved pulse separation, and the ability to handle multiple overlapping pulses. The method extracts precise amplitude and timing information by fitting each pulse waveform to a combined gradual step function and exponential decay model.\n\n\n---\n\n## pqac-00000014\n\nFrom text 'goldstein2018energydispersivexray pages 25-26'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\nThe excerpt discusses the fundamental trade-off in EDS detectors between pulse process time, energy resolution, and throughput. Longer pulse process times achieve better energy resolution but produce poor ultimate throughput. Conversely, shorter pulse process times maximize throughput but introduce coincidence events (pulse pile-up) that limit quantitative accuracy. The document indicates that optimal detector performance involves a three-way trade-off between throughput, resolution, and coincidence rate. Practically, operators define an acceptable coincidence rate and select a process time that maximizes throughput while maintaining that rate, typically sacrificing only a few eV of resolution quality. This resolution compromise is deemed acceptable since accurate quantitative analysis prioritizes throughput over optimal resolution. However, the excerpt does not specifically address the electronic noise and series noise components or their detailed relationship to determining optimal shaping time.\n\n\n---\n\n## pqac-00000015\n\nFrom text 'goldstein2018energydispersivexray pages 14-15'.\n\nJoseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\nThe excerpt explains the inverse relationship between pulse process time and detector performance in SDD-EDS systems. Longer process times produce better spectral resolution but lower X-ray throughput, while shorter process times increase throughput at the expense of resolution. The text emphasizes that resolution degrades slowly relative to throughput gains when reducing process time. Moderate process time settings typically degrade resolution by only a few percent while substantially increasing throughput. Modern SDDs achieving 122-128 eV resolution can be compromised to 130-150 eV while maintaining excellent quantitative analysis, since precision depends more on the number of measured X-rays than spectral resolution alone. The excerpt does not discuss the electronic noise or series noise components that determine optimal shaping time.\n\n\n---\n\n## pqac-00000016\n\nFrom text 'newbury2011isscanningelectron pages 2-3'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\nThe excerpt demonstrates the inverse relationship between pulse processing time constant (shaping time) and detector performance metrics in SDD-EDS systems. Shorter time constants enable higher throughput (OCR) but with a resolution trade-off. For example, a 500 ns time constant achieves resolution below 130 eV (MnK\u03b1), while reducing the time constant to 220 ns increases maximum OCR to 270 kHz but degrades resolution to 145 eV. The text illustrates that SDD-EDS detectors significantly outperform Si(Li)-EDS in throughput capability (by a factor of at least 60 for similar resolution), and this improved count rate performance enables collection of statistically robust spectra within practical measurement intervals. However, the excerpt does not explicitly discuss the underlying noise mechanisms (electronic noise vs. series noise) or the theoretical optimization process for determining optimal shaping time based on noise trade-offs.\n\n\n---\n\n## pqac-00000017\n\nFrom text 'blaj2017optimalpulseprocessing pages 1-2'.\n\nG. Blaj, C. J. Kenney, A. Dragone, G. Carini, S. Herrmann, P. Hart, A. Tomada, J. Koglin, G. Haller, S. Boutet, M. Messerschmidt, G. Williams, M. Chollet, G. Dakovski, S. Nelson, J. Pines, S. Song, and J. Thayer. Optimal pulse processing, pile-up decomposition, and applications of silicon drift detectors at lcls. IEEE Transactions on Nuclear Science, 64:2854-2868, Jun 2017. URL: https://doi.org/10.48550/arxiv.1706.01211, doi:10.48550/arxiv.1706.01211. This article has 15 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses silicon drift detectors (SDDs) at free-electron lasers and presents an alternative to traditional pulse shaping approaches. Rather than using conventional pulse shaping, the authors demonstrate that waveform fitting with signal amplitude and rise time parameters can achieve simultaneously high energy resolution and high counting rates (2 orders of magnitude higher than conventional digital pulse processors). By avoiding pulse shaping entirely, they achieved rise times of tens of nanoseconds, which resulted in reduced pulse pile-up. This approach allows decomposition of remaining pile-up at photon separation times down to hundreds of nanoseconds while maintaining 10 nanosecond time-of-arrival precision. However, the excerpt does not explicitly address the trade-off between electronic noise and series noise in determining optimal shaping time, nor does it provide detailed quantitative analysis of the relationship between shaping time and the energy resolution versus throughput trade-off.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017]\n\nStatus: Paper Count=21 | Relevant Papers=4 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=18 | Current Cost=$0.1511 | Disease-Target Evidence=0",
+                "name": "gather_evidence",
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+                  "end_ts": 2782.600824802
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Good. Now let me read the Currie paper and gather evidence on detection limits, and search for the SDD noise trade-off:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01R4XA96akT6vHtcV3eGPRMj",
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+                      "arguments": "{\"text_name_list\": [\"currie1999detectionandquantification pages 1-2\", \"currie1999detectionandquantification pages 2-4\", \"currie1999detectionandquantification pages 4-6\", \"currie1999detectionandquantification pages 6-7\", \"currie1999detectionandquantification pages 7-8\"]}",
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+                  {
+                    "id": "toolu_01FNAV5kmdFvTHg1GUnqvKRN",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"query\": \"SDD silicon drift detector noise components parallel series 1/f ballistic deficit shaping time energy resolution optimization\"}",
+                      "name": "paper_search"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "## 1. currie1999detectionandquantification pages 4-6 (Context ID: pqac-00000018)\n\n Poisson counting processes; and  (b)\nof the estimator ^L: under the null hypothesis, at the      (standard deviation) increasing in a linear fashion.\ndetection limit, and at the quanti\u00aecation limit, respec-      Detailed treatment of this issue is beyond the scope\ntively; s20 represents an estimate of   20, based on v      of this document, but further information may be\ndegrees of freedom; z and t represent the appropriate     found in [2]. To illustrate, given normality, negligible\none-sided critical values of the standard normal variate      uncertainty in the mean value of the blank (such that\nand Students-t, respectively; and  represents the non-    0!  B), and   \u0085^S\u0086 increasing with a constant slope\ncentrality parameter of the non-central t distribution.      (d /dS) of 0.04 \u00b1 equivalent to an asymptotic relative\nThe actual value for  (0.05, 0.05, 4) appearing above      standard deviation (RSD) of 4%, we \u00aend the follow-\n(Eq. (5b)) is 4.07.                                           ing:\n  The above relations represent the simplest possible\n                                               LC \u0088 1:645 B;                                     (7)\ncase, based on restrictive assumptions; they should in\nno way be taken, however, as the de\u00aening relations for     LD \u0088 LC \u0087 1:645 D;   with  D \u0088  B \u0087 0:04LD;\ndetection and quanti\u00aecation capabilities. Some inter-                                                           (8)\nesting  complications  arise when  the  simplifying\n                                             LQ \u0088 10 Q;   with  Q \u0088  B \u0087 0:04LQ:           (9)\nassumptions do not apply. These will be discussed\nbelow. It should be noted, in the second expressions        Solutions to Eqs. (8) and (9) are LD\u00883.52  B, and\nfor LC and LD given above, that although s0 may be     LQ\u008816.67  B, respectively. Thus, with a linear relation\nused for a rigorous detection test,   0 is required to      for   \u0085^S\u0086, with intercept  B and a 4% asymptotic RSD,\ncalculate the detection limit. If s0 is used for this      the ratio of the quanti\u00aecation limit to the detection\npurpose, the calculated detection limit must be viewed      limit is increased from 3.04 to 4.73.\nas an estimate with an uncertainty derived from that of          If   increases too sharply, LD and/or LQ may not be\n  /s. Finally, for chemical measurements at least, the      attainable for the CMP in question. This problem may\nfundamental contributing factor to  0, and hence to the     be attacked through replication, given   reduction by                              pdetection and quanti\u00aecation performance characteris-     1=     \u0081\u0081n , but caution should be exercised since unsus-\ntics is the variability of the blank. This, together with     pected systematic error will not be correspondingly\nthe in\u00afuence of heteroscedasticity, is introduced for-     reduced!\nmally in Section 2.2.2.\n   Finally, there is the link to the ``outside world''.      2.2.3. The Zero myth\nDetection or quanti\u00aecation capabilities are generally        In many cases the lay public believes, given suf\u00ae-\nof interest because of an external driving force LR,      cient effort or funding, that a concentration of zero\nwhich we take as an external value that the CMP must    may be detected and/or achieved. Not unlike the third\nbe able to detect (or quantify). To illustrate such a     law of thermodynamics, however, neither is possible,\nrelationship, as well as most of the foregoing princi-     even in concept. A policy of reporting ``zero'' when                                        L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134                              131\n\n^L < LC, yielding the decision ``not detected'', com-      different results being obtained for each realization of\npounds this lack of understanding. These are issues of      the calibration curve, even though the underlying\nmajor national importance, especially in the context of     measurement process is \u00aexed. IUPAC [9] suggests\nlegislation and  regulation, where  necessarily, and      dealing with this problem by considering the median\nappropriately, many of the policy makers have critical      of the distribution of such ``detection limits''. (The\nsociopolitical expertise, but not necessarily scienti\u00aec     expected value is in\u00aenity.) An alternative, suggested in\nor technical expertise. The solution to this sociotech-      [9] and developed in [3], treats the exact, non-normal\nnical dilemma is, once again, very careful commu-      distribution of ^x in developing concentration detection\nnication; and, beyond that, mutual understanding and       limits.\neducation among the complementary disciplines.\n  One possible (partial) solution to this dilemma is the\nsubstitution of a non-zero value L0 for characterizing      3. Trans-definitional issues\nthe null hypothesis. Eq. (1) would then take the form\n                                                                3.1. Specification of the measurement (and\nPr\u0085^L > LCjL \u0088 L0\u0086       :                        (10)                                                               evaluation) process\n  Further discussion of such a non-zero null is given\nin Chapter 1 of [2] in connection with discrimination        This is absolutely essential. Quoting from Section\nlimits (Section 3.3.1).                                      3.7.2 of IUPAC [9]: ``Just as with other performance\n                                                                characteristics, LD and LQ cannot be speci\u00aeed in the\n2.2.4. Signal and concentration domains                absence of a  fully de\u00aened measurement process,\n  Formulation of the generic, de\u00aening ``L'' expres-      including such matters as types and levels of inter-\nsions  for  signal and  concentration  detection and      ference as well as the data reduction algorithm. `Inter-\nquanti\u00aecation limits  is given in [9], and extended      ference  free  detection  limits'  and  `instrument\nin  [3]. Treatment of SC, SD, and SQ  is relatively      detection  limits', for example, are perfectly valid\nstraightforward; but some interesting problems arise      within their respective domains; but if detection or\nin making the transition to the concentration domain,      quanti\u00aecation characteristics are sought for a more\nparticularly when there is non-negligible uncertainty     complex chemical measurement process, involving,\nin the ``sensitivity'' A (slope of the calibration curve).      for example sampling, analyte separation and puri\u00ae-\nFor the simplest (single component, straight  line)      cation, and interference and matrix effects, then it is\ncalibration function the estimated concentration ^x is     mandatory that  all these factors be considered in\ngiven by                                                 deriving values for LD and LQ for that process. Other-\n                                                    wise the actual performance of the CMP (detection,^x \u0088 \u0085y \u00ff ^B\u0086=^A:                                 (11)\n                                                        quanti\u00aecation capabilities) may fall far short of the\n  Although this is the simplest case, it nonetheless      requisite performance''.\noffers challenges, for example, in the application of\nerror propagation for the estimation of the ^x distribu-      3.2. What is sigma?\ntion if ey is non-normal, and for the non-linear parts of\nthe transformation (denominator of Eq. (11)). In [3],       Beyond the conceptual framework for detection and\nwhich treats a normal response only, three cases for      quanti\u00aecation limits, there is probably no more dif\u00ae-\nerror in the estimated slope of the calibration curve are      cult or controversial issue than deciding just what to\nconsidered: (1) negligible (A known), (2) systematic     use for  0 or its estimate s0. Though often ignored, the\n(eA \u00aexed), and (3) random (eA  N(0, VA)). The last of      matter of heteroscedasticity must obviously be taken\nthese is commonly employed to obtain ``calibration''-      into account. But it is crucial also to take into account\nor ``regression''-based detection limits, using a tech-      the complete error budget of the speci\u00aeed measure-\nnique introduced by Hubaux and Vos [6]. This method,     ment process. If this is done successfully, and if all\nhowever, has a drawback in that it yields, ``detection     assumptions are satis\u00aeed, the apparent dichotomy\nlimits'' that are random variables, as acknowledged in     between the intralaboratory approach and the inter-\nthe original publication of the method ([6], p. 850);      laboratory approach to detection and quanti\u00aecation132                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n                                                          estimates for compound CMPs involving different\n                                                       samples, different instruments,  different operators,\n                                                          or even different met\n\n## 2. currie1999detectionandquantification pages 7-8 (Context ID: pqac-00000019)\n\nexamined with respect to contamination and\ninterference contributions, and the whole is then esti-     A graphical representation of these concepts  is\nmated as the sum of its parts \u00b1 with due attention to     given in Fig. 2, where the ``driving force'' in this\ndifferential recoveries and variance propagation. This      hypothetical example is the ability to detect the release\nis an important point: that the blank introduced at one      of speci\u00aec chemical precursors of earthquakes (e.g.,\nstage of the CMP will be attenuated by subsequent      radon)  at  levels corresponding  to earthquakes  of\npartial recoveries. Neither the internal nor the external     magnitude LR and above. Thus LR is the ``requisite\napproach to blank assessment is easy, but one or the       limit'' or maximum acceptable limit for undetected\nother is mandatory for accurate low-level measure-      earthquakes; this is driven, in turn, by a maximum\nments; and consistency (internal, external) is requisite      acceptable loss to society. (Derivation of LR values for\nfor quality. Both approaches require expert chemical      sociotechnical problems, of course, is far more com-\nknowledge concerning the CMP in question.             plex than the subject of this report!) The lower part of\n                                                           the \u00aegure shows the minimum detectable value for the\n                                                     chemical precursor LD, that must not exceed LR, and\n5. Some future challenges                                        its relation to the probability density functions (pdfs)\n                                                                  at L\u00880 and at L\u0088LD together with   and    , and the\n  The ``real world'' holds many complexities and      decision point (critical value) LC. The \u00aegure has been\nchallenges beyond the preceding, relatively straight-     purposely constructed to illustrate heteroscedasticity \u00b1\nforward univariate, linear, and monotonic perspective.\nVery real detection and quanti\u00aecation capability issues         4This example is adapted directly from Section 3.7.3. of [9].134                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n\n                                                                               [2] L.A.  Currie,  (Ed.),  Detection  in  Analytical  Chemistry:\n                                                                          Importance, Theory, and Practice, ACS Symposium Series,\n                                                                                     vol. 361, American Chemical  Society, Washington, DC,\n                                                                        1988.\n                                                                               [3] L.A. Currie, in: International Conference on Environmetrics\n                                                                   and Chemometrics, Las Vegas, NV, 1995, Detection: inter-\n                                                                                national update, and some emerging di-lemmas involving\n                                                                                     calibration,  the  blank, and  multiple  detection  decisions,\n                                                         Chemom. Intell. Lab. Syst. 37 (1977) 151\u00b1181.\n                                                                               [4] R.D. Gibbons, Some statistical and conceptual issues in the\n                                                                               detection  of  low-level environmental  pollutants, Environ.\n                                                                             Ecol. Statist. 2 (1995) 125\u00b1167; [Discussants: K. Cambell,\n                                                              W.A. Huber, C.E. White, H.D. Kahn, B.K. Sinha, W.P. Smith,\n                                                                   H. Lacayo, W.A. Telliard, C.B. Davis].\n                                                                               [5] W. Horwitz, IUPAC Commission on Analytical Nomencla-\n                                                                                         ture, Nomenclature for Sampling in Analytical Chemistry,\n                                                                      Pure Appl. Chem. 62 (1990) 1193.\n                                                                               [6] A. Hubaux, G. Vos, Decision and detection limits for linear\n                                                                                  calibration curves, Anal. Chem. 42 (1970) 849\u00b1855.\n                                                                               [7]  P. Wilrich, Chairman, ISO/DIS 11843-1,2 (1995), Capability\n                                                                           of  Detection, ISO/TC69/SC6, ISO  Standard,  11843-1,\n                                                                        1977.\n                                                                               [8] IUPAC, Orange book, in: H. Freiser, G.H. Nancollas (Eds.),\n                                                           Compendium of Analytical Nomenclature, 2nd ed., Black-\nFig. 2. Detection: needs and capabilities. Top portion shows the             well, Oxford; 1st ed., 1978.\nrequisite limit LR, bottom shows detection capability LD.                   [9] IUPAC, prepared by L.A. Currie, IUPAC Commission on\n                                                                             Analytical Nomenclature, Recommendations in Evaluation\n                                                                             of Analytical Methods including Detection and Quantification\nin this case, variance increasing with signal level, and             Capabilities, Pure Appl. Chem. 67 (1995) 1699\u00b11723.\nunequal   and    . The point of the latter construct is       [10] H. Kaiser, Die Berechnung der Nachweisempfindlichkeit,\nthat, although 0.05 is the recommended default value            Spectrochim. Acta 3 (1947) 40.\nfor these parameters, particular circumstances may       [11] H. Kaiser, Zum Problem der Nachweisgrenze, Z. Anal. Chim.\n                                                                209 (1965) 1.\ndictate more stringent control of the one or the other.                                                                        [12] G.L. Long, J.D. Winfordner, Limit of detection: a closer\nInstructive implicit issues in this example are that (1) a            look at the IUPAC definition, Anal. Chem. 55(7) (1983)\nmajor factor governing the detection capability could           713A.\nbe the natural variation of the radon background       [13]  J. Mandel, R.C.  Paule,  Interlaboratory  evaluation  of  a\n(blank variance) in the environment sampled, and             material with unequal numbers of replicates, Anal. Chem.\n                                                                42 (1970) 1194.\n(2) a calibration factor or function is needed in order                                                                        [14] M. Natrella, Experimental Statistics, NBS Handbook 91, US\nto couple the two abscissae in the diagram. In prin-          Government Printing Office, Washington, 1963.\nciple, the response of a sensing instrument could be       [15] IUPAC, J. Incze\u00c2dy, T. Lengyel, A.M. Ure, A. Gelencse\u00c2r, A.\ncalibrated directly to the Richter scale (earthquake            Hulanicki (Eds.) Compendium of Analytical Nomenclature,\nmagnitude); alternatively, there could be a two-stage            3rd ed., Blackwell, Oxford, 1998.\ncalibration: instrument response\u00b1radon concentration,\n                                                               Note added in proof\nand radon concentration\u00b1Richter scale.\n                                                                          Shortly after the submission of this article to Analytica Chimica\n                                                                 Acta a new edition of the IUPAC Compendium of Analytical\n                                                             Nomenclature was  published  [15].  In  the new  edition  the\nReferences                                                                           deficiencies in the [old] ``IUPAC Definition'' of the Detection\n                                                                        Limit, as discussed in Section 2.1.1, were remedied by incorpora-\n [1] L.A. Currie, Limits for qualitative detection and quantitative        tion of the new IUPAC Recommendations of 1995 [9].\n     determination, Anal. Chem. 40 (1968) 586.\n\n## 3. currie1999detectionandquantification pages 6-7 (Context ID: pqac-00000020)\n\ns done successfully, and if all\nhowever, has a drawback in that it yields, ``detection     assumptions are satis\u00aeed, the apparent dichotomy\nlimits'' that are random variables, as acknowledged in     between the intralaboratory approach and the inter-\nthe original publication of the method ([6], p. 850);      laboratory approach to detection and quanti\u00aecation132                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n                                                          estimates for compound CMPs involving different\n                                                       samples, different instruments,  different operators,\n                                                          or even different methods. In the context of (material)\n                                                       sampling, an excellent exposition of the nature and\n                                                     importance of the hierarchical  structure has been\n                                                        presented by Horwitz [5].\n                                              From the interlaboratory perspective, the \u00aerst popu-\n                                                               lation in Fig. 1 (e1) would represent the distribution of\n                                                              errors among  laboratories;  the second  [S] would\n                                                         re\u00afect  intralaboratory  variation  (``repeatability'');\n                                                  and the third [T], overall variation (``reproducibility'').\n                                                                        If the sample of collaborating laboratories can be\n                                                       taken as unbiased, representative, and homogeneous,\n          Fig. 1. Sampled [S] and target [T] populations.             then the interlaboratory ``process'' can be treated as a\n                                             compound CMP. In this fortunate (at best, asymptotic)\nlimits essentially vanishes.3 Some perspective on this      situation, results from individual laboratories are con-\nissue is given in Section 4.1 of [9] (quoted below), in      sidered random, independent variates from the com-\nterms of sampled and target populations.              pound CMP population. For parameter estimation\n  Sampled population [S] vs. target population [T].     (means, variances) in the interlaboratory environment\nThe above concept has been captured by Natrella [14]         it may be appropriate to use weights \u00b1 for example,\nwith reference to two populations which represent,    when member laboratories employ different numbers\nrespectively, the population (of potential measure-      of replicates [13].\nments) actually sampled, and that which would be\nsampled in the ideal, bias-free case. The correspond-\ning S and T populations are shown schematically in      4. Central role of the blank ([9], Section 3.8.8)\nFig. 1, for a two-step measurement process. When\nonly the S population is randomly sampled (left-hand      4.1. Blank (B)\nside of the \u00aegure), the error e1 from the \u00aerst step is\nsystematic while e2  is random. In  this  case, the       The blank is one of the most crucial quantities in\nestimated uncertainty is likely to be wrong, because      trace analysis, especially in the region of the detection\n(a) the apparent imprecision (  S) is too small, and (b)       limit. In fact, as shown above, the distribution and\nan unmeasured bias (e1) has been introduced. Realiza-      standard deviation of the blank are intrinsic to calcu-\ntion of the T-population (right-hand side of the \u00aegure)      lating the detection limit of any CMP. Standard devia-\nrequires that all steps of the CMP be random \u00b1 i.e., e1      tions are dif\u00aecult to estimate with any precision (ca. 50\nand e2 in the \u00aegure behave as random, independent      observations required for 10% RSD for the standard\nerrors; T thus represents a compound probability      deviation). Distributions (cdfs) are harder! It follows\ndistribution. If the contributing errors combine line-      that extreme care must be given to the minimization\narly and are themselves normal, then the T-distribution     and estimation of realistic blanks for the overall CMP,\nalso is normal. The concept of the S and T populations     and that an adequate number of full scale blanks must\nis absolutely central to all hierarchical measurement     be assayed, to generate some con\u00aedence in the nature\nprocesses (compound CMPs), whether intralaboratory      of the blank distribution and some precision in the\nor interlaboratory. Strict attention to the concept is      estimate of the blank RSD.\nessential  if one  is to obtain consistent uncertainty        Note: An imprecise estimate for the blank standard\n                                                          deviation is taken into account without dif\u00aeculty in\n                                                          detection decisions, through the use of Student's-t.\n  3In  practical  application,  the complexity  of  defining and\n                                                       Detection limits, however, are themselves renderedestimating   goes considerably deeper. For a recent informative\nand provocative discussion of this and related regulatory-detection      imprecise if  B is not well known (see [9], Section\nissues, the reader may consult [4].                                  3.7.3.2).                                        L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134                              133\n\n  Blanks or null effects may be described by three      in the environmental and physical sciences, for exam-\ndifferent  terms, depending upon  their  origin:  the      ples, include: (1) multiple univariate and multivariate\ninstrumental background  is the null signal (which      detection decisions and limits as found, for example,\nfor certain instruments may be set to zero, on the      in the analysis of multicomponent nuclear spectra; (2)\naverage) obtained in the absence of any analyte- or      multivariate environmental blanks, especially in the\ninterference-derived signal; the (spectrum or chroma-     measurement and source apportionment of multiiso-\ntogram) baseline comprises the summation of the      topic chemical species, such as atmospheric carbon\ninstrumental background plus signals in the analyte     monoxide; and (3) the appropriate treatment of detec-\n(peak) region of interest due to interfering species; the      tion and quanti\u00aecation limits for archaeological or\nchemical (or analyte) blank is that which arises from      geophysical artifacts or events that are governed by\ncontamination from the reagents, sampling procedure,      discrete, non-linear, and non-monotonic calibration\nor sample preparation steps, which corresponds to the      curves, as in the case of radiocarbon (14C) dating.\nvery analyte being sought.                      An introduction and references to some of these\n  Assessment of the blank (and its variability) may be     problems in the physical and environmental sciences\napproached by an ``external'' or ``internal'' route, in    may be found in [3].\nclose analogy to the assessment of random and sys-\ntematic error components [2]. The ``external'' approach\nconsists of the generation and direct evaluation of a     Acknowledgements\nseries of ideal or surrogate blanks for the overall\nmeasurement process, using samples that are identical       The author gratefully acknowledges the work of Dr.\nor closely similar to those being taken for analysis \u00b1     David E. Coleman of Alcoa Laboratories, who served\nbut containing none of the analyte of interest. The      as Voluntary Peer Reviewer for the original version of\nCMP and matrix and interfering species should be       this paper.\nunchanged. (The surrogate is simply the best available\napproximation to the ideal blank \u00b1 i.e., one having a\nsimilar matrix and similar levels of interferants.) The     Appendix A\n``internal'' approach has been described as ``propaga-\ntion of the blank''. This means that each step of the     Detection of earthquake precursors4\nCMP is examined with respect to contamination and\ninterference contributions, and the whole is then esti-     A graphical representation of these concepts  is\nmated as the sum of its parts \u00b1 with due attention to     given in Fig. 2, where the ``driving force'' in this\ndifferential recoveries and variance propagation. This      hypothetical example is the ability to detect the release\nis an important point: that the blank introduced at one      of speci\u00aec chemical precursors of earthquakes (e.g.,\nstage of the CMP will be attenuated by subsequent      radon)  at  levels corresponding  to earthquakes  of\npartial recoveries. Neither the internal nor the external     magnitude LR and above. Thus LR is the ``requisite\napproach to blank assessment is ea\n\n## 4. currie1999detectionandquantification pages 2-4 (Context ID: pqac-00000021)\n\nquestion. The \u00aerst, ``signal/noise'' school,\nexplicitly recognizes only the false positive (   , Type-1        1The regrettable confusion between the two types of ``detection\nerror), which in effect makes the probability of the        limits'' arose in part from an oversight in Kaiser's first publication\nfalse negative (  , Type-2 error) equal to 50%. The      on the topic [10] which ignored the idea of the false negative. False\nsecond, ``hypothesis testing'' school employs inde-       negatives nevertheless occur, and when ignored (equivalent to\n                                                                     equating LC and LD) their de facto probability becomes 50%, at\npendent values for   and    , commonly each equal to                                                                                 least for symmetric distributions. Kaiser corrected his error by\n0.05 or perhaps 0.01. In the most extreme case, the       inventing the term ``limit of guarantee for purity'' [11], but this\nsame numerical value of the ``detection  limit''  is       term has scarcely ever appeared in the literature.                                        L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134                              129\n\nformal requests by Codex2 in 1990 to each of the      curve; it is noted that A is not necessarily independent\norganizations for guidance on the terms ``limit of      of x, nor even a simple function of x. Subscripts C, D,\ndetection'' and ``limit of determination'', because of     and Q are used to denote the critical value, detection\nthe urgency of endorsing methods of analysis based on       limit, and quanti\u00aecation limit, respectively.\ntheir capabilities to reliably measure essential and       The de\u00aening  relations,  with  default  parameter\ntoxic elements in foods \u00b1 a problem that Codex had      values in parentheses, are given as follows:\nbeen attempting to resolve since 1982.                     Detection decision (critical value) (LC,  \u00880.05):\n                                                                  Pr\u0085^L > LCjL \u0088 0\u0086       :                            (1)2.2. Summary of the 1995 international\n    recommendations                                     Detection limit (minimum detectable value) (LD,\n                                                       \u00880.05):\n  Detection and quanti\u00aecation capabilities are con-\n                                                                  Pr\u0085^L   LCjL \u0088 LD\u0086 \u0088   :                           (2)sidered by IUPAC as fundamental performance char-\nacteristics  of  the  chemical measurement  process        Quanti\u00aecation limit (minimum quanti\u00aeable value)\n(CMP). As such, they require a fully de\u00aened, and      (LQ, RSDQ\u00880.10):\ncontrolled measurement process, taking into account\n                                             LQ \u0088 kQ Q;  where kQ \u0088 1=RSDQ:              (3)\nsuch matters as types and levels of interference, and\neven the data reduction algorithm. Perhaps the most       Note that LD, LQ, and  Q denote CMP  ``true''\nimportant purposes of these performance character-     parameter values. In practice they may be derived\nistics are for planning \u00b1  i.e., for the selection or     from estimates (or assumptions), such that calculated\ndevelopment of CMPs to meet a speci\u00aec scienti\u00aec      values will be characterized by uncertainties. Also, for\nor regulatory need. In the new IUPAC and ISO docu-    LD and   to be meaningful, LC (  ) must be employed\nments,   detection   limits  (minimum   detectable      for detection decision making. The relation,   vs. LD,\namounts) are derived from the theory of hypothesis       is known as the ``operating characteristic'' (OC) of the\ntesting and the probabilities of false positives    , and      (detection) signi\u00aecance test performed at signi\u00aecance\nfalse negatives    [7,9]. Quanti\u00aecation limits [9] are      level   ; (1\u00ff  ) is the ``power'' of the test. Eq. (1) is\nde\u00aened in terms of a speci\u00aeed value for the relative     given as an inequality, because not all values of   are\nstandard deviation (RSD). Default values for  and        possible for discrete distributions, such as the Poisson.\nare 0.05, each; and the default RSD for quanti\u00aecation     Note that the values of    ,    , and kQ given above are\nis taken as 10%.                              IUPAC recommended default values, which serve as a\n  As CMP performance characteristics, both detec-    common basis for measurement process assessment.\ntion and quanti\u00aecation  limits are associated with     They may be adjusted appropriately  in  particular\nunderlying true values of the quantity of interest; they      applications where detection or quanti\u00aecation needs\nare not associated with any particular outcome or      are more or less stringent.\nresult. The detection decision, on the other hand, is       Also addressed in the IUPAC document is the issue\nresult-speci\u00aec; it is made by comparing the experi-      of reporting. The recommendation is to always report\nmental result with the critical value, which  is the     both the estimated value of the measured quantity (^L)\nminimum signi\u00aecant estimated value of the quantity     and its uncertainty, even when ^L < LC results in the\nof interest. For presentation of the de\u00aening relations, L      decision ``not detected''. Otherwise, there is needless\nis used as the generic symbol for the quantity of      information loss, and of course, the impossibility of\ninterest. This  is replaced by S when treating net     averaging a series of results. The practice of quoting\nanalyte signals; and x, when treating analyte concen-     upper limits for ``non-detects'' can be helpful, but this\ntrations or amounts. The symbol A is used by IUPAC        still impairs future uses of the data. Quoting LD as an a\nto represent the sensitivity, or slope of the calibration      posteriori upper limit is not recommended, as this is\n                                                               really an a priori performance characteristic. Although\n                                                                                     it can be viewed as the ``maximum'' upper limit in the  2Codex Alimentarius Commission, Committee on Methods of\nAnalysis and Sampling, Food and Agricultural Organization, World      case of the null hypothesis, LD does not re\u00afect the new\nHealth Organization.                                        information contained in the experimental result.130                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n2.2.1. Simplified relations                                    ples, an hypothetical example from IUPAC [9] is given\n  Under the very special circumstances where the      in Appendix A.\ndistribution of ^L can be taken as normal, with constant\nstandard deviation  0 (homoscedastic) and the default      2.2.2. Heteroscedasticity\nparameter values, the foregoing de\u00aening relations       The following paragraphs, taken largely from Sec-\nyield the following expressions:                            tion 3.7.8 of [9], address the impact of heteroscedas-\n                                                                     ticity on the relative magnitudes of LC, LD, and LQ.LC \u0088 z1\u00ff   0 ! 1:645  0;                        (4a)\n                                                                           If the variance of the estimated quantity  is not\nLC \u0088 t1\u00ff ;vs0 ! 2:132s0   \u00894 df\u008a;               (4b)      constant, then its variation must be taken into account\n                                                             in computing detection and quanti\u00aecation limits. TheLD \u0088 LC \u0087 z1\u00ff  D ! 2LC \u0088 3:29  0;            (5a)\n                                                                    critical level is unaffected, since it re\u00afects the variance\nLD \u0088      ;  ;v  0   2t1\u00ff  ;v  0 ! 4:26  0   \u00894 df\u008a;    (5b)      of the null signal only. Two types of   variation are\n                                         common in chemical and physical metrology: (a)  2\nLQ \u0088 kQ Q ! 10  0;                               (6)\n                                                           (variance) proportionate to response, as with shot\nwhere   0,  D, and  Q represent the standard deviation      noise and Poisson counting processes; and  (b)\nof the estimator ^L: under the null hypothesis, at the      (standard deviation) increasing in a linear fashion.\ndetection limit, and at the quanti\u00aecation limit, respec-      Detailed treatment of this issue is beyond the scope\ntively; s20 represents an estimate of   20, based on v      of this document, but further information may be\ndegrees of freedom; z and t represent the appropriate     found in [2]. To illustrate, given normality, negligible\none-sided critical values of the standard normal variate      uncertainty in the mean value of the blank (such that\nand Students-t, respectively; and  represents the non-    0!  B), and   \u0085^S\u0086 increasing with a constant slope\ncentrality parameter of the non-ce\n\n## 5. currie1999detectionandquantification pages 1-2 (Context ID: pqac-00000022)\n\n                                        Analytica Chimica Acta 391 (1999) 127\u00b1134\n\n\n\nDetection and quanti\u00aecation limits: origins and historical overview$\n\n                                 Lloyd A. Currie*\n\n                            National Institute of Standards and Technology, Gaithersburg, MD 20899, USA\n\n                                     Received 17 February 1998; accepted 18 February 1998\n\n\n\nAbstract\n\nDetection and quanti\u00aecation capabilities represent fundamental performance characteristics of measurement processes, yet\nthere have been decades of confusion and miscommunication regarding the underlying concepts and terminology. New,\ncoordinated documents prepared for the International Union of Pure and Applied Chemistry (IUPAC) [L.A. Currie, IUPAC\nCommission on Analytical Nomenclature, Recommendations in Evaluation of Analytical Methods including Detection and\nQuanti\u00aecation Capabilities, Pure Appl. Chem. 67 (1995) 1699\u00b11723] and the International Organization for Standardization\n(ISO) [P. Wilrich, Chairman, ISO/DIS 11843-1,2 (1995), Capability of Detection, ISO/TC69/SC6, ISO Standard, 11843-1,\n1977] promise  to  alleviate  this  situation by providing,  for the  \u00aerst time, a harmonized  position on standards and\nrecommendations for adoption by the international scienti\u00aec community. The text begins with (1) a brief historical summary\nof detection limits in chemistry, illustrating the critical need for the development of a sound and uniform system of terms and\nsymbols; and  (2) a review of the ISO\u00b1IUPAC deliberations and the ensuing harmonized position on concepts and\nnomenclature. In the following text a number of special topics are introduced, including: speci\u00aecation of the measurement\nprocess, attention to the meaning and evaluation of ``sigma'', special considerations for calibration (or regression)-based\ndetection and quanti\u00aecation limits, the central role of the blank, and \u00aenally, some challenges for the future. # 1999 Elsevier\nScience B.V. All rights reserved.\n\n\nKeywords: Detection; Quanti\u00aecation; International nomenclature; Metrology; IUPAC; ISO\n\n\n1. Introduction                                           nized. For some three decades, however, efforts to\n                                                     develop an internationally accepted system of nomen-\n  The importance of objective measures for detection      clature and scienti\u00aecally sound conceptual basis for\nand quanti\u00aecation capabilities of chemical and phy-     such capabilities have been impeded by the evolution\nsical measurement processes has long been recog-      of a wide range of terms, concepts, and ad hoc rules\n                                                                that are contradictory, and in some cases not even\n                                                              internally self-consistent. The need for a harmonized\n   *Tel.: +1-301-975-3919; fax: +1-301-216-1134; e-mail:            international position was recognized in 1993, when\ncurrie@nist.gov                                    members of IUPAC and ISO met, with the objective of\n  $Adapted from the Proceedings of the 1996 Joint Statistical                                                      developing such a position, based on documents then\nMeetings (American Statistical Association, 1997). Original title:\n                                                             in draft stage. These efforts culminated in 1995, with``Foundations and future of detection and quantification limits''.\nContribution of the National Institute of Standards and Technology;      the publication of IUPAC recommendations for the\nnot subject to copyright.                                         international chemical community [9], and the pre-\n\n\n0003-2670/99/$ \u00b1 see front matter # 1999 Elsevier Science B.V. All rights reserved.\nPII: S 0 0 0 3 - 2 6 7 0 ( 9 9 ) 0 0 1 0 5 - 1128                                    L.A. Currie / Analytica Chimica Acta 391 (1999) 127\u00b1134\n\nparation of an ISO document for metrology in general     employed, e.g., 3.3  0, where  0 is the standard devia-\n[7]. While not identical, the documents are based on      tion of the estimated net signal (S\u00c3) when its true value\nthe same fundamental concepts, and compatible for-      (S) is zero. The ratio   /   for the \u00aerst (signal/noise)\nmulations and terminology. In the following text, we      group, assuming normality,  is thus 0.50/0.0005 or\npresent these concepts, together with their application     1000, far in excess of the unit ratio of the second\nto chemical metrology as developed in the IUPAC      group!1\ndocument. A brief review of the relevant history of the        Unfortunately, many are unaware of the above\ntopic, and discussions of critical approaches and open      subtle differences in concepts and terminology, or\nquestions in the application of the basic concepts      of the care and attention to assumptions required\nwhich follow are drawn, in part, from Currie [2,3].      for calculating meaningful detection limits; but these\nThe literature cited in the foregoing references pro-     become manifest when dif\u00aecult, low-level laboratory\nvides detailed information on the statistical and che-      intercomparisons are made. By way of illustration, in\nmical aspects of the topic.                                the International Atomic Energy Agency's interla-\n                                                        boratory comparison of arsenic in horse kidney (mg/\n                                                g level), several laboratories failed to detect the As, yet\n2. Communication and concepts                           their reported ``detection limits'' lay far below quan-\n                                                                     titative results reported by others; and the range of\n2.1. A very brief history                                 reported values spanned nearly \u00aeve orders of magni-\n                                                        tude ([2], Chapter 9).\n  Early papers on chemical detection limits were\npublished by Kaiser [10] and Currie [1]. In the latter,      2.1.1. Stimuli for the recent IUPAC and ISO efforts\nwhich  treated  the hypothesis  testing approach  to        Early guidance on detection limits, strongly in\u00afu-\ndetection decisions and limits in chemistry,  it was     enced by the work of Kaiser, was given by IUPAC.\nshown that the then current meanings attached to the      Resulting ``of\u00aecial'' recommendations appear in the\nexpression ``detection limit'' led to numerical values      early  editions  of  the Compendium  of  Analytical\nthat spanned three orders of magnitude, when applied     Nomenclature, where the ``limit of detection  . . . is\nto the same speci\u00aec measurement process. Differing      derived from the smallest measure that can be detected\nconcepts are but one side of the problem. A review of     with reasonable certainty for a given analytical pro-\nthe history of detection and quanti\u00aecation limits in      cedure''. This quantity is then related to a multiple k of\nchemistry published in 1988 [2] gives a partial com-      the standard deviation of the blank ``according to the\npilation of terms, all referring to the same, detection     con\u00aedence level desired'', with the general recom-\nlimit concept \u00b1 ranging from ``identi\u00aecation limit'' to     mendation of k\u00883. Hypothesis testing was not men-\n``limiting detectable concentration'' to ``limit of guar-      tioned, nor was the issue of false negatives, nor the\nantee for  purity'', for example. Perhaps the most      quanti\u00aecation limit [8,9]. De\u00aeciencies in the ``IUPAC\nserious terminological trap has been the use of the      de\u00aenition'' have been recognized by many  [12],\nexpression ``detection limit'' (a) by some to indicate     and are responsible, in  part, for the new IUPAC\nthe critical value (LC) of the estimated amount or       effort [9].\nconcentration above which the decision ``detected''     A second important factor in the new IUPAC effort\nis made; but (b) by others, to indicate the inherent      to develop a proper treatment of both detection and\n``true'' detection capability (LD) of the measurement      quanti\u00aecation limits, and a parallel effort by ISO, were\nprocess in question. The \u00aerst, ``signal/noise'' school,\nexplicitly recognizes only the false positive (   , Type-1        1The regrettable confusion between the two types of ``detection\nerror), which in effect makes the probability of the        limits'' arose in part from an oversight in Kaiser's first publication\nfalse negative (  , Type-2 error) equal to 50%. The      on the topic [10] which ignored the idea of the false negative. False\nsecond, ``hypothesis testing'' school employs inde-       negatives nevertheless occur, and when ignored (equivalent to\n                                                                     equating LC and LD) their de facto probability becomes 50%, at\npendent values for   and    , commonly each equal to             \n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022]\n\nStatus: Paper Count=21 | Relevant Papers=5 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=23 | Current Cost=$0.1511 | Disease-Target Evidence=0",
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+                "content": "Retrieved Papers:\n## 1. Expanding the detection efficiency of silicon drift detectors\nValid Text Names:\n'schlosser2010expandingthedetection pages 1-2', 'schlosser2010expandingthedetection pages 2-4', 'schlosser2010expandingthedetection pages 4-6', 'schlosser2010expandingthedetection pages 6-7', 'schlosser2010expandingthedetection pages 7-7'\n\nBibTex:\n@article{schlosser2010expandingthedetection,\n    author = \"Schlosser, D.M. and Lechner, P. and Lutz, G. and Niculae, A. and Soltau, H. and Str\u00fcder, L. and Eckhardt, R. and Hermenau, K. and Schaller, G. and Schopper, F. and Jaritschin, O. and Liebel, A. and Simsek, A. and Fiorini, C. and Longoni, A.\",\n    title = \"Expanding the detection efficiency of silicon drift detectors\",\n    year = \"2010\",\n    journal = \"Nuclear Instruments \\& Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment\",\n    volume = \"624\",\n    pages = \"270-276\",\n    month = \"Dec\",\n    doi = \"10.1016/j.nima.2010.04.038\",\n    url = \"https://doi.org/10.1016/j.nima.2010.04.038\",\n    publisher = \"Elsevier BV\",\n    issue = \"2\",\n    issn = \"0168-9002\"\n}\n\n\nRelevant Snippet:\n\u2026 Results of the energy resolution for the 137 Cs 662 keV line \u2026 The serial white and 1/f noise strongly depend on the total \u2026 In contrast the optimal shaping time of a SDD with minimal noise \u2026\n\n\n---\n\n## 2. Novel high-resolution silicon drift detectors\nValid Text Names:\n'lechner2004novelhighresolutionsilicon pages 1-2', 'lechner2004novelhighresolutionsilicon pages 2-4', 'lechner2004novelhighresolutionsilicon pages 4-5', 'lechner2004novelhighresolutionsilicon pages 5-6', 'lechner2004novelhighresolutionsilicon pages 6-6'\n\nBibTex:\n@article{lechner2004novelhighresolutionsilicon,\n    author = \"Lechner, P. and Pahlke, A. and Soltau, H.\",\n    title = \"Novel high-resolution silicon drift detectors\",\n    year = \"2004\",\n    journal = \"X-Ray Spectrometry\",\n    volume = \"33\",\n    pages = \"256-261\",\n    month = \"Jul\",\n    doi = \"10.1002/xrs.717\",\n    url = \"https://doi.org/10.1002/xrs.717\",\n    publisher = \"Wiley\",\n    issue = \"4\",\n    issn = \"0049-8246\"\n}\n\n\nRelevant Snippet:\n\u2026 electronics and detector gives an optimal signal-to-noise ratio\u2026 The noise contributions of an SDD are serial noise, 1/f noise \u2026 Silicon drift detectors benefit from their low shaping times of \u2026\n\n\nUnobtainable Papers:\nCarlo Fiorini, Luca Bombelli, Paolo Busca, Alessandro Marone, Roberta Peloso, Riccardo Quaglia, Pierluigi Bellutti, Maurizio. Boscardin, Francesco Ficorella, Gabriele Giacomini, Antonino Picciotto, Claudio Piemonte, Nicola Zorzi, Nick Nelms, and Brian Shortt. Silicon drift detectors for readout of scintillators in gamma-ray spectroscopy. IEEE Transactions on Nuclear Science, 60:2923-2933, Aug 2013. URL: https://doi.org/10.1109/tns.2013.2273418, doi:10.1109/tns.2013.2273418.\nArslan Dawood Butt, Riccardo Quaglia, Carlo Fiorini, Paolo Busca, Michele Occhipinti, Gabriele Giacomini, Claudio Piemonte, Franco Camera, Nick Nelms, and Brian Shortt. Development of a detector for gamma-ray spectroscopy based on silicon drift detector arrays and 2$^\\prime ^\\prime $ lanthanum bromide scintillator. IEEE Transactions on Nuclear Science, 62:2334-2342, Sep 2015. URL: https://doi.org/10.1109/tns.2015.2464676, doi:10.1109/tns.2015.2464676.\nB. Beckhoff, B. Kanngie\u00dfer, N. Langhoff, R. Wedell, and H. Wolff. Handbook of practical x-ray fluorescence analysis. ArXiv, Jan 2006. URL: https://doi.org/10.1007/978-3-540-36722-2, doi:10.1007/978-3-540-36722-2.\nCarlo Fiorini. Gamma detectors for spectroscopy and imaging based on scintillators coupled to semiconductor detectors. SPIE Proceedings, Nov 2000. URL: https://doi.org/10.1117/12.407570, doi:10.1117/12.407570.\nGriseld Deda, Idham Hafizh, Giacomo Borghi, Marco Carminati, Francesco Ficorella, Giancarlo Pepponi, and Carlo Fiorini. Scarlet: a readout asic bump-bonded to sdd array for large event throughput. IEEE Transactions on Nuclear Science, 71:2323-2333, Oct 2024. URL: https://doi.org/10.1109/tns.2024.3455424, doi:10.1109/tns.2024.3455424.\nK. Hansen and C. Reckleben. Noise analysis of an si-drift detector system with time-variant shaping. IEEE Transactions on Nuclear Science, 51:3845-3852, Dec 2004. URL: https://doi.org/10.1109/tns.2004.839369, doi:10.1109/tns.2004.839369.\nAndrei Stratilatov. Semiconductor detectors for portable energy\u2010dispersive xrf spectrometry. ArXiv, pages 475-500, May 2021. URL: https://doi.org/10.1002/9781119636489.ch19, doi:10.1002/9781119636489.ch19.\nC. Fiorini, A. Gola, A. Longoni, F. Perotti, and L. Struder. Timing properties of silicon drift detectors for scintillation detection. 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515), 2:701-703Vol.2, Jan 2004. URL: https://doi.org/10.1109/tns.2004.829581, doi:10.1109/tns.2004.829581.\nS. G. Basiladze. Application specific integrated circuits for ionizing-radiation detectors (review, part 1). Instruments and Experimental Techniques, 59:1-52, Jan 2016. URL: https://doi.org/10.1134/s0020441216010280, doi:10.1134/s0020441216010280.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022]\n\nStatus: Paper Count=23 | Relevant Papers=5 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=23 | Current Cost=$0.1511 | Disease-Target Evidence=0",
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+                "content": "Now let me read the SDD noise papers and gather more evidence:",
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+                "content": "## 1. niculae2006optimizedreadoutmethods pages 2-3 (Context ID: pqac-00000023)\n\n                                                                         (1)  The most frequently used method to operate the SDD     vs\u00f0s\u00de \u00bc\n                                                    Cd 1 \u00fe gds \u00f01 \u00fe Cgs 1 \u00fe s  tf 1 1 \u00fe s  trwith on-chip FET is the source\u2013follower readout [5] with                       gm      Cd\u00de\nthe detector operated in the self-reset mode. As shown in\n                                                     where  Qin  is  the  input  charge, gm and  gds  are  theFig. 2, the integrated JFET is biased in a source\u2013follower\n                                                          transconductance and the channel conductance of the\ncon\ufb01guration and is followed by a voltage ampli\ufb01er. Cd is\n                                                               integrated transistor, respectively; z0  is a high-frequency\nthe total capacitance seen by the detector anode and is a\n                                                            zero  given by  z0 \u00bc gm=Cgs and  plays no  role  at  thesum of the gate-drain capacitance Cgd and the depletion\n                                                              frequencies of interest.\ncapacitances between  the anode and  the  neighboring\n                                                           Considering the input charge as a time-domain step\nregions\u2014Cbulk, Ca  ig, Ca  r1 in Fig. 3. Cgs  is the gate-\n                                                               function,  tr  is the  rise time (the time constant of the\nsource capacitance of the integrated FET and CL  is the\n                                                            exponential increase) of the source signal, whereas tf 1 is the\ntotal load capacitance at the source node.\n                                                        decay time constant of the source signal. They are given by\n  The self-reset mechanism\u2014represented in the circuit by\nthe resistance Rd\u2014works basically in the following way: as                                               CL \u00fe Cin \u00fe Cd\u00feCgsCdCgs     CL \u00fe Cin\nthe  electrons  (signal  or/and  thermally  generated)  are     tr \u00bc              Cd                  Cd                   (2)\ncollected to the detector anode, this becomes more and            gds \u00fe gm Cd\u00feCgs     gds \u00fe gm Cd\u00feCgs\nmore  negative.  Consequently  the  transistor  gate  gets\nincreasingly reverse biased with respect to the channel.                                gds\nAt a given potential difference, a weak avalanche break-     tf 1 \u00bc Rd  Cd \u00fe Cgs                  .                          (3)\n                                                                      gm \u00fe gds\ndown region is formed in the transistor channel between\ngate and drain; the holes generated in  this region are    Analyzing the expression of tr from Eq. (2), one can see\ncollected at the gate and compensate for the signal/leakage    that the ampli\ufb01er  rise time  is determined by the total\nelectrons. A very detailed characterization of the dischar-    capacitance seen by the source node and the transistor\nging mechanism can be found in Ref. [6].                   parameters gm and  gds. Since the optimization of the\n  Performing the small-signal analysis of the circuit in    integrated transistor with respect to  this parameters  is\nFig.  2,  the  expression  of  the  source  voltage  vs\u00f0s\u00de  in    limited by the technology, the minimization of the signal                            ARTICLE IN PRESS\n\n338                     A. Niculae et al. / Nuclear Instruments and Methods in Physics Research A 568 (2006) 336\u2013342\n\nrise time is also limited. Typical values of tr are in the range    assumptions like ideal operational ampli\ufb01er A0 with A0 !\nof 80\u2013100 ns for 10 pF total load capacitance.       1 and in\ufb01nite bandwidth and is given by:\n  The output voltage of the whole ampli\ufb01er chain  is\n                                                                        Qin     s  t1     s  t2\ngiven by                                                                vout\u00f0s\u00de                                                       (5)\n                                                         Ca  ig  1 \u00fe s  t1 1 \u00fe s  t2\n                Cin    s  tf 2\nvout\u00f0s\u00de \u00bc   vs\u00f0s\u00de                                             (4)    where\n                Cfb  1 \u00fe s  tf 2\n                                                                     t1 \u00bc Rd Ca  ig;   t2 \u00bc Rfb  Cin.                           (6)\nwhere  tf 2 \u00bc Cfb  Rfb  is the decay time constant of the\nvoltage ampli\ufb01er.                                   The time constants t1 and t2 are determined with the\n                                                       approximation  that  t1bt2  which   is  valid  since  the\n2.2. Charge sensitive ampli\ufb01er readout and self-reset                                                       dynamical resistance Rd  is very large (e.g. hundreds of\noperation                                                  GO). One can observe that the frequency bandwidth of the\n                                                         ampli\ufb01er is no more limited by the integrated transistor\n  The rise time limitations of the source\u2013follower readout                                                         parameters gm and gds. The rise time of the output signal\ncon\ufb01guration can be overcome by choosing an alternative                                                                                  is then determined by the rise time of the incoming charge\nreadout scheme of the SDD, which is the charge-sensitive-                                                                     signal.\nampli\ufb01er (CSA) readout. This readout concept  is com-\nmonly used for PIN diode detector types (with external\n                                                                      3. Pulsed reset operation mode\nfront-end transistors) and has also been implemented for\nsome special types of SDD detectors having an integrated\n                                                As  described  in  the  previous  section,  the  self-reset\nfeedback capacitor [7,8].\n                                                           operation  is a very comfortable way of operating the\n  The  standard SDDs  detectors  have no  integrated\n                                               SDDs. However, the reset current provided by the self-reset\ncapacitors; nevertheless one can use the parasitic capacitor\n                                                   mechanism to discharge the anode acts in the same way as\nbetween the detector anode and the transistor guard ring\n                                                             the  detector  leakage  current  as  far  as  the  noise  is\n(Ca  ig  in  Fig.  3)  as  feedback  capacitor. The  circuit\n                                                           concerned. Since the reset current is proportional to the\nschematic is shown in Fig. 4. The integrated transistor is\n                                                            input photon  rate,  it  is unavoidable  that  the energy\nstill biased in the source follower con\ufb01guration, but  is\n                                                               resolution degrades with the increasing photon rate. For\nfollowed by a low input impedance, high gain ampli\ufb01er\n                                                              application requiring constant energy resolution over a\nresulting  into a high gain  inverting  voltage ampli\ufb01er.\n                                                                 large range of input count rates, the pulsed reset operation\nThe collected charge will be integrated over the feedback\n                                              mode can be employed.\ncapacitor Ca  ig. Rb is a very large resistance needed to bias\nthe transistor guard ring with a negative voltage, Cc is a\nlarge  coupling  capacitor needed  to decouple  the DC\n                                                                                                                 collecting anode\nvoltages of the guard ring and the ampli\ufb01er output. Their\nin\ufb02uence  in  the  ampli\ufb01er  transfer  function  can  be         integrated FET\nneglected.\n  The frequency transfer function of the CSA readout\ncon\ufb01guration can be determined by  considering some\n\n                                                                                                                                             reset\n\n\n                                                                          S\n                               fd\n SDD\n           Rd                                                     G\n                                                   Rfb                                                                 D\n\n                      Ca-ig      fs                                out\n                                          Ao\n   ~                                   Cin\n  iin           Cd\n\n                          ig\n                                          Cc\n                               Rb\n\n      \n\n## 2. niculae2006optimizedreadoutmethods pages 3-6 (Context ID: pqac-00000024)\n\n\n\n                                                                                                                                             reset\n\n\n                                                                          S\n                               fd\n SDD\n           Rd                                                     G\n                                                   Rfb                                                                 D\n\n                      Ca-ig      fs                                out\n                                          Ao\n   ~                                   Cin\n  iin           Cd\n\n                          ig\n                                          Cc\n                               Rb\n\n                                         Vig\n\nFig. 4. Charge-Sensitive-Ampli\ufb01er readout con\ufb01guration with parasitic     Fig.  5. Schematic top view of the inner part of the SDD with the\nfeedback capacitance of the SDD with integrated FET.                       integrated transistor and the reset diode.                            ARTICLE IN PRESS\n\n                        A. Niculae et al. / Nuclear Instruments and Methods in Physics Research A 568 (2006) 336\u2013342                     339\n\n  To operate the detector in the pulsed reset mode, a reset\nstructure integrated directly onto the detector anode (see\nFig. 5) can be used; by applying short positive pulses to this\ndiode, the signal charge collected at the anode is removed.\n  For  the  pulsed  reset  operation  of  the SDD  with\nintegrated FET, the CSA readout con\ufb01guration shown in\nFig. 4 has been employed.                                                                                                                                                                                                                                         events\n                                                                              of\n\n4. Measurements and results                                                                                                                                                                                                                                         Nunber\n\n  The spectroscopic measurements performed with SDDs\noperated in the readout con\ufb01gurations described in the\nprevious section will be now presented.\n\n\n4.1. Source\u2013follower vs. CSA readout\n\n  To compare the performance of both SF and the CSA                                      Energy [eV]\nreadout con\ufb01gurations, spectroscopic measurements with a                                                                               Fig. 7. Energy spectra of 55Fe source measured in both SF and CSA\nconventional 5 mm2 SDD operated in the self-reset mode     con\ufb01gurations at  20 C and 1 ms shaping time.\nhave been  carried  out.  Fig. 6 shows  the  oscilloscope\nwaveform of the CSA output signal due to a 5.9 keV\nphoton from a 55Fe radioactive source. The  rise time\nmeasured from 10% to 90% of the amplitude (i.e. 2:2   tr)\nis about 50 ns and is much smaller than in the SF readout\n(e.g. 200\u2013300 nS). From the amplitude of the  5.9 keV\nsignals, a value of about 30 fF has been estimated for the           [eV]\nparasitic feedback capacitance Ca  ig.                                                        line\n  The  energy  spectra  of  the  55Fe  radioactive  source\nmeasured in both con\ufb01gurations with the detector cooled             Mn-K\u03b1\nat  20 C and at a shaping time of 1 ms are plotted Fig. 7.      of\nThe     value           of the                 input                    photon rate was                                    about                                          1 kcps.                                          As            FWHMexpected,           the               noise                    performances                                    are                                           similar                                                     in both\ncon\ufb01gurations and this is due to the fact that the noise is\ndetermined entirely by detector capacitance, by the leakage\n\n\n\n\n                                                                                                       Input count rate [kcps]\n\n                                                                               Fig. 8. Energy resolution of Mn-Ka line as a function of the input count\n                                                                                  rate measured with both SF and CSA con\ufb01gurations.\n\n\n\n\n                                                             current and by the  properties of the input  transistor\n                                                               integrated on the detector [9].\n                                                   The  energy  resolution  measured  at  different  input\n                                                    photon rates is plotted in Fig. 8. The operation tempera-\n                                                               ture was again  20 C and the shaping time was reduced to\n                                                      250 ns in order to minimize pile-up events at high count\n                                                                      rates. One can  see  in both  cases  the same  expected\n                                                          degradation of the energy resolution with the increasing\n                                                            input count rate due to the increase of the reset current in\n                                                             the self-reset mechanism, as previously explained.\n                                                       Another consequence of the self-reset mechanism, which\n                                                        has not been discussed so far, is the change of the peak\n           Fig. 6. CSA output signal from a 5.9 keV photon.             position with the changing input count rate, which can be                            ARTICLE IN PRESS\n\n340                     A. Niculae et al. / Nuclear Instruments and Methods in Physics Research A 568 (2006) 336\u2013342\n\n\n\n\n [eV]\n line\n Mn-K\u03b1\n of\n   position\n Peak\n\n\n\n\n\n                               Input count rate [V]\n\nFig. 9. Peak position of Mn-Ka line as a function of the input count rate\nmeasured with both SF and CSA con\ufb01gurations.                              Fig. 10. Oscilloscope picture of the ampli\ufb01er output signal with the SDD\n                                                                        operated in pulsed reset mode.\n\n\nobserved in the plot of Fig. 9. The change is caused by the\ndischarging mechanism which  is self-adapting, therefore\nthe  reset  current  sets  itself  to  the  values needed  to\ncompensate the various rates of signal electrons arriving\nto the anode. This leads to a change of the anode potential\nwhich translates into a change of the depletion capaci-\ntances connected to the anode and contributing to the\nsignal amplitude.                                                                                                                   [mV]\n Now looking at the expression of the source voltage in           \u2206VoutEq. (1), this is inverse proportional to the total capacitance\nCd \u00bc Cg d \u00fe Ca  ig \u00fe Ca  r1 \u00fe Cbulk. The initial increase of\nthe peak position can be explained by the reduction of the\ncapacitance Cg d with more negative gate voltage. At the\nsame time, the other capacitances which contributes to Cd\nincrease with the decreasing anode voltage due to the\nincreasing  input  count  rate.  Their  variation becomes\ndominant for the last part of the plot.                                    (a)                       Reset ON voltage [V]\n  In the case of the CSA readout, only one capacitance\n(Ca  ig) determines the signal amplitude (see Eq. (5)). With\nmore negative anode voltage due to the increase of the\ncount rate, Ca  ig increases and the peak position decrease.\n  In both cases the peak position change with the input\nrate (or with the temperature) can be greatly reduced by\nusing a peak  shift compensation  circuit. Using such a             [mV]\ncircuit, a minimum peak shift of  0:03% (i.e.  2 eV for\n5.9 keV photons) up to input count rates as high as 400           \u2206Vout\nkcps has been reported in Ref. [10].\n\n4.2. Measurements of the SDDs in pulsed reset mode\n\n  As already mentioned, the CSA readout circuit described\nin Fig. 4 has been used for the measurements with SDDs\noperated  in  the  pulsed  reset  mode.  The  dynamical\nresistance Rd of the self-reset mechanism must be however      (b)                     Reset pulse width [ns]\nreplaced by the  reset diode connected to the detector     Fig. 11. Output voltage difference before and after reset as a function of:\nanode.                                                                              (a) reset high voltage and (b) reset pulse width.                            ARTICLE IN PRESS\n\n                        A. Niculae et al.\n\n## 3. schlosser2010expandingthedetection pages 2-4 (Context ID: pqac-00000025)\n\ne FWHM especially at lower X-ray\nenergies. In the low energy regime the bene\ufb01t of a low electronic\nnoise value on the energy resolution is the greatest.\n   Possibilities to improve the energy resolution are the reduction\nof  the  total  detector  capacitance and  the  leakage  current.\nA reduction of  Ctot from 150 to 80 fF  is achieved by moving\nthe anode and the integrated JFET from the center (standard SDD)\nto the border of the SDD (droplet SDD\u00bcSD3) [10,11]. The JFET\nlocated at the SDD border has a second positive effect. Irradiation\nof the integrated JFET can be avoided by mounting an appropriate\ncollimator. Undesired background events can be reduced. This\ncircumstance leads to a higher P/B ratio [10]. Furthermore the\nleakage current could be decreased, through a new fabrication\ntechnology, poly-silicon, to a stable level down to 200 pA/cm2 at\nroom temperature, reducing the energy resolution further.\n   The dependence of the energy resolution of a 10 mm2 SD3 on      Fig. 3. Superposition of spectra of Boron, Carbon and Oxygen measured with a\nthe count rate is illustrated in Fig. 2. Energy resolution values     10 mm2 SD3, with pn-Window at T\u00bc  20 1C. The FWHM of the B2Ka, C2Ka and\ndown to a full width at half maximum (FWHM) of 123 eV at    O2Ka lines are down to 38, 42 and 48 eV.\nthe Mn2Ka  line have been currently measured at moderate\ntemperatures of T\u00bc  20 1C. The charge sensitive ampli\ufb01er (CSA)\n\n                                                               readout con\ufb01guration  in combination with the pulsed  reset\n                                                                  operation mode ensures a nearly constant energy resolution up\n                                                                     to a few hundred kcps [9].\n\n\n\n                                                                             3. Optimizing the detector for light element performance\n\n\n                                                                  Apart from the detector noise, the detector entrance window is\n                                                               important  at low X-ray  energies. A modi\ufb01ed new  detector\n                                                                entrance window, pn-Window, has been developed for optimum\n                                                                            light element detection. The pn-Window reduces the loss of\n                                                                generated electrons in the SDD p+ layer of the entrance window\n                                                                           after an interaction of a X-ray photon in this region, so that a\n                                                             lower number  of events with  partial charge  collection  are\n                                                                     detected. This leads to an improved energy resolution measured\n                                                                         at lower X-ray  energies. The  spectra  of boron and carbon\n                                                         measured with a 10 mm2 SD3 detector are plotted in Fig. 3.\nFig. 1. Energy resolution against X-ray energy for different contributions of the    Energy resolution values of 38 eV for Boron line (138 eV) or 42 for\nelectronic noise.                                                Carbon line (277 eV) have been determined.272                              D.M. Schlosser et al. / Nuclear Instruments and Methods in Physics Research A 624 (2010) 270\u2013276\n\n\n\n\n\n                                                                                                Fig. 6. FWHM at Mn  Ka of a circular 30 mm2 SDD vs. shaping time at  20 and\nFig. 4. Spectra of two 10 mm2 SD3 with a standard entrance window (EW) (gray)      30 1C. At optimal shaping times of 2 or 3ms FWHM of 129 eV have been\nand a optimized EW (black), while irradiating with a 55Fe source. The optimization     measured.\nof the P/B and P/V ratios by the pn-Window is obvious.\n\n\n\n\n\n                                                                                                Fig. 7. FWHM at Mn2Ka of a square 100 mm2 SDD vs. shaping time at   20,   25,\n                                                                        30 and   351C.\n\nFig. 5. Spectrum of a 20 mm2 SD3 with optimized pn-Window, while irradiating\nwith a 55Fe source. The FWHM of the Mn2Ka line is 125 eV and a P/B ratio of up to\n16 000 has been measured.\n\n\n\n   The P/B and P/V (peak to valley) ratio of the SDDs with\npn-Window is improved by the same physical mechanism also for\nhigher X-ray energies e.g. Mn\u2013Ka. This effect is shown in Fig. 4.\n\n\n4. Optimization of area and geometry to increase the\ndetection ef\ufb01ciency for the \ufb02uorescent X-rays\n                                                                                                   Fig. 8. Detector consisting of 6  100 mm2 cells with an on chip collimator.\n   The optimization of the geometry of the detection area is\nimportant  for  applications  requiring  maximum  collection   FWHM  at Mn2Ka  of  a  100 mm2  circular SDD  for  four\nef\ufb01ciency of the incoming photons. This can be achieved by    temperatures is plotted against the shaping time.\nmaximizing  the  detection  area,  by  matching  the  detector        Increasing the detector area furthermore to several cm2 by\ngeometry to the geometry of the system, as well as by maximizing    maintaining the energy resolution and avoiding dead area  is\nthe detection solid angle for the incident radiation.                  possible with monolitical SDD arrays. Detectors with large areas\n    Fig. 5 shows the spectrum of 55Fe measured with a droplet    have been produced in that way [11]. The one presented here has\nshaped, SD3, detector, of which the detection area has been    an area  of 6  100 mm2, consisting  of  six  cells. The energy\nincreased to 20 mm2. The energy resolution at Mn2Ka line is     resolution of this detector is down to 140 eV at the Mn2Ka line\n125 eV at T\u00bc  20 1C with a P/B ratio of 16 000. Prototypes of    and moderate temperatures of   201 for each channel. Operation\n30 mm2 SD3 have also been developed. They are  still under      is possible for input count rates of up to 3 Mcps. By means of an\ninvestigation.                                                 adapted radiation entrance window, these detectors can also be\n    Fig. 6 shows the FWHM at Mn2Ka of a 30 mm2 circular SDD    used in combination with scintillators for gamma ray detection\nagainst shaping time at two different temperatures. In Fig. 7 the     (Figs. 8 and 9).                                 D.M. Schlosser et al. / Nuclear Instruments and Methods in Physics Research A 624 (2010) 270\u2013276                          273\n\n\n\n\n\n                                                            Fig. 9. 55Fe spectra of each channel of the six element SDD.\n\n\n\n\n\n                                                                                                Fig. 12. SDD without a housing, electrically coupled by a \ufb02ex lead, as a detector to\n                                                                          be integrated arbitrarily into analysis instruments  e.g. electron microscopes,\n                                                                      where the space for the detector is limited.\n\n\n                                                                                cooling plate\n\n                                                                                                              peltier element\n\nFig. 10. Rococo 2 consists of four SDDs, with an area of 15 mm2 each, a central\nhole and a on chip collimator.\n\n\n\n\n                                                                       ceramic\n                                                           SDD chip\n\n\n                                                                                                Fig. 13. Example of a construction for the \ufb02exlead SDD shown in Fig. 12, which is\n                                                                                 cooled in this case by a cooling plate and a peltier element.\n\n\n                                                                     Speci\ufb01c devices with a central hole for close arrangement of the\n                                                                     detector to the sample to ensure high collection ef\ufb01ciency of X-ray\n                                                               \ufb02uorescence photons have been developed and tested (Fig. 10)\n                                                                              [12]. In such a geometry the detector covers a bigger solid angle\n                                                           from the excitation point of the \ufb02uorescent X-rays on the sample,\n                                                                so that the detected fraction of \ufb02uorescent X-rays is increased\n           \n\n## 4. lechner2004novelhighresolutionsilicon pages 2-4 (Context ID: pqac-00000026)\n\nard the drift rings. This\noperating conditions. The arrows indicate the paths of                                              new layout allows the design of a readout anode which has\nelectrons drifting to the anode.                                                          a smaller area. As the capacitance of the readout node is\n                                                        mainly given by the area of the anode, reducing the area\n                                                             helps greatly.\nthe low collecting anode capacitance being independent of       The capacitance of the readout node in\ufb02uences the\nthe detector area. This results in low series and 1/f noise      electronic noise of the detector. The noise contributions of an\ncontributions [see Eqn (1)]. The anode capacitance is about    SDD are serial noise, 1/f noise and parallel noise:\n200 fF for standard SDDs.\n                                                                           2kBT C2  A continuous discharge of the anode capacitance  is          ENC2 D A1                                                     C A22 afC2 C  A3qIl        \u25b71\u25c1\ndirectly implemented within the integrated FET, so a pulsed                     gm\n                                                                                                                                                                 serial 1/f noise    parallel noise\nreset mechanism is avoided. The high electric \ufb01eld in the gate-                                     serial white noise\ndrain channel region is responsible for a weak avalanche\n                                                    where\nprocess, which injects holes into the gate. This process\ndischarges the collected signal and thermally generated       ENC D numberofelectrons:equivalentnoise charge (C);\nelectrons.11\n\n\n\nCopyright \uf6d92004 John Wiley & Sons, Ltd.                                                                       X-Ray Spectrom. 2004; 33: 256\u2013261258    P. Lechner, A. Pahlke and H. Soltau\n\n\n\n\n\n                                                                 Drift Rings\n\n\n\n                                                         Irradiated area\n\n\n                                                    Signal electrons\n\n\n                                         Anode and\n                                                      integrated FET\n\n\n\n\n      Figure 3. Layout of the SD3 chip. The integrated JFET is\n     moved to the margin of the chip. The drift \ufb01eld is de\ufb01ned in\n     such a way as to make all signal electrons drift towards the\n      readout anode situated next to the JFET. The size of the anode     Figure 4. Photograph of a mounted and bonded SD3 chip.\n        is 400 \u00b5m2.                                              The chip is mounted on a TO8 housing. The droplet-like shape\n                                                              can be seen.\n\n           gm D transconductance of the JFET (A V  1);               The standard SDD achieves an energy resolution of\n      A1, A2, A3 D constants depending on the \ufb01lter function of the     152 eV  at   11 \u00b0C (shaping time  1.0 \u00b5s)  at  5.9 keV (Mn\n                  shaper;                                     K\u02db) and a count rate of a few thousand cps, whereas\n          T D temperature (K);                                   the SD3 has an energy resolution of 134 eV under the\n         C D total detector capacitance (F);                  same conditions. By further cooling the SD3  to   15 \u00b0C\n                    af D constant parameterizing the 1/f noise (V2);        and using a smaller collimator (0.8 mm radius; see later)\n                        Il D leakage current (A);                           which covers the outer margin of the chip, the energy\n         D shaping time (s);                                    resolution can be improved to 128 eV  at a count  rate\n              q D elementary charge (C);                              of 100 cps  (see  Fig. 5). The shaping time  is  1.0 \u00b5s  for\n              kB D Boltzmann\u2019s constant (J K  1).                          this measurement. By further cooling the chip to   25 \u00b0C\n                                                        and at low count rates \u25b7<<1 kcps\u25c1, an energy resolution\n     For the noise equation, the mathematical frequency spectrum\n                                                                        of 125 eV could be achieved at shaping times of about\n   1  \u03c9 1 is used. The readout electronics use a source\n                                                                           1.5 \u00b5s (Rohde M, R\u00a8ontek Holding, personal communication,\n      follower con\ufb01guration. An Amptek A250 serves as a charge-\n                                                                         2001).\n      sensitive preampli\ufb01er.12\n                                                                          All measurements were performed with a radioactive\n       By reducing the capacitance, the electronic noise contri-                                                                        55Fe source. In the spectrum (Fig. 5) the Mn K\u02db (5895 eV) and\n      butions of serial white and serial 1/f noise can be minimized.\n     The detector capacitance of an SD3 is determined from ENC2\n     vs shaping time measurement and is measured to be about                                  energy (eV)\n     120 fF compared with 200 fF for standard SDDs.                          1000   2000   3000   4000   5000   6000\n         In Fig. 4, a mounted and bonded SD3 chip is shown. The        10000\n      chip is mounted on a TO8 housing with 16 pins for the                    shaping time 1,0 \u00b5s\n                                                                                    Temperature -15\u00b0C     supply voltages. A thermoelectric element is included in the         1000\n                                                                                    energy resolution 128 eV (Mn-K\u03b1)\n      housing. The droplet-like shape of the detector can easily be\n      seen. The homogeneous entrance window which is shown\n                                                                     100     on the picture consists of a \ufb02at p implant covered with a thin                  counts\n     aluminum layer. The detector is back-side illuminated.\n                                                                      10\n\n   MEASUREMENTS ON SD3 COMPARED WITH\n                                                                       1\n   STANDARD SDD                                               500     1000    1500    2000    2500    3000\n                                                                                                     channel\n    Energy resolution\n     To characterize the properties of the new SD3, chip measure-     Figure 5. Fe55 spectrum, showing an energy resolution of\n     ments were performed on standard SDD and SD3 chips from     128 eV at  15 \u00b0C. The spectrum was recorded using a shaping\n      the same wafer. The substrate orientation was < 100 >. Both      time of 1 \u00b5s, temperature  15 \u00b0C and count rate 100 cps. The\n     SD3 and standard SDDs underwent the same production      collimator used has a diameter of 1.6 mm. The\n      steps.                                                       peak-to-background value is \u00be9000.\n\n\n\n       Copyright \uf6d92004 John Wiley & Sons, Ltd.                                                                       X-Ray Spectrom. 2004; 33: 256\u2013261                                                                                Novel high-resolution silicon drift detectors   259\n\n\nMn K\u02c7 (6492 eV) lines can be seen. The theoretical limit for         350\nenergy       resolution is given by the Fano noise: FWHMFANO D                           0.25 \u00b5s   p\n2 ln\u25b72  2\u25c1  \u03b5FE  , where \u03b5  is the pair production energy         300              0.5 \u00b5s\n                                                                                            1.0 \u00b5s(3.7 eV for silicon at room temperature), F the Fano factor           (eV)                   2.0 \u00b5s\n(0.115 for silicon) and E  the energy of the absorbed photon         250\n(5895 eV for the Mn K\u02db line). This gives a theoretical limit                                                                                                                               Mn-K\u03b1\nof 118 eV for a detector based on silicon for the detection of         200\nthe Mn K\u02db line. The electronic noise of the detector can bedetermined in a good approximation by                                              FWHM 150\n\n               FWHM2  FWHM2FANO                     100\n         ENC D       p                      \u25b72\u25c1             -15   -10    -5    0     5    10    15    20    25\n                         2 ln\u25b72  2\u25c1\u03b5\n                                                                               Temperature (\u00b0C)\nThe electronic noise for an energy resolution of 128 eV was     Figure 7. Temperature dependence of the energy resolu\n\n## 5. lechner2004novelhighresolutionsilicon pages 4-5 (Context ID: pqac-00000027)\n\n                                                                                                    Mn-K\u03b1\nof 118 eV for a detector based on silicon for the detection of         200\nthe Mn K\u02db line. The electronic noise of the detector can bedetermined in a good approximation by                                              FWHM 150\n\n               FWHM2  FWHM2FANO                     100\n         ENC D       p                      \u25b72\u25c1             -15   -10    -5    0     5    10    15    20    25\n                         2 ln\u25b72  2\u25c1\u03b5\n                                                                               Temperature (\u00b0C)\nThe electronic noise for an energy resolution of 128 eV was     Figure 7. Temperature dependence of the energy resolution of\ndetermined as 5.7 electrons, which is independent of energy.     an SD3 chip. Even at room temperature the energy resolution\n   The improvement in energy resolution compared with       for the Mn K\u02db line is better than 200 eV. Cooling to  5 \u00b0C is\nstandard SDDs is a result of the reduced detector capacitance.      suf\ufb01cient for an energy resolution down to 140 eV.\nElectronic noise with regard to serial and 1/f  noise  is\nreduced. For comparison, SD3  detectors with standard                                                                   In Fig. 7 the temperature dependence of the spectroscopic\nreadout anode design were processed. They show the same                                                         performance of an SD3 chip is plotted. For a shaping time of\nenergy resolution as standard SDDs. The newly designed                                                                 0.25 \u00b5s the energy resolution is better than 200 eV for room\nreadout anode  is therefore the reason for the improved                                                             temperature. The in\ufb02uence of the temperature-dependent\nenergy resolution.                                                             leakage current can be reduced by the use of short shaping\n   The reduced energy resolution plays an important role                                                            times at room temperature. For temperatures below 0 \u00b0C the\nfor the detection of low-Z elements. For photon energies                                                 optimum shaping time changes to 0.5 or 1.0 \u00b5s because of the\nof 1000 eV the Fano noise is only 49 eV. Electronic noise of                                                                         serial noise contribution. Cooling to  15 \u00b0C is suf\ufb01cient for\nthe detector remains constant for all energies, as mentioned                                                 optimum energy resolution. This temperature can easily be\nabove. An improvement in energy resolution of 15 eV at                                                           achieved by the thermoelectric element which is included in\n5.9 keV, as has been seen for SD3 chips compared with                                                               the TO8 housing.\nstandard SDDs, is therefore very important for the detection\nof photons in the low energy range.                       Count rate dependence\n                                                    The count rate dependence is a very important point in many\nNoise measurement                                          \ufb01elds of applications.7 Si(Li) detectors are at a disadvantage\nTo extract the noise parameters of an SD3 chip, energy     because of their long shaping times. Silicon drift detectors\nresolution is measured for different shaping times (see Fig. 6).     bene\ufb01t from their low shaping times of less than 1.0 \u00b5s.\nThe chip is cooled with a thermoelectric element to  15 \u00b0C.         In Fig. 8, the count rate dependence of FWHM of Fe K\u02db\nUsing Eqn (1) \ufb01tting of a ENC2 vs shaping time measurement     (6400 eV) is plotted for a standard SDD compared with the\ngives a leakage current of 2.76 pA, a 1/f  coef\ufb01cient of     SD3 for two different shaping times. As x-ray source an x-\n4.79 \u00f0 10  12 V2 and a total detector capacitance of 120 fF.     ray tube with an iron anode was used. The gradient for the\nTypical total capacitance values for standard SDDs are 200 fF.\nLeakage current and 1/f coef\ufb01cient are the same for standard\n                                                              280\nSDDs.\n                                                              260            0.5 \u00b5s Std. SDD        1 \u00b5s\n                                                                                          1.0 \u00b5s Std. SDD\n                                                              240    120                                                                                                        (eV)                 0.5 \u00b5s SD3\n            leakage current:      1.37 pA                           220            1.0 \u00b5s SD3                 0.5 \u00b5s\n    100      1/f coefficient:        5.6475e-12 V2                                                                                                                              Fe-K\u03b1 200\n             detector capacitance: 119 fF\n                                                              180\n     80\n                                                              160 [q2]                                                                                                               FWHM\n ENC2  60                                                        140                                                              120\n     40                                                                 1000         10000        100000        1000000\n                                                                                 count rate (cps)\n     20\n                                                             Figure 8. Count rate dependence of FWHM of Fe for an SD3\n      0                                                         chip compared with a standard SDD. Because of the\n       0       1       2       3       4       5      6\n                                                           asymmetric shape of the SD3 chip the count rate dependence\n                                    \u03c4 [\u00b5s]\n                                                                                     is larger than that of a standard SDD. Nevertheless, even at a\nFigure 6. ENC2 vs  measurement for an SD.3 The \ufb01tting gives     count rate of 105 cps the energy resolution is better than\na total capacitance of 119 fF.                                180 eV for the Fe K\u02db line.\n\n\n\nCopyright \uf6d92004 John Wiley & Sons, Ltd.                                                                       X-Ray Spectrom. 2004; 33: 256\u2013261260    P. Lechner, A. Pahlke and H. Soltau\n\n\n     SD3 is somewhat higher than for standard SDDs. The reason        7000\n      for this behavior is the asymmetric shape of the detector.        6000\n     The rise time of the signal varies with the position of the                                                                   5000             SD3\n      incident photon. Especially for low shaping times which are                               standard SDD\n     needed for high count rates this results in a degraded energy        PTB 4000      resolution.                                                    3000\n                                                                                                                                              Partial events at\n         Nevertheless, using a shaping time of 0.5 \u00b5s count rates of        2000      Partial events at                  the outer margin                                                                                           the integrated FET\n      105 cps are feasible with an energy resolution of better than\n                                                                   1000\n     180 eV for Fe. The SD3 chip can therefore be used for count\n      rate applications up to 105 cps as well as the standard SDD.            0\n                                                                                      0.0     0.2     0.4     0.6     0.8     1.0     1.2\n                                                                                               collimator radius (mm)\n     Peak-to-background value\n   A good peak-to-background (PTB) value is important for     Figure 10. Peak-to-background values of an SD3 compared\n     low-energy spectroscopy. PTB is de\ufb01ned as the maximum      with a standard SDD for different collimator radii. The PTB of\n     amplitude of the Mn K\u02db line from a 55Fe radioactive source      the SD3 is no longer limited by partial events occurring at the\n     divided by the average amplitude of the continuum in the      integrated FET but only by the entrance windows and the outer\n     energy range from 800 to 1200 eV. The background of the     margin of the detector.\n    SDD spectrum is given by partial events occurring near the\n     FET, at the outer margin of the chip or in the \ufb01rst few      partial e\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027]\n\nStatus: Paper Count=23 | Relevant Papers=8 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=28 | Current Cost=$0.1511 | Disease-Target Evidence=0",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000028\n\nFrom text 'rinaldi2015electronprobemicroanalysis pages 7-8'.\n\nRomano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.\n\nAt low beam energies (<5 keV), FEG electron sources can achieve finely focused beams (<100 nm) with relatively high currents (up to 100 nA), reducing the effective ionization range to sub-micrometer scales and improving lateral resolution and surface sensitivity. For trace element analysis, detection limits of a few ppm are achievable through high-beam currents (up to 3 \u03bcA) and long acquisition times. Improved methods employ fractional counting times at multiple sample positions to mitigate beam damage, statistical data filtering, and improved background modeling. Analyses for trace elements at high resolution have been performed at 35 keV with 500 nA and total counting times of 15 minutes. However, at low voltages (5-6 keV), accuracy challenges arise with systematic deviations in transition element analysis, including Cr underestimation (-0.7 to -17%) and Fe/Ni overestimation (+14 to +42%), highlighting the need for careful standard selection and X-ray line choices at low overvoltages.\n\n\n---\n\n## pqac-00000029\n\nFrom text 'wuhrer2016lowvoltageimaging pages 7-10'.\n\nRichard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.\n\nThe excerpt discusses low-voltage SEM microanalysis and acquisition parameter adjustments. It explains that lowering accelerating voltage improves spatial resolution and image quality, requiring selection of lower excitation energy X-ray lines (L- and M-family lines at 0-4 kV) rather than K-lines. Beyond voltage adjustment, reducing probe current and changing scan speed are necessary acquisition parameter modifications. The excerpt mentions improved detector technology with SDD detectors achieving greater X-ray collection efficiencies and better sensitivity for low-energy X-rays. New soft X-ray spectroscopy systems offer superior energy resolution and detection limits for light elements below 100 ppm. Higher accelerating voltages create larger interaction volumes that degrade spatial resolution, while lower voltages reduce the analytical volume. However, the excerpt does not specifically address overvoltage effects at 5 keV or detailed counting strategies for trace element detection.\n\n\n---\n\n## pqac-00000030\n\nFrom text 'wuhrer2016lowvoltageimaging pages 10-12'.\n\nRichard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.\n\nThe excerpt discusses challenges with low-voltage EDS analysis that relate to trace element detection and sensitivity. At lower accelerating voltages, there is improved spatial resolution but analysts must shift to L- and M-family X-ray lines (0-4 kV) rather than K-lines. However, measurement of low-energy L-lines presents complications including low fluorescence yield, increased X-ray absorption, X-ray interferences from other elements, and poorly determined mass absorption coefficients. The use of transition element L-lines specifically results in poor accuracy and sensitivity. Large quantification errors exist on lower energy X-ray lines, limiting quantitative analysis capabilities. The excerpt emphasizes that for accurate results, standards-based analysis is preferable to standardless analysis, though errors remain.\n\n\n---\n\n## pqac-00000031\n\nFrom text 'gollaschindler2026edswithlowvoltage pages 3-6'.\n\nUte Golla-Schindler and Gerhard Schneider. Eds with low-voltage sem: possibilities and limitations of lithium detection and quantification. EPJ Web of Conferences, 349:01004, Jan 2026. URL: https://doi.org/10.1051/epjconf/202634901004, doi:10.1051/epjconf/202634901004. This article has 0 citations and is from a peer-reviewed journal.\n\nThis excerpt discusses low-voltage EDS analysis and how lowering accelerating voltage addresses detection limits and spatial resolution challenges. It explains that reducing accelerating voltage from 20 keV to 1 keV decreases interaction volume by approximately 100 times, improving both information depth and spatial resolution. The information depth is roughly one-third to one-half of the electron range. The excerpt notes that detection limits depend on scattering cross-section and signal detection capabilities. It also addresses acquisition parameter adjustments, noting that lowering beam current and current density reduces all beam damage effects. At lower voltages, knock-on damage decreases but beam damage from heating and ionization may increase due to enhanced cross-sections for inelastic and elastic scattering. The text emphasizes that these factors become increasingly critical with decreasing acceleration voltage, particularly for light element detection.\n\n\n---\n\n## pqac-00000032\n\nFrom text 'gollaschindler2026edswithlowvoltage pages 1-3'.\n\nUte Golla-Schindler and Gerhard Schneider. Eds with low-voltage sem: possibilities and limitations of lithium detection and quantification. EPJ Web of Conferences, 349:01004, Jan 2026. URL: https://doi.org/10.1051/epjconf/202634901004, doi:10.1051/epjconf/202634901004. This article has 0 citations and is from a peer-reviewed journal.\n\nThis paper by Golla-Schindler and Schneider addresses EDS (Energy Dispersive X-ray Spectroscopy) detection capabilities in low-voltage SEM, specifically focused on lithium detection and quantification in lithium-ion batteries. The work discusses how low accelerating voltages improve detection by increasing effective cross-sections for elastic and inelastic interactions, thereby generating more secondary and backscattered electrons. The study presents methods to reduce examination artifacts through lower accelerating voltages and beam currents. Key challenges addressed include contamination, radiation damage, and charging effects that can compromise EDS analysis accuracy. The authors demonstrate the use of a windowless Oxford Extreme EDS detector (100 mm\u00b2 size, 124.7 eV energy resolution for Mn) that enables low-energy X-ray detection. The paper also introduces a novel quantification method called 'Li by difference' for calculating lithium content from non-normalized EDS quantification. However, the excerpt provided does not contain specific information about Newbury-Ritchie detection limits, detailed acquisition parameters at specific beam energies like 5 keV, overvoltage effects, or counting strategies for trace elements.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032]\n\nStatus: Paper Count=23 | Relevant Papers=11 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=33 | Current Cost=$0.1950 | Disease-Target Evidence=0",
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+                "content": "Let me now gather evidence specifically from the Newbury papers and Goldstein text for the Bethe/overvoltage derivation and detection limits:",
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+                      "arguments": "{\"question\": \"Newbury Ritchie EDS detection limits trace analysis 0.001 mass fraction measurement time dose counting statistics precision accuracy standardless vs standards-based quantification\"}",
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+                      "arguments": "{\"text_name_list\": [\"newbury2019electronexcitedxraymicroanalysis pages 13-15\", \"newbury2019electronexcitedxraymicroanalysis pages 15-16\", \"newbury2019electronexcitedxraymicroanalysis pages 16-18\", \"newbury2015performingelementalmicroanalysis pages 2-4\", \"newbury2015performingelementalmicroanalysis pages 17-20\"]}",
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+                "content": "Most relevant evidence (with ids):\n\n## pqac-00000033\n\nFrom text 'newbury2015performingelementalmicroanalysis pages 1-2'.\n\nDale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 609 citations and is from a peer-reviewed journal.\n\nThis paper demonstrates that SDD-EDS enables trace element detection with limits of detection below 0.001 mass fraction (1000 ppm) within practical measurement times of 500 seconds. The authors describe the k-ratio protocol for quantitative analysis, where characteristic X-ray intensities from unknowns are compared to standards under identical conditions (same beam energy, dose, and detector efficiency). This approach allows the detector efficiency to cancel out mathematically, improving accuracy and precision. The k-ratio/ZAF matrix correction method represents a standards-based quantification approach where measurements don't require standards that closely match the unknown composition, providing flexibility for analyzing complicated multi-element materials. The SDD advances provide accuracy and precision comparable to wavelength-dispersive spectrometry on electron probe microanalyzers, with high-count spectra enabling accurate peak fitting even for severe peak overlaps.\n\n\n---\n\n## pqac-00000034\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 13-15'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses EDS (Energy Dispersive Spectrometry) detection limits and analytical precision for trace element analysis. Trace elements are defined as those with mass concentration C < 0.01. Detection limits ranging from 0.0002\u20130.0005 mass fraction (200\u2013500 ppm) can be achieved with counting times below 500 seconds, depending on the element and matrix composition. The detection limit formula CDL = [3NB1/2/(NS \u2212NB)]CS is presented, where NB is background counts, NS is peak counts, and CS is the known concentration. The excerpt includes precision data showing relative standard deviations (\u03c3 relative) ranging from 0.008\u20131.8% and combined uncertainties from 0.0044\u20131.7% for various elements. The analysis addresses challenges including peak overlap from major/minor constituents and peak interference situations that can be resolved through peak fitting techniques.\n\n\n---\n\n## pqac-00000035\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 1-2'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThis review article by Newbury and Ritchie from 2019 discusses the 50-year evolution of energy dispersive X-ray spectrometry (EDS) in electron-excited X-ray microanalysis. The authors highlight that EDS has matured into a fully quantitative analytical technique capable of matching wavelength dispersive spectrometry (WDS) accuracy for major constituents (>0.1 mass fraction) and minor constituents (0.01-0.1 mass fraction). Importantly, the article indicates that useful analytical accuracy can extend into the trace constituent range (0.001 < mass fraction < 0.01), even when severe peak interference occurs. The excerpt discusses the foundational standards-based k-ratio protocol with matrix correction factors (Z, A, F, c corrections) developed by Castaing. The article emphasizes the importance of controlling measurement parameters such as dose, spectrometer performance, and instrumental drift. The presence of pages 1-2 suggests the full article likely contains more detailed discussion of detection limits, measurement time requirements, counting statistics, precision, accuracy, and potentially comparisons between standardless and standards-based quantification methods.\n\n\n---\n\n## pqac-00000036\n\nFrom text 'ritchie2018exploringthelimits pages 9-11'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThis study explores EDS (Energy Dispersive Spectroscopy) capabilities for rare earth element analysis using silicon drift detectors (SDD). For major/minor elements above 1% mass fraction, SDD achieved relative deviations better than 10%. Between 0.1-1% mass fraction, detection was inconsistent with large uncertainties. Below 0.1% mass fraction, detection was unreliable. The analysis required extended acquisition times (10 minutes live-time per measurement). The authors note that WDS (Wavelength Dispersive Spectroscopy) maintains lower detection limits due to superior peak-to-background ratios. While most EDS measurements remain qualitative or standardless with large error bars, careful analysts using standards-based quantification can achieve accurate results comparable to WDS for major/minor elements. The study suggests combining SDD speed and accuracy for major elements with WDS sensitivity for trace elements.\n\n\n---\n\n## pqac-00000037\n\nFrom text 'ritchie2018exploringthelimits pages 1-4'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThis paper discusses EDS (energy-dispersive X-ray spectrometry) capabilities for trace element analysis, specifically examining rare-earth element detection. The authors explain that EDS detection limits are primarily constrained by the background (continuum) level relative to signal (characteristic) level. They demonstrate that trace measurements in the 0.1-1.0% mass fraction range can be performed accurately with modern silicon drift detectors (SDDs). However, SDDs cannot match WDS (wavelength-dispersive X-ray spectrometry) at the lowest trace levels due to inferior peak-to-background ratios. The paper emphasizes recent improvements in EDS technology\u2014particularly SDDs\u2014that have dramatically enhanced throughput and resolution (approaching 120 eV at Mn-K\u03b1). The authors note that peak-to-background ratios in EDS depend on channel ranges used for continuum and peak estimation, with optimal results achieved by integrating peaks over the central full-width half-max. Recent advances allow EDS to match or exceed WDS accuracy and precision in many applications.\n\n\n---\n\n## pqac-00000038\n\nFrom text 'ritchie2018exploringthelimits pages 4-5'.\n\nN W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\nThis paper addresses EDS (Energy Dispersive Spectroscopy) microanalysis capabilities for trace element detection, specifically focusing on rare earth elements (REE) in mineral samples. The authors discuss measurements of materials with trace quantities below 10% mass fraction, which present challenges for both WDS and EDS techniques. The paper covers the k-ratio quantification method comparing unknown samples to standards, matrix corrections accounting for atomic number (Z), absorption (A), and secondary fluorescence (F) effects, and the importance of multiple measurements for quality assurance. For accurate trace analysis, the authors recommend collecting multiple spectra (5-10 acquisitions) to enable inter-comparison, outlier rejection, and improved spectral quality. The paper includes practical examples using rare earth element-containing glasses at approximately 3-4% mass fraction, demonstrating EDS measurement capabilities at these concentration levels.\n\n\n---\n\n## pqac-00000039\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 18-20'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThis excerpt from Newbury & Ritchie (2019) discusses standardless quantification methods in EDS microanalysis. Standardless analysis requires only beam energy and spectrometer takeoff angle, but lacks electron dose information, necessitating normalization to 100 wt% for meaningful results. Early testing showed standardless analysis produced relative deviations (RDEV) spanning \u00b125% range for 95% of results. The authors note that approximately 95% or more of EDS quantitative compositional results are derived from standardless analysis. The excerpt includes analysis data from NIST reference materials (K523 glass and SRM 610 trace elements glass) measured at 20 keV, demonstrating detection capabilities for trace elements and providing measured concentrations with uncertainties. However, the excerpt does not explicitly address detection limits at 0.001 mass fraction, measurement time, dose-counting statistics relationships, or detailed comparisons of standardless versus standards-based approaches.\n\n\n---\n\n## pqac-00000040\n\nFrom text 'newbury2019electronexcitedxraymicroanalysis pages 16-18'.\n\nDale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\nThe excerpt discusses two quantification approaches in EDS analysis: first-principles standardless analysis and standards-based methods using remote standards. The remote standards method is described as inherently more accurate than first-principles standardless analysis, providing a compromise between the two approaches since it is tied to measurements of real materials. However, the authors note a significant limitation: vendors implementing standardless quantification often lack adequate documentation explaining their methodology for deriving numerical concentrations. The excerpt emphasizes the importance of understanding which quantification method is being employed and how it affects analytical accuracy. Additionally, the text mentions detector calibration methods, including use of a 'golden detector' calibrated at a beamline to transfer calibration to other detectors.\n\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040]\n\nStatus: Paper Count=23 | Relevant Papers=14 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=41 | Current Cost=$0.2376 | Disease-Target Evidence=0",
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+                "content": "## 1. newbury2015performingelementalmicroanalysis pages 2-4 (Context ID: pqac-00000041)\n\n                                     as determined by a mature version of the k-ratio/matrix\nunknown and standards required for Eq. (1) [3]. To place\n                                                               correction procedure in 1975 is shown in Fig. 1 for WDS\nthe specimen reproducibly within the narrow spatial range,                                                      measurements of major1 constituents [5]. This distribution\nspanning a few micrometers, over which the WDS had\n                                                       can be characterized by a standard deviation of 2.5 %\nconstant  X-ray  transmission,  a  \ufb01xed-position  optical\n                                                                      relative, so that approximately 95 % of the analyses fall\nmicroscope with a shallow depth of focus was incorporated\n                                                            within the span of \u00b15 % relative error.\ninto the EPMA at the coincident focal position for  all\nspectrometers. The condition of the specimen surface was\nrecognized to be another critical requirement [4]. It came to\nbe understood early in the development of EPMA that the\nspecimen had to metallographically polished to a very high\ndegree of surface \ufb01nish, but not chemically etched. To\ncreate contrast in optical metallography, chemical etching\ntypically produces topography through orientation-depen-     1 Note: in this paper, the following arbitrary convention for broadly\ndent etch rates in different grains and phases, but even \ufb01ne-     classifying the concentration range will be followed:\nscale topography can in\ufb02uence measured X-ray intensities,\n                                                                                    \u2018\u2018major,\u2019\u2019 mass concentration C [ 0.1 (more than 10 wt%)\nespecially  for low-energy photons. Moreover,  in some\n                                                                                \u2018\u2018minor\u2019\u2019 0.01 B C B 0.1 (1\u201310 wt%)\ncases, chemical etching induces changes in the surface/         \u2018\u2018trace\u2019\u2019 C \\ 0.01 (\\1 wt%).\n\n123J Mater Sci (2015) 50:493\u2013518                                                                                        495\n\n\nFurther development: energy-dispersive X-ray               continuum, various strategies were developed to determine\nspectrometry                                                     characteristic  intensities,  including  digital  \ufb01ltering  for\n                                                      background removal followed by  multiple  linear  least\nThe development of semiconductor-based X-ray detection    squares (MLLS) \ufb01tting and background modeling under the\nin the 1960s led to the \ufb01rst successful energy-dispersive    peak window  constrained by  the continuum  intensity\nX-ray spectrometer (EDS) using lithium-compensated sil-    measured in energy windows where no peaks occurred [8,\nicon [Si(Li)-EDS] operated on an electron-column instru-    10]. The background-corrected  characteristic  intensities\nment,  an EPMA  [6]. As  compared  to  the  narrow    for the unknown and the standards were used to calculate\ninstantaneous energy range of the WDS, the Si(Li)-EDS     k-ratios followed by the matrix correction procedure. The\nprovided a view of the entire excited X-ray spectrum from     k-ratio matrix correction procedure with the Si(Li)-EDS\na  threshold  of approximately 100 eV (modern  perfor-   was demonstrated to be capable of achieving relative errors\nmance) to the Duane-Hunt limit set by the incident beam    within the WDS distribution for major constituents when\nenergy, up to 20 keV or higher. This wide energy range    the characteristic X-ray peaks did not suffer signi\ufb01cant\nenabled detection of all elements, with the exception of H    overlap from the peaks of other elements. An example is\nand He (modern performance), at every location sampled   shown in Table 1 for the Si(Li)-EDS analysis of gold-\nby the beam, which provided an enormous advantage when    copper alloys (NIST Standard Reference Material 482)\ndealing with complex microstructures where local segre-    where the observed relative errors range from -1.6 to\ngation can create unexpected compositional variation and    1.0 %, falling well within the WDS analysis error distri-\nwhere unexpected elements can be localized as inclusions.    bution of Fig. 1.2 Further development of the EDS quan-\nComprehensive elemental analysis capability, combined     titative microanalysis method enabled accurate analyses\nwith the relative simplicity of non-focusing line-of-sight   when signi\ufb01cant peak overlaps occurred providing the\ndetection, the large solid angle of collection which exceeds     intensities of the mutually interfering species were similar.\nthat of WDS by at least a factor of 10, and the long-term\noperating stability, resulted in the enthusiastic acceptance    Typical SEM/EDS microanalysis practice\nof EDS, especially by the rapidly developing scanning\nelectron microscope (SEM) community. The combination    Despite the level of analytical accuracy demonstrated for\nof SEM imaging with EDS X-ray microanalysis has given    the EDS k-ratio/matrix corrections protocol and the avail-\nthe materials community one of its most powerful micro-     ability of this procedure within most commercial imple-\nstructural characterization tools [2].                         mentations of EDS analytical software, modern SEM/EDS\n  The capability of Si(Li)-EDS to perform quantitative    microanalysis practice has developed along a  different\nX-ray microanalysis was established soon after its intro-    trajectory that minimizes the need for the user\u2019s expertise.\nduction by several members of the microanalysis commu-   As an unintended consequence, EDS microanalysis as\nnity, most  of whom had  extensive WDS  quantitative    performed in the SEM has acquired an unfortunate repu-\nmicroanalysis experience [7\u201311]. Thus, the  initial EDS    tation as a \u2018\u2018semi-quantitative\u2019\u2019 technique. This situation\nimplementation of quantitative analysis was based upon    has developed because of three contributing factors: (1) the\ntheir experience with the WDS k-ratio protocol. The EDS     rise of standardless analysis which now dominates EDS\ncould be used in an equivalent manner by measuring the    quantitative analysis [14]; (2) the severe effects of speci-\nintensities  for  the unknown and  appropriate  standards   men geometry on the accuracy of X-ray microanalysis\nunder the same carefully controlled conditions of surface    which occur no matter which analytical protocol is fol-\ncondition (highly polished), beam energy, known dose    lowed, standards-based or standardless [15]; and (3) the\n(beam current 9 detector live time), beam incidence angle,    occasional but signi\ufb01cant failures in qualitative analysis,\ndetector elevation angle (\u2018\u2018take-off angle\u2019\u2019), and detector      i.e., incorrect elemental identi\ufb01cation, which immediately\nef\ufb01ciency (e.g., constant detector-to-target distance to yield    undermines con\ufb01dence in the method [16\u201318].\nconstant detector solid angle). The enormous advantages of\nthe EDS over WDS for analysis were quickly recognized:   The rise of \u2018\u2018standardless\u2019\u2019 quantitative analysis\n(1) all elements in the unknown were measured simulta-\nneously minimizing the dose to the specimen; (2) the large   By necessity, WDS measures each element in the sample\nsolid angle of the EDS relative to WDS further improved     relative to the same element in an appropriate standard to\nef\ufb01ciency of detection which lowered the necessary dose\nrelative to WDS; and (3) the stability of the EDS meant\n                                                                                2 Materials analyzed in this paper include NIST Standard Reference\nthat the spectra of standards could be archived and recalled\n                                                                           Materials, NIST microanalysis research materials (glasses), natural\nas needed. Since the measured EDS spectrum consists of     minerals, and stoichiometric compounds con\ufb01rmed to be homoge-\nthe characteristic X-ray peaks superimposed on the X-ray    neous on a micrometer lateral scale.\n\n                                  123496                                                                                                                  J Mater Sci (2015) 50:493\u2013518\n\n\nTable 1 Si(Li)-EDS analysis of NIST Standard Reference Material 482 Copper\u2013Gold Alloysa (all concentration values in mass fraction)\n\nCu (certi\ufb01ed)        Analyzed              Rel. error (%)      Au (certi\ufb01ed)        Analyzed              Rel. error (%)        Total\n\n0.198               0.198 \u00b1 0.002           0.0                0.801               0.790 \u00b1 0.002       -1.4                0.988\n\n0.396               0.399 \u00b1 0.001           0.8                0.603               0.594 \u00b1 0.002       -1.6                0.993\n\n0.599               0.605 \u00b1 0.001           1.0                0.401               0.402 \u00b1 0.002        \n\n## 2. newbury2015performingelementalmicroanalysis pages 17-20 (Context ID: pqac-00000042)\n\nfeatureless background\npeaks are separated by 4 eV. The results of k-ratio protocol    under the composite peaks. Figure 17b demonstrates that\nanalysis of seven replicates with DTSA-II are also pre-   when peak \ufb01tting is performed without including a peak\nsented in Table 11, using elemental Ti and the mineral    reference for Ti, the TiKa and TiKb peaks can be recog-\nsanbornite (BaSi2O5)  for Si and Ba as references and    nized in the residuals. This example illustrates that com-\nstandards, with O calculated by assumed stoichiometry.    prehensive analysis of an unknown must be performed\nAfter quanti\ufb01cation with DTSA-II, the relative errors are     iteratively. In  the  \ufb01rst round,  qualitative  analysis  \ufb01rst\nless than 2.5 % for all measured constituents.                 identi\ufb01es with high con\ufb01dence the major constituents and\n\n\n                                  123510                                                                                                                  J Mater Sci (2015) 50:493\u2013518\n\n\n\n\n\n                                               SrWO4\n                                                              E0 = 10 keV\n                                                                         Fi  ng with SrF2 and W\n                                      O by stoichiometry\n\n\n\n\n\nFig. 15 SDD-EDS spectrum of SrWO4 at a beam energy of E0 = 10 keV (red); residual spectrum (blue) after peak \ufb01tting with SrF2 and W\n(Color \ufb01gure online)\n\n\nTable 9 NIST DTSA-II SDD-EDS analysis of SrWO4 at E0 = 10 keV; SrF2 and W as references and standards; O by stoichiometry; 15\nreplicates\n\nParameter              Raw analytical total        O (atomic conc.,             Sr (atomic conc.)      W (atomic conc.)\n                           (mass concentration)          by stoichiometry)\n\nMean                       1.0017                        0.6660                     0.1678                     0.1661\n\nRelative error (%)                                     -0.10                       0.68                     -0.33\nr                          0.0019                        0.00053                    0.00065                    0.00033\nr relative (%)                0.19                           0.80                        0.39                        0.20\n\n                                   O (mass conc.)                Sr (mass conc.)       W (mass conc.)\n\nSingle analysis                     1.0029               0.1913                       0.2627                       0.5489\n\nRelative error (%)                                         0.27                          0.58                          0.16\n\nk error (%)                                                                               0.0007, 0.27                   0.0009, 0.16\n\nA-factor error (%)                                                                        0.0093, 3.5                    0.0077, 1.4\n\nZ-factor error (%)                                                                2.7E-5, 0.010               5.8E-5, 0.011\n\nCombined errors (%)                                                                      0.0093, 3.5                    0.0078, 1.4\n\n\n\nany well-resolved minor and trace constituents present.     The residual spectrum can also be used to estimate\nAfter peak \ufb01tting and quantitative analysis for those ele-    limits of detection for trace constituents of interest, and the\nments are performed, careful examination of the residual    analytical strategy can be modi\ufb01ed if necessary to lower\nspectrum with those peaks stripped off may reveal previ-    the limit of detection by accumulating more counts.\nously unrecognized minor and trace constituents hidden\nunder the higher intensity peaks. In the second round, the    Quantifying a trace constituent with severe interference\nfull analysis is then repeated, including the newly recog-    from a major constituent\nnized minor/trace constituents. If inspection of the latest\nresiduals reveals no new peaks, the analysis can be con-   NIST microanalysis glass K873, the spectrum of which is\nsidered complete.                                   shown  in  Fig. 18 and whose composition  is  listed  in\n\n123J Mater Sci (2015) 50:493\u2013518                                                                                        511\n\n\n\n                                               WSi 2\n                                                             E0 = 10 keV\n                                                                        Fi  ng with Si and W\n\n\n  Counts\n\n\n\n\n\n                                             photon Energy (kev)\n\nFig. 16 SDD-EDS spectrum of WSi2 at a beam energy of E0 = 10 keV (red); residual spectrum (blue) after peak \ufb01tting with Si and W (Color\n\ufb01gure online)\n\n\nTable 10 NIST  DTSA-II  SDD-EDS   analysis   of  WSi2   at    Ba, Al2O3 for Al, CeO2 for Ce, PbTe for Pb, and with O\nE0 = 10 keV; Si and W as references and standards; 12 replicates      calculated by assumed stoichiometry. The relative errors in\nParameter        Raw analytical total   Si (atomic W (atomic    the trace constituents are 20 % for Ce and -20 % for Ta,\n                   (mass concentration)   conc.)       conc.)       which might be further reduced by accumulating higher\n                                                               counts.\nMean              0.9801               0.6615      0.3385\n\nRelative error (%)                      -0.78       1.55\n                                                             Quantitative X-ray microanalysis of low atomic number\nr                  0.0057               0.0011      0.0011\n                                                          elements\nr relative (%)       0.58                  0.17        0.33\n\n                                 Si (mass conc.)  W (mass conc.)    Quantitative electron-excited X-ray microanalysis of the\n                                                   low atomic number elements, including C, N, O, and F that\nSingle analysis        0.9894   0.2262           0.7632\n                                                       can only be measured with X-ray peaks whose energies fall\nRelative error (%)             -3.4           -0.36\n                                                    below 1 keV, has presented a great challenge since the\nk error (%)                      0.0002, 0.088     0.0005, 0.066\n                                                                       earliest years of the electron-excited X-ray microanalysis\nA-factor error (%)               0.0002, 0.088     0.0047, 0.62\n                                                           technique [2]. When measured with wavelength-dispersive\nZ-factor error (%)             6.6E-6, 0.0029   0.0002, 0.026\n                                                             spectrometry, the low-energy photon peaks are subject to\nCombined errors (%)            0.00028, 0.13     0.0047, 0.62\n                                                               the so-called \u2018\u2018chemical effects\u2019\u2019 manifested as shifts in the\n                                                       X-ray peak position and changes in peak shape that depend\n                                                   on chemical binding. These effects have been described in\nTable 12, features two examples of interference of a major     detail in the classic series of papers by Bastin and Heiligers\nconstituent upon a trace constituent: Ba (concentration    [26], who developed a \u2018\u2018peak-shape\u2019\u2019 factor correction to\n0.219 mass fraction) on Ce (0.0041) (Ba/Ce = 53/1) and Si    compensate for chemical shifts that signi\ufb01cantly affected\n(0.115) on Ta (0.0041) (Si/Ta = 28/1). The BaLb1 and   \ufb01xed peak-channel WDS measurements. The low-Z spec-\nCeLa peaks are separated by 12 eV, while the BaLb2 and    trum measurement problem is further complicated by peak\nCeLb1 peaks are separated by 106 eV. The SiKa  falls    interferences that often arise from the L-, M-, and N-family\nbetween the TaMa (-30 eV) and the TaMb (26 eV). The    X-rays of heavier elements that occur throughout this low\nresults of k-ratio protocol analysis of seven replicates with    photon energy range. Because of the signi\ufb01cantly poorer\nDTSA-II are also presented in Table 12, using as standards    spectral resolution of EDS compared to WDS and the\nelemental Mn and Ta, with sanbornite (BaSi2O5) for Si and    consequent impact of interfering peaks, direct quantitative\n\n\n                                  123512                                                                                                                  J Mater Sci (2015) 50:493\u2013518\n\n\n                   Minor element (0.01\u2264 C \u2264 0.1) quantification with major element (C > 0.1) overlap\n\n (a)                                                               K2496 glass\n                                                                                 E0 = 10 keV\n                                                                   1000 nA-s\n              K2496\n               \n\n## 3. newbury2019electronexcitedxraymicroanalysis pages 13-15 (Context ID: pqac-00000043)\n\n          Concentration)            Concentration)              Concentration)\n\n\n        Mean                        0.9823                    0.3197               0.2256                    0.0176                   0.4371\n\n          As-synthesized                                         0.3230               0.2291                    0.0180                   0.4299\n\n        RDEV (%)                                          \u22121.0                \u22121.5                    \u22122.2                         1.7\n\n        \u03c3 (seven                                              0.000049             0.00028                  0.00031                  0.00058\n           replicates)\n\n        \u03c3 relative (%)                                           0.008                 0.13                        1.8                       0.13\n\n         k uncertainty                                                                    0.0001, 0.044%            0.0003, 1.7%              0.0007, 0.16%\n\n           A-factor                                                                          0.0015, 0.66%             0.0000039, 0.022%        0.000019, 0.0044%\n          uncertainty\n\n           Z-factor                                                                       0.000011, 0.0049%        0.0000003, 0.0014%       0.00000021, 0.000048%\n          uncertainty\n\n        Combined                                                                       0.0015, 0.66%              0.0003, 1.7%              0.0007, 0.16%\n          uncertainty\n\n\n\n      the lateral resolution and reducing the sampling depth (Goldstein   Microanalysis of Trace Elements\n       et al., 2018). However, to excite a particular characteristic X-ray\n                                                             Measurement of trace elements, arbitrarily defined in this paper\n      peak, the beam energy must exceed the critical shell excitation\n                                                                            as those present at a mass concentration C < 0.01, involves fitting\n       energy, Ec, ideally by a factor of at least 1.25. This condition places                                                                   peaks that are close to the X-ray continuum background and that\n       practical constraints on the selection of E0. A beam energy of                                                     may also be subject to overlap from the significantly more\n      5 keV  is the lowest value at which at least one characteristic\n                                                                         intense peaks of major and minor constituents. In the absence\n      X-ray peak or family can be excited for  all elements of the                                                                            of significant peak overlap, limits of detection in the range\n       Periodic Table, except for H and He which do not produce char-                                                                   0.0002\u20130.0005 mass concentration (200\u2013500 parts per million),\n        acteristic X-rays. As the beam energy is reduced below 5 keV, an                                                                depending  on  the   particular  element  and  the  matrix\n       increasing number of elements becomes inaccessible to EPMAdue   composition, can be reached with counting times below 500 s\n       to the lack of a practically measurable characteristic X-ray peak   (Newbury &  Ritchie,  2016b). An  example   is  shown  in\n     (Newbury & Ritchie, 2016a). Even with the selection of E0 =    Figure 10 for NIST microanalysis glass K523, which has the\n      5 keV, the analyst is forced to make use of unfamiliar X-ray fam-    as-synthesized composition listed in Table 22. For peaks that\n         ilies for some elements. For example, Ba is typically analyzed with   do not suffer interference, CDL, the limit of detection (minimum\n      the Ba L-family X-rays (L3 = 5.247 keV), but this family is not   mass fraction) can be estimated from the measured (or indepen-\n       available with E0 \u22645 keV, requiring the use of the Ba M-family,    dently known) composition as\n      which is illustrated in Figure 9a. A difficult low beam energy anal-\n        ysis involving the Ba M-family is presented in Figure 9b, which\n                                                                         CDL = [3NB1/2/(NS \u2212NB)]CS,               (6)      shows the spectrum for YBa2Cu3O7 and the peak-fitting residual.\n      This analysis involves interference of the O K-L2,3 family and the\n     Cu L-M family with the Ba M-family. The results, including oxy-   where NB is the number of counts in the background under the\n      gen analyzed with a standard, are presented in Table 21, where the   peak (integral across the contiguous channels that define the\n       largest RDEV is 6.5% relative for Y. Ba, despite the severe interfer-    peak), NS is the number of counts in the peak integral, and CS\n      ence of the O K-L2,3 family and the Cu L-M family, is analyzed     is the known (or measured) concentration of the trace constitu-\n      with an RDEV of 0.5%. Additional challenges that become signif-   ent (Goldstein et al., 2018). For the particular measurement con-\n       icant at low beam energy include the stratified nature of most    ditions listed in Table 22, the values of CDL estimated with\n       materials. Native oxides and other surface layers make a more sig-   equation (6) are listed for several of the trace constituents.\n       nificant contribution to the measured spectrum at low incident     An example of trace measurements at the extreme limit of EDS\n     beam energy compared with the measurement at conventional    microanalysis (spectrum integral 0.1\u201320 keV = 1.7 billion counts)\n     beam energies, where the surface layer comprises only a small     is presented in Figure 11, which shows the spectrum of NIST\n       fraction of the total electron range. Contamination from carbon  SRM 610 (\u201cTrace Elements  in Glass\u201d) containing numerous\n      deposition can increase the absorption of X-rays with energies    trace elements at a nominal level of 0.0005 mass fraction (500\n      near the carbon K-edge (0.284 keV) above that expected from    parts per million) in a matrix of O\u2013Na\u2013Al\u2013Si\u2013Ca. There are\n      the compositions of the unknown and standard. While this effect   many peak interference situations encountered in the analysis of\n       also occurs for conventional beam energy analysis, the analytical  SRM 610, but those that involve mutual interferences of trace\n       strategy can usually make use of more energetic characteristic    constituents that produce peaks of similar intensity, e.g., the Ti\n      X-ray peaks that are much less affected by absorption from the   K-family and the Ba L-family, can be solved with peak fitting.\n      contamination layer.                                            Table 23 gives the results of the DTSA-II analysis. With some\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X     14                                                                                 Dale E. Newbury and Nicholas W.M. Ritchie\n\n\n\n\n\n        Fig. 8. EDS spectrum of an inclusion in NIST SRM 168 (E0 = 20 keV) for the photon energy range from 0 to 10 keV: (a) full spectrum with a linear intensity axis; (b) full\n      spectrum with a logarithmic intensity axis; (c) spectrum and peak fitting residual spectrum (blue) after fitting for Ti, Cr, Fe, Co, Nb, and Ta; (d) expansion 0\u20135 keV\n      showing the detection of the W M-family in the peak fitting residual spectrum; and (e) original spectrum (green) and comparison of second (red) and third (blue)\n      peak fitting residual spectra, showing the detection of Mo L-family. Note that where the red and blue traces overlap exactly, the red spectrum dominates the display.\n\n      exceptions, e.g., Cu, the EDS results are consistent with the bulk    When the X-ray peak for a trace constituent is buried under\n      analysis  values reported  for  this SRM (Newbury &  Ritchie,    the interfering peak of a major or minor constituent, the measure-\n     2016b).                                                ment challenge  is substantially increased. Moreover, there are\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X      Microscopy and Microanalysis                                                                                          15\n\n\n\n\n\n         Fig. 8. Continued.\n\n\n\n       Table 15. Analysis of an Inclusion in SRM 168 (E0 = 20 keV) Pure Element Standards.\n\n                                Analytical\n     \n\n## 4. newbury2019electronexcitedxraymicroanalysis pages 15-16 (Context ID: pqac-00000044)\n\ntchie,    the interfering peak of a major or minor constituent, the measure-\n     2016b).                                                ment challenge  is substantially increased. Moreover, there are\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X      Microscopy and Microanalysis                                                                                          15\n\n\n\n\n\n         Fig. 8. Continued.\n\n\n\n       Table 15. Analysis of an Inclusion in SRM 168 (E0 = 20 keV) Pure Element Standards.\n\n                                Analytical\n         SRM168_Inclusion     Total        C           Ti         Cr         Fe       Co         Ni       Nb         Mo        Ta     W\n\n\n            First analysis        0.9325 \u00b1     0.0696 \u00b1    0.0495 \u00b1    0.0120 \u00b1    0.0011 \u00b1    0.0144 \u00b1    0.0086 \u00b1    0.5733 \u00b1                   0.2040 \u00b1\n                               0.0083      0.0074     0.0002     0.0001     0.0001     0.0002     0.0002     0.0036                   0.0009\n\n        Second analysis      1.001 \u00b1     0.0751 \u00b1    0.0502 \u00b1    0.0121 \u00b1    0.0011 \u00b1    0.0144 \u00b1    0.0086 \u00b1    0.6012 \u00b1                   0.2051 \u00b1     0.0328 \u00b1\n                               0.0092      0.0079     0.0002     0.0001     0.0001     0.0002     0.0002     0.0040                   0.0011       0.0022\n\n          Third analysis        1.014 \u00b1     0.0763 \u00b1    0.0503 \u00b1    0.0121 \u00b1    0.0011 \u00b1    0.0144 \u00b1    0.0086 \u00b1    0.6061 \u00b1        0.0073 \u00b1   0.2053 \u00b1     0.0329 \u00b1\n                               0.0094      0.0081     0.0002     0.0001     0.0001     0.0002     0.0002     0.0040          0.0005   0.0011       0.0022\n\n\n\n       Table 16. Analysis of Binary Fluorides [All Analyses Performed with E0 = 10 keV and the K-L2,3 Peak (Na and Ca), L3-M4,5 Peak (Sr, Ba, and La), M5-N6,7 (Pr and Nd)].\n\n                          Fmean (Atom        RDEV        \u03c3 (Seven         Relative \u03c3        Metalmean (Atom       RDEV        \u03c3 (Seven            \u03c3Relative\n          Fluoride        Concentration)         (%)          Replicates)          (%)            Concentration)          (%)          Replicates)         (%)\n\n        NaF                0.5143               2.9          0.00069            0.13                0.4857             \u22122.9          0.00069           0.14\n\n         CaF2               0.6686               0.29         0.00074            0.11                0.3314             \u22120.57         0.00074           0.22\n\n          SrF2                0.6611            \u22120.83         0.00021           0.032               0.3389               +1.7          0.00021           0.062\n\n         BaF2               0.6527            \u22122.1          0.00152            0.23                0.3473               +4.2          0.00152           0.44\n\n         LaF3               0.7600               1.3          0.00283            0.37                0.2400             \u22124.0          0.00283            1.2\n\n          PrF3               0.7825               4.3          0.00267            0.34                0.2175          \u221213            0.00267            1.2\n\n        NdF3               0.7526               0.35         0.0139             1.8                 0.2474             \u22121.1          0.0139             5.6\n\n\n\n        relatively few materials of known composition with such major/    to 1,000:1, the k-ratio for the trace constituent is recovered with\n     minor  interferences on  trace  constituents  that can  serve  as   an RDEV of 26% for U in a Th-matrix and \u22129.4% for Th in a\n     unknowns to test the performance of peak fitting in such situa-   U-matrix. Figure 12 shows the spectra for the U-matrix with Th\n       tions. As an  alternative,  the \u201cspectrum  arithmetic\u201d  tools  in    additions. When Th  is not included in the peak fitting suite,\n     NIST DTSA-II can be used to create suitable synthesized compos-    the peak fitting residual spectra visually reveal the Th constituent\n        ite spectra from experimentally measured spectra. The synthe-   down to the 1% level. Figure 13 shows the same sequence for the\n       sized spectra are then subjected to peak fitting using different   Th-matrix with U additions, and again when U is not included in\n      experimentally measured spectra as peak references. Examples    the peak fitting suite, the peak fitting residual spectra visually\n       of such studies are presented in Table 24 for the interference of    reveal the U constituent down to the 1% level.\n      the Th M-family and the U M-family for which Th M4-N6\n      (3.146 keV) and U M5-N6,7 (3.165 keV) families are separated                                                                   \u201cStandardless\u201d Analysis\n      by 19 eV at photon energy where the EDS resolution is 99 eV.\n      For an intensity ratio of 100:1, the k-ratio for the trace constituent    \u201cStandardless\u201d analysis avoids the need to measure a standard\n         is recovered with an RDEV of 2% for U in a Th-matrix and \u22121.1%    intensity for the denominator of the k-ratio in equation (4) either\n       for Th in a U-matrix. When the relative intensity ratio is increased   by calculating an intensity from the equations of X-ray generation\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X     16                                                                                 Dale E. Newbury and Nicholas W.M. Ritchie\n\n\n      Table 17. Analysis of Binary Oxides (All Analyses Performed with E0 = 10 keV and the K-L2,3 Peak, except for Zn L3-M4,5 and Y L3-M4,5).\n\n                     Omean (Atom        RDEV        \u03c3 (Seven          Relative \u03c3        Metalmean (Atom       RDEV        \u03c3 (Seven             \u03c3Relative\n        Oxide        Concentration)         (%)          Replicates)          (%)            Concentration)          (%)          Replicates)          (%)\n\n      MgO             0.4966            \u22120.68          0.00064             0.13                0.5034              +0.67          0.00064            0.13\n\n         Al2O3            0.5905            \u22121.6           0.00039             0.07                0.4095              +2.4           0.00039            0.10\n\n        SiO              0.4989            \u22120.20          0.00033             0.07                0.5011              +0.20          0.00033            0.07\n\n        SiO2             0.6568            \u22121.5           0.00030             0.05                0.3432              +3.0           0.00030            0.09\n\n        TiO2             0.6702             +0.54          0.0011              0.16                0.3297             \u22121.1           0.0011             0.32\n\n        Cr2O3            0.5962            \u22120.64          0.0117              2.0                 0.4038              +0.95          0.0117              2.9\n\n        Fe2O3            0.5988            \u22120.20          0.00068             0.11                0.4012              +0.30          0.00068            0.17\n\n       Cu2O             0.3292            \u22121.2           0.00069             0.21                0.6708              +0.62          0.00069            0.10\n\n      CuO             0.5065             +1.30          0.0022              0.44                0.4935             \u22121.3           0.0022             0.45\n\n       ZnO             0.4905            \u22121.90          0.0058              1.2                 0.5095              +1.10          0.0058             1.10\n\n        Y2O3             0.5998            \u22120.04          0.00071             0.12                0.4002              +0.05          0.00071            0.18\n\n\n\n      Table 18. Analysis of Binary Nitrides [All Analyses Performed with E0 = 5 keV (ZrN at 10 keV); K-L2,3 Peak for B, Al, and Si; All others L-Family].\n\n                      Nmean (Atom        RDEV        \u03c3 (Seven         Relative \u03c3        Metalmean (Atom       RDEV        \u03c3 (Seven            \u03c3Relative\n         Nitride        Concentration)         (%)          Replicates)          (%)            Concentration)          (%)          Replicates)         (%)\n\n      BN                0.5202                4.0           0.0085              1.6                 0.4798            \u22124.0           0.0085             1.8\n\n        AlN               0.4784            \u22124.3           0.0024             0.50               0.5216                4.3           0.0024            0.46\n\n         Si3N4             0.5857              +2.5           0.0036             0.61               0.4143            \u22123.3           0.0036            0.86\n\n        TiN               0.5098              +2.0           0.0016             0.31               0.4902            \u22122.0           0.0016            0\n\n## 5. newbury2019electronexcitedxraymicroanalysis pages 16-18 (Context ID: pqac-00000045)\n\ntration)         (%)          Replicates)          (%)            Concentration)          (%)          Replicates)         (%)\n\n      BN                0.5202                4.0           0.0085              1.6                 0.4798            \u22124.0           0.0085             1.8\n\n        AlN               0.4784            \u22124.3           0.0024             0.50               0.5216                4.3           0.0024            0.46\n\n         Si3N4             0.5857              +2.5           0.0036             0.61               0.4143            \u22123.3           0.0036            0.86\n\n        TiN               0.5098              +2.0           0.0016             0.31               0.4902            \u22122.0           0.0016            0.32\n\n       VN                0.5118              +2.4           0.0051              1.0                 0.4882            \u22122.4           0.0051             1.0\n\n        Cr2N              0.3322            \u22120.33          0.0046              1.4                 0.6678              +0.17          0.0046            0.69\n\n        Fe3N              0.2573              +2.9           0.0069              2.7                 0.7427            \u22121.0           0.0069            0.93\n\n      GaN              0.4717            \u22125.7           0.0020             9.43               0.5283              +5.70          0.0020            0.38\n\n       ZrN               0.4959            \u22120.82          0.0033             0.66               0.5041               0.82          0.0033            0.65\n\n\n\n      Table 19. Analysis of Binary Carbides [Analyses Performed with the K-L2,3 Peak (E0 = 10 keV) or L-Family for Hf (E0 = 5 keV)].\n\n                                                  \u03c3 (Five or                                                   \u03c3 (Five or\n                     Carbonmean (Atom      RDEV          More           Relative \u03c3       Metalmean (Atom      RDEV          More               \u03c3Relative\n        Carbide        Concentration)         (%)          Replicates)          (%)           Concentration)         (%)          Replicates)          (%)\n\n         SiC            0.5112 \u00b1 0.3925           2.2           0.0004              0.07          0.4888 \u00b1 0.0002        \u22122.2           0.0004             0.07\n\n         TiC            0.4897 \u00b1 0.0477        \u22122.1           0.0008              0.16          0.5103 \u00b1 0.0005           2.1           0.0008             0.16\n\n       VC             0.4963 \u00b1 0.2517        \u22120.7           0.0017              0.33          0.5037 \u00b1 0.0006           0.7           0.0017             0.33\n\n         Cr3C2          0.3925 \u00b1 0.2127        \u22121.9           0.0029              0.73          0.6075 \u00b1 0.0008           1.3           0.0029             0.47\n\n         Cr7C3          0.2960 \u00b1 0.1608        \u22122.0           0.0097              3.3           0.7059 \u00b1 0.0009          0.84          0.0098              1.4\n\n         Cr23C6         0.2086 \u00b1 0.1143          0.82          0.0057              2.7           0.7914 \u00b1 0.0010          0.21          0.0057             0.72\n\n        Fe3C           0.2531 \u00b1 0.1572           1.2           0.00073            0.29          0.7469 \u00b1 0.0015          0.41          0.00073            0.10\n\n        HfC            0.4742 \u00b1 0.0121        \u22125.2           0.00272            0.57          0.5258 \u00b1 0.0006           5.2           0.00272            0.52\n\n\n\n    and propagation (\u201cfirst-principles\u201d method) or by using a library    fluorescence yield, especially for L- and M-shell X-rays. Since\n      of remotely measured standards (\u201cremote standards\u201d method)    the remote standards method  is tied to measurements of real\n     (Goldstein  et  al., 2018). The accuracy  of the  first-principles    materials, it is inherently more accurate and is a good compro-\n    method is limited by the lack of accurate values for critical phys-   mise between first-principles standardless analysis and locally col-\n       ical parameters such as the ionization cross section and the    lected standards-based analysis. However, the user is often left\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X      Microscopy and Microanalysis                                                                                          17\n\n\n       Table 20. Analysis of Binary Borides (All Analyses Performed with E0 = 5 keV; B K-L2,3 Peak, C K-L2,3 Peak, Ti and Cr L-Family, and La M-Family Peaks).\n\n                                                  \u03c3 (Five or                                                    \u03c3 (Five or\n                      Boronmean (Atom      RDEV          More            Relative \u03c3       Metalmean (Atom       RDEV          More               \u03c3Relative\n         Boride        Concentration)         (%)          Replicates)          (%)           Concentration)         (%)          Replicates)          (%)\n\n         B4C           0.7744 \u00b1 0.1104        \u22123.2           0.0033              0.43           0.2256 \u00b1 0.1240       13              0.0033              1.5\n\n          TiB2          0.6609 \u00b1 0.1887        \u22120.87          0.0043              0.65           0.3391 \u00b1 0.0003         1.7             0.0043              1.3\n\n         CrB2          0.6552 \u00b1 0.5276        \u22121.7           0.00092             0.14           0.3448 \u00b1 0.0034         3.5             0.00092            0.27\n\n         CrB           0.4913 \u00b1 0.4563        \u22121.7           0.0055               1.1            0.5087 \u00b1 0.0028         1.7             0.0055              1.1\n\n         Cr2B          0.3362 \u00b1 0.3283          0.86          0.0047               1.4            0.6638 \u00b1 0.0026       \u22120.42          0.0047             0.70\n\n         LaB6          0.8702 \u00b1 0.2183           1.5           0.00063             0.07           0.1298 \u00b1 0.0012      \u22129             0.00063            0.49\n\n\n\n\n\n         Fig. 9. (a) EDS spectrum of BaCl2 at E0 = 5 keV; note the extended Ba M-family. (b) EDS spectrum (red) of YBa2Cu3O7\u2212x at E0 = 5 keV and the peak fitting residual\n       spectrum (blue).\n\n\n\n\n       Table 21. Analysis of YBa2Cu3O7 at E0 = 5 keV. O (Y2O3 Standard and Reference); Cu (Standard and Reference); Y (Y2O3 Standard and Reference); Ba (BaF2 Standard\n      and BaCl2 Reference), Values in Normalized Mass Concentration; Combined Uncertainties as Estimated from NIST DTSA-II.\n\n                         Raw Analytical Total (Mass         O (Mass             Cu (Mass                Y (Mass              Ba (Mass\n         Parameter                    Concentration)               Concentration)           Concentration)           Concentration)           Concentration)\n\n\n        Mean                  1.026                                    0.1627                  0.2983                   0.1248                  0.4143\n\n          Ideal                                                          0.1681                  0.2862                   0.1335                  0.4123\n\n        RDEV (%)                                                  \u22123.2                        4.2                   \u22126.5                        0.5\n\n        \u03c3 (five replicates)                                               0.0022                  0.0040                   0.0019                  0.0076\n\n        \u03c3 relative (%)                                                       1.3                        1.3                        1.5                        1.8\n\n        Combined                                                       \u00b10.0013,                  \u00b10.0052,                  \u00b10.0004,                  \u00b10.0053,\n          uncertainty                                              \u00b10.8%                 \u00b11.7%                \u00b10.32%                \u00b11.3%\n\n\nDownloaded from https://www.cambridge.org/core. the NIST Virtual Library (NVL), on 23 Aug 2019 at 13:33:09, subject to the Cambridge Core terms of use, available at\nhttps://www.cambridge.org/core/terms. https://doi.org/10.1017/S143192761901482X     18                                                                                 Dale E. Newbury and Nicholas W.M. Ritchie\n\n\n\n\n\n        Fig. 10. EDS spectrum of NIST microanalysis glass K523 (E0 = 20 keV): upper, 0\u201315 keV; lower, 0\u201310 keV with an expanded intensity axis.\n\n\n     guessing how vendors implement their \u201cstandard-less quantifica-    corrected. One method is to use a \u201cgolden detector\u201d calibrated\n      tion\u201d because they have typically not provided the customer with    at a beamline and a carefully chosen reference material to trans-\n     adequate documentation on what is actually being done to derive    fer the calibration from the golden detector to others (Alvisi\n     numerical concentrations.                                                et al., 2006).\n       The remote standards library is populated with characteristic       Standardless analysis requires only\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045]\n\nStatus: Paper Count=23 | Relevant Papers=14 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=46 | Current Cost=$0.2376 | Disease-Target Evidence=0",
+                "name": "read_text",
+                "tool_call_id": "toolu_014Vv5PkK6B2RGN1hC6sSaDS",
+                "info": {
+                  "start_ts": 2919.501040849,
+                  "end_ts": 2934.070308387
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me read the dead-time model more carefully and search for the Donovan dead time paper and more Goldstein:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01UCKP9WxxM8PsBoLzYdzVrc",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"text_name_list\": [\"goldstein2018energydispersivexray pages 9-10\", \"donovan2023anewmethod pages 2-3\", \"donovan2023anewmethod pages 3-4\", \"donovan2023anewmethod pages 4-5\"]}",
+                      "name": "read_text"
+                    }
+                  },
+                  {
+                    "id": "toolu_01GLLGDKo7sADfUGLPZF3SS8",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"question\": \"What is the Bethe ionization cross-section formula? How does ionization cross-section Q vary with overvoltage U = E0/Ec? Where is the maximum of the ionization cross-section and why does it determine the optimal accelerating voltage? What is the Kanaya-Okayama electron range equation?\"}",
+                      "name": "gather_evidence"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "## 1. goldstein2018energydispersivexray pages 9-10 (Context ID: pqac-00000046)\n\n Level of System Dead-Time\nbins will define an X-ray peak. Since the peak width is a func-   X-rays are generated randomly in time with an average rate\ntion of photon energy, as described by Eq. (16.2), decreasing  determined by the flux of electrons striking the specimen,\nfrom approximately 129 eV at Mn K-L3 (5.895 keV) to   thus scaling with the incident beam current. As discussed\napproximately 50 eV FWHM for C K-L2 (0.282 keV), a selec-   above, the EDS system can measure only one X-ray photon at\ntion of a 5-eV bin width is a useful choice to optimize peak   a time, so that it is effectively unavailable if another photon\nfitting since this choice will provide 10 channels across C   arrives while the system is \u201cbusy\u201d measuring the first photon.\nK-L2. The number of bins that comprise the spectrum multi-  Depending on the separation in the time of arrival of the sec-\nplied by the bin width gives the energy span. It is useful to  ond photon, the anti-coincidence function will exclude the\ncapture the complete energy spectrum from a threshold of  second photon, but if the measurement of the first photon is\n0.1 keV to the incident beam energy, E0. Thus, to span   not sufficiently advanced, both photons will be excluded\n0\u201320 keV with 5 eV bins requires 4096 channels.            from the measurement and effectively lost. Due to this pho-\n                                                        ton loss, the output count rate (OCR) in counts/second of the\nChoosing the Solid Angle of the EDS                                                              detector will always be less than the input count rate (ICR).\nThe solid angle \u03a9 of a detector with an active area A at a dis-  The relation between the OCR and ICR is shown in .\u2003 Fig. 16.9\ntance r from the specimen is                                    for a four-detector SDD-EDS. An automatic correction func-\n                                                              tion measures the time increments when the detector is busy\n    W = A / r 2                                           (16.4)   processing photons, and to compensate for possible photon\n                                                                    loss during this \u201cdead-time,\u201d additional time is added at the\n                                                          conclusion of the user-specified measurement time so that all\n\n. .\u200a\u200a\u200aFig. 16.9\u2003  Output count rate\nversus input count rate for a four-                               Quad SDD (medium peaking time)\ndetector SDD-EDS\n                                       1,000,000                                                               80\n                                  Mn\n                           OCR           E0 = 20 keV\n                                                                                                         70                                      SDD 470 ns\n                                                shaping                                       800,000\n                                                time\n                                                                                                         60\n                                                                                           Single SDD\n                                                                 Maximum = 130 kcps\n                                                                                                         50\n                                       600,000                                550 kHz\n                                                                       (c/s)\n                                                         rate                                                 127.5 eV at MnK\u03b1              40                                                                                                                                                                                                                                                                                                                                                                                                         Deadtime\n                                       400,000                                                                       Count                                                ICR (c/clock-s)                  30\n\n                                                                 OCR (Medium)\n                                                                                                         20\n                                       200,000\n                                                                            Deadtime\n                                                                                                         10\n                                                         Single SDD chip: maximum output ~ 130 kHz\n\n                                         0                                                               0\n                                           0       500 kHz     1MHz        1.5 MHz    2 MHz    2.5 MHz\n                                                                              Input count rate           218    Chapter 16 \u00b7 Energy Dispersive X-ray Spectrometry: Physical Principles and User-Selected Parameters\n\n\n         measurements are made on the basis of the same \u201clive-time\u201d  time over the full dead-time range to 80\u2009% or higher. (Note\n          so as to achieve constant dose for quantitative measurements.   that as a component of a quality measurement system, the\n         The level of activity of the EDS is reported to the user as a  dead-time  correction  function  should  be  periodically\n          percentage \u201cdead-time\u201d:                                  checked by systematically changing the beam current and\n                                                             comparing the measured X-ray intensity with predicted.)\n                                                                          (16.5)  However, as the dead-time increases and the arrival rate of               Deadtime ( % ) = \uf8ee\uf8f0 ( ICR \u2212 OCR ) / ICR \uf8f9\uf8fb\u00d7 100%\n                                                                   X-rays at the EDS increases, coincidence events become\n         Dead-time increases as the beam current increases. The   progressively more prominent. This effect is illustrated in\n         dead time correction circuit can correct the measurement   .\u2003 Fig. 16.10 for a sequence of spectra from a glass with six\n\n\n\n               140 000                                             K412\n                                                                             E0 = 20 keV                  K412 (mass frac)\n               120 000                                   7% deadtime             O            0.428\n                                                                       Mg          0.117\n               100 000                                                                                        Al           0.0491\n                                                                                                                                     Si           0.212\n                80 000                                                                      Ca           0.109                                  Counts                                                                                                  Fe           0.0774\n\n                60 000\n\n\n                40 000\n\n\n                20 000\n\n\n                    0\n                      0                   2                  4                  6                   8                  10\n                                                           Photon energy (keV)\n\n\n                                             Coincidence               Coincidence\n               14 000                                           peaks                    peaks\n\n\n\n\n                   K16           12 000\n                                                                                            K-L                               V        CrK-L                                       NaK                          SiK+O\n               10 000                                                                                                   not                                       not                         2MgK     2AlK   2SiK               not\n             K                                                                 K412 (mass frac)\n                8 000       2O\n                                         20DT                                     O           0.428                                  Counts\n                                                                           Mg          0.117                                                                                                                                                                                                                       \n\n## 2. donovan2023anewmethod pages 3-4 (Context ID: pqac-00000047)\n\ne values of our dead time constants when utilizing\nsion which should be utilized if count rates exceed 100 to                                                                      of\n                                                                 these more precise dead time models, to account for improved\n200 kcps (depending on the exact value of the dead time con-\n                                                        modeling of these nonlinear effects at higher count rates.\nstant). This new expression is again merely an extended form\n                                                                  Typically, this means slightly lowering the dead time constants\nof this Maclaurin like expansion series as shown here, with an                                                        a few hundredths of a \u03bcs as discussed below. This is a tiny nu-                     Wisconsin\nadditional four terms of the series to further improve modeling                                   -\n                                                              merical change which is essentially invisible at low to moder-\nof these nonlinear dead time effects (further increasing the\n                                                                  ate count rates. The appropriate dead time values to be used\nnumber of terms has essentially little to no effect even at these                                                          with these more precise dead time models should be obtained                Madisonhigh count rates):\n                                                              using                                                                     the dead                                                                          time                                                                                       calibration                                                                                methods                                                                                                       as                                                                                                               detailed                                                                                                                bellow.\n                                                       At even                                                                        higher                                                                         count                                                                                            or 400                                                                                                        kcps,                                                                                                   depending                                                                                                on         user                                                                                             rates (>300                                            icps\n                                      \udbff\udf13Icps =   \udbff\udf12                                                                the hardware specifics) these nonlinear effects come to domin-     on                                    \u03c43        \u03c44     1 \u2212   icps \u00b7\u03c4 +i2cps \u00b7\u03c42 + i3cps \u00b7  + i4cps \u00b7  +i5cps \u00b7\u03c45 +i6cps \u00b7\u03c46       ate the pulse processing electronics, and the dead time correc-     17                  2      3      4      5      6\n                                                                  tion becomes extremely sensitive to the exact value of the dead       May                                                              (3)                                                            time constant utilized. For example, some instruments multi-\nSuch high count rates are quite readily obtained at even mod-    plex the pulse pileup processing from multiple spectrometers         2023\nerately high beam currents when utilizing modern instruments     into a single circuit, while other electronic processing delays\nwith large area Bragg diffraction crystals with strong emission    can become more relevant when pulse streams approach the\nlines. Though in fact, this extended form of the dead time cor-    frequency of the response time in the processing electronics.\nrection expression can still be utilized at low and moderate      Regardless of pulse processing limitations, it might be ap-\ncount rates to correct for simple photon coincidence because    propriate to utilize an even more radical mathematical model\nthese high-order terms are all close to zero at low to moderate    such as the exponential expression proposed by Schiff (1936)4                                                                      Microscopy and Microanalysis, 2023, Vol. 00, No. 0\n\n\nTable 2. Calculated Count Rates Using All 4 Dead Time Expressions at a 1.5 \u03bcs Assumed Dead Time Constant where \u201c1t\u201d = Traditional Linear Expression,\n\u201c2t\u201d = Willis et al. (1993), \u201c6t\u201d = Six-Term Expansion, and \u201cnt\u201d = Logarithmic Expression. The \u201cObserved\u201d Count Rate is the Recorded Count Rate as it\nwould be Measured in an Actual Instrument After Pulse Processing. The \u201cPredicted\u201d Count Rate is the Theoretical Count Rate as it would be upon\nEntering the Detector Before any Pulse Processing.\n\nobsv cps         1t pred        1t obs/pre        2t pred        2t obs/pre         6t pred        6t obs/pre         nt pred        nt obs/pre\n\n0           0            0            0            0            0            0            0            0\n10,000       10,152.28      0.985          10,153.44      0.984888       10,153.46      0.984886      10,153.46      0.984886\n20,000       20,618.56      0.97           20,628.13      0.96955        20,628.32      0.969541      20,628.32      0.969541                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     Downloaded30,000       31,413.61      0.955          31,446.95      0.953988       31,447.99      0.953956      31,447.99      0.953956\n40,000       42,553.19      0.94           42,634.83      0.9382         42,638.26      0.938125      42,638.26      0.938125             from\n50,000       54,054.05      0.925          54,218.91      0.922188       54,227.67      0.922039      54,227.67      0.922039\n60,000       65,934.06      0.91           66,228.82      0.90595        66,247.88      0.905689      66,247.88      0.905689\n70,000       78,212.29      0.895          78,697         0.889,488      78,734.09      0.889069      78,734.09      0.889069\n80,000       90,909.09      0.88           91,659.03      0.8728         91,725.59      0.872167      91,725.59      0.872167\n90,000       104,046.2      0.865         105,154       0.855888       105,266.3      0.854974      105,266.3      0.854974\n100,000      117,647.1      0.85          119,225       0.83875        119,405.6      0.837481      119,405.7      0.837481\n110,000      131,736.5      0.835          133,919.7      0.821388       134,199.2      0.819677      134,199.3      0.819676\n120,000      146,341.5      0.82           149,290.9      0.8038         149,709.9      0.80155        149,710.1      0.801549\n130,000      161,490.7      0.805         165,397       0.785988       166,009.3      0.783089      166,009.7      0.783087\n140,000      177,215.2      0.79           182,303.5      0.76795        183,178.8      0.764281      183,179.5      0.764278\n150,000      193,548.4      0.775          200,083.4      0.749688       201,311.8      0.745113      201,313.2      0.745108\n160,000      210,526.3      0.76           218,818.4      0.7312         220,515.8      0.725572      220,518.4      0.725563\n170,000      228,187.9      0.745          238,600.7      0.712488       240,915.4      0.705642      240,919.8      0.705629\n180,000      246,575.3      0.73           259,534.3      0.69355        262,655.3      0.685309      262,662.8      0.685289\n190,000      265,734.3      0.715          281,737.1      0.674388      285,905       0.664556      285,917.5      0.664527\n200,000      285,714.3       0.7            305,343.5      0.655          310,864.3      0.643368      310,884.8      0.643325\n210,000      306,569.3      0.685         330,507       0.635388       337,770.3      0.621724      337,803.3      0.621664\n220,000      328,358.2      0.67          357,404       0.61555        366,906.3   \n\n## 3. donovan2023anewmethod pages 2-3 (Context ID: pqac-00000048)\n\nn and processing effects, all of which fall under the general    of an exactly rectilinear pulse shape and constant dead time      by\nterm of dead time, and that we properly correct for these ef-     relative to the count rate, the traditional dead time expression\nfects to allow for accurate quantitative analyses over a wide      is limited to input count rates up to \u223c50 kcps; a region in\nrange of count rates.                                     which the dead time pulse processing effects are minimal com-                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     University\n                                                          pared to the average time between the pulses and yield a fairly                                                                                                                                    of\n                                                                     linear response with beam current. However, as the pulses be-\nThe Linear Dead Time Expression\n                                                                gin to overlap in time at sufficiently high count rates due to the\nThe traditional form of the dead time expression is commonly                                                               imperfect pulse shapes as observed in typical pulse processing\nnotated as                                                                    electronics (Geller & Herrington, 2002), at count rates higher                           Wisconsin-\n                                            icps                           than \u223c50 kcps, these nonideal pulse shapes begin to become\n                            Icps =                                 (1)     similar to the average time between photon pulses and there-                      1 \u2212(icps \u00b7 \u03c4)                                                                       fore, start to impact the accuracy of the traditional dead                     Madison\nwhere: Icps is the dead time corrected (predicted) count rate in    time model. In addition, it is possible that the assumption of\ncps, \u03c4 is the dead time constant in seconds, and icps is the raw    a constant dead time interval at higher count rates is not per-            user\n(observed) count rate in cps.                                         fectly valid (i.e., an extending dead time constant) (Beaman &      on\n  This classic linear expression (Goldstein et al., 1992, Ruark    Solosky, 1972). We therefore must precisely characterize these      17\n& Brammer, 1937, p. 289) has been utilized for decades for    nonlinear dead time artifacts to improve modeling for accur-         May\nthe correction of observed WDS intensities. It is also tradition-     ate quantitative analysis at these higher count rates.\nally used for determination of the WDS dead time constants.       In addition to the above considerations, the linearity of the            2023\nThis equation considers the mathematical probability of a    picoammeter is also critical for accurate estimates of raw or\nphoton coincident within the dead time interval of the spec-    \u201cobserved\u201d count rate versus beam current as utilized in trad-\ntrometer system with an initial incident photon. The equation     itional  determinations  of dead  time  constants.  In  fact,\nfurther assumes that the photon pulse shape is mathematically    Heinrich et al. (1966) proposed a \u201cratio\u201d method for the de-\nrectilinear and that the dead time interval is constant as a func-    termination of dead time that was based on the measurement\ntion of count  rate. In  fact, with these assumptions, the    of simultaneous K\u03b1 and K\u03b2 emissions on two spectrometers,John J. Donovan et al.                                                                                             3\n\n\nthereby eliminating any nonlinearity of the picoammeter.   EPMA count rates. Furthermore, hardware and electronics\nHowever, the Heinrich \u201cratio\u201d method still assumes a linear    pulse processing limitations at extremely high count rates\nresponse of the pulse processing system which is problematic.     will generally restrict the application of these extended expres-\nWe therefore propose a new nonlinear expression for an im-    sions long before reaching their mathematical limits, e.g.,\nproved software correction of WDS intensities for dead time   when the product of count rate and dead time exceed 1 for\neffects. In addition, we also propose a new method for deter-    both the traditional linear and expanded nonlinear expres-\nmining the accuracy of our dead time constants, which utilizes     sions. However, in practice, the six-term expanded expression\nthe ratio of two intensities from two materials, which we call    (Eq. (3)) is applicable to trace, minor and major element WDS                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              Downloaded\nthe \u201cconstant k-ratio\u201d method. Simply because the traditional    microanalysis from low count rates to count rates up to ap-\nWDS k-ratio should (ideally) remain constant as a function of    proximately 300 to 400 kcps depending on the actual dead         from\nbeam current, if the dead time correction is being properly ap-    time constants of the particular EPMA hardware.\nplied in software.                                               Thankfully, we can greatly simplify this expression by rec-\n                                                              ognizing the Maclaurin series of ln(1 \u2212 x), where ln denotes\n                                                                the natural logarithm:\nExpressions for Nonlinear Dead Time Correction\nA significant improvement in dead time correction accuracy at                  ln(1 \u2212x) \u2248\u2212x \u2212x2 \u2212x3 \u2212x4 \u2212. . .\nthese higher count rates has been described by the use of an                           2   3   4\nadditional term in the traditional linear expression as shown    and with x = \u03c4 \u00b7 icps:\nhere from Willis et al. (1993).\n                                                                                                           \u03c42 \u00b7 i2cps   \u03c43 \u00b7 i3cps   \u03c44 \u00b7 i4cps\n                                            icps                                 ln(1 \u2212\u03c4 \u00b7 icps) \u2248\u2212\u03c4 \u00b7 icps \u2212     \u2212     \u2212      \u2212. . .\n                     Icps =   \udbff\udf12         \udbff\udf13               (2)                           2      3      4\n                                               \u03c42\n                 1 \u2212   icps \u00b7 \u03c4 + i2cps \u00b7                        hence, we have:                                2\n                                                                                                                                       icps\nThis nonlinear expression was originally developed for calcu-                              Icps =                                    (4)\n                                                                      1 + ln(1 \u2212\u03c4 \u00b7 icps)lating work function \u201cdead time\u201d for training of early neural\nnetworks but has now been applied to microanalysis and    With this logarithmic expression, we can correct for not only\nfound useful for correction of observed count rates up to    photon coincidence at low to moderate count rates but also at\nroughly 100 kcps, as we will demonstrate below. These are    higher input count rates for nonlinear response of the WDS de-\ncount rates often encountered when using moderate to high     tectors and pulse processing electronics for improved accuracy\nbeam currents and/or when dead time constants are larger                                                                    at high beam currents, which have been previously impractical\nthan 2 \u00b5s. This Willis expression has been sufficient for most                                                                  for quantitative analysis. Once again, all of these new expres-\nEPMA work  until the rece\n\n## 4. donovan2023anewmethod pages 4-5 (Context ID: pqac-00000049)\n\n  0.725572      220,518.4      0.725563\n170,000      228,187.9      0.745          238,600.7      0.712488       240,915.4      0.705642      240,919.8      0.705629\n180,000      246,575.3      0.73           259,534.3      0.69355        262,655.3      0.685309      262,662.8      0.685289\n190,000      265,734.3      0.715          281,737.1      0.674388      285,905       0.664556      285,917.5      0.664527\n200,000      285,714.3       0.7            305,343.5      0.655          310,864.3      0.643368      310,884.8      0.643325\n210,000      306,569.3      0.685         330,507       0.635388       337,770.3      0.621724      337,803.3      0.621664\n220,000      328,358.2      0.67          357,404       0.61555        366,906.3      0.599608      366,958.8      0.599522\n230,000      351,145        0.655          386,238.2      0.595488      398,614       0.576999      398,696.5      0.57688\n240,000      375,000        0.64           417,246.2      0.5752         433,309.3      0.553877      433,437.6      0.553713\n250,000      400,000        0.625          450,704.3      0.554687       471,503.4      0.530219      471,701.4      0.529996\n260,000      426,229.5      0.61          486,937       0.53395        513,831.5      0.506002      514,135.1      0.505704\n270,000      453,781.5      0.595          526,328.6      0.512988       561,093.4      0.481203      561,556.9      0.480806\n280,000      482,758.6      0.58           569,337.1      0.4918         614,309.8      0.455796      615,015.9      0.455273\n290,000      513,274.3      0.565         616,513       0.470388       674,804.8      0.429754      675,879.8      0.42907\n300,000      545,454.6      0.55           668,523.7      0.44875        744,326.6      0.403049      745,966.3      0.402163\n\n\n\n\nfor extending dead times. Such an expression can be solved for    begins to diverge, and above 200 kcps, the six-term or loga-\nIcps by using the Lambert W-function which can be numerical-    rithmic expressions deviate even further. Though it must bely evaluated. Unfortunately, this exponential expression is    noted that for quantitative analysis, the sensitivity of these                                                                                                                                                                                                                                                https://academic.oup.com/mam/advance-article/doi/10.1093/micmic/ozad050/7165464\nquite limited in practice, in that the product of the dead time    graphical plots for predicted versus observed count rates is in-      by\nand count rate cannot exceed 1/e. This mathematically limits     sufficient for properly evaluating these various expressions, as\nits application to count rates of 245 kcps or less at 1.5 \u03bcs   we will discuss further below.\nand 123 kcps or less at dead times of 3 \u03bcs. Therefore, it is      For an instrument with roughly twice this dead time con-                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     University\nnot considered further in this paper.                              stant (typical of Cameca instruments), these corrections are                                                                                                                                    of\n                                                          even more significant. Assuming a dead time constant of\n                                              \u223c3 \u03bcs, we obtain the following plot as seen in Figure 3 which,\nDiscussion of the Various Dead Time Expressions      though limited to 200 kcps observed count rates, looks muchThe predicted count rates from each of the four dead time cor-    the same as the 1.5 \u03bcs plot from Figure 2 which utilizes ob-                           Wisconsin-\nrection expressions, i.e., traditional (Eq. (1)), Willis two-term    served count rates to 400 kcps. In other words, the predicted\n(Eq.  (2)), six-term expansion (Eq.  (3)), and logarithmic    count rates in Figure 3 are almost the same as Figure 2 yet(Eq. (4)) are shown in Table 2 to identify the mathematical    with only half the input count rates. Hence, the typically high-                     Madison\n                                                                    er dead                                                                   time                                                                           constants                                                                                      of Cameca                                                                                            instrument                                                               WDS spectrom-(modeled)           differences                   between                               the various                                           expressions                                              and\n                                                                          lose                                                                     accuracy                                                                                             faster                                                                                                                                  if not properly                                                                                                             corrected,                                                                                               and the            usercan be examined                 graphically                            as shown                                         in Figure                                                  1, where                                         we     eters\ncan see the dead time corrected theoretical (predicted) inten-    six-term and logarithmic expressions appear to start deviating      on\nsities for recorded (observed) intensities up to 300 kcps with    from the traditional expression above \u223c100 kcps input count      17\na nominal dead time constant of 1.5 \u03bcs.                             rates.                                                                                            May\n  Note that the six-term expression plots underneath the loga-       In addition, the gas detector itself can contain other laten-\nrithmic expression and is not visible in this plot, but which can     cies, for example, the time for the bias voltage to return to            2023\nbe better resolved by plotting the observed count rate up to    nominal while the gas ionization is neutralized. When the\n400 kcps as seen in Figure 2. On an instrument with \u223c1.5 \u03bcs    count rate increases to a time comparable to the duration of\ndead times (typical of JEOL instruments) and up to about    the gas ionization interval, the detector will undergo \u201cparalyz-\n200 kcps, the traditional dead time expression appears to per-    ing\u201d behavior, and the observed count rate drops to zero.\nform similarly. But above that count rate (or with higher dead   Though this gas ionization time constant appears to relatively\ntime constants), the Willis et al. (1993) two-term expression     insignificant until count rates over 500 to 1,000 kcps areJohn J. Donovan et al.                                                                                             5\n\n                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              Downloaded\n                                                                                                                                                                                                                                                                      from\n\n\n\n\n\nFig. 1. Plotting all four dead time correction expressions at a dead time of 1\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049]\n\nStatus: Paper Count=23 | Relevant Papers=15 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=50 | Current Cost=$0.2376 | Disease-Target Evidence=0",
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+                "content": "No relevant evidence found for your question.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049]\n\nStatus: Paper Count=23 | Relevant Papers=15 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=50 | Current Cost=$0.2725 | Disease-Target Evidence=0",
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+                "content": "Let me search for the specific Bethe/Powell paper and the Rinaldi review more carefully:",
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+                      "arguments": "{\"query\": \"Powell Llovet Salvat Bethe equation inner-shell ionization electron impact overvoltage dependence\"}",
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+                "content": "Search retrieved no additional papers. This may be because nothing matched the search query, or because all found papers have been previously retrieved.\n\nUnobtainable Papers:\nDavid Bote and Francesc Salvat. Calculations of inner-shell ionization by electron impact with the distorted-wave and plane-wave born approximations. Physical Review A, 77:042701, Apr 2008. URL: https://doi.org/10.1103/physreva.77.042701, doi:10.1103/physreva.77.042701.\nMathias Procop and Ralf Terborg. Measurement and calculation of x-ray production efficiencies for copper, zirconium, and tungsten. Dec 2022. URL: https://doi.org/10.1017/s1431927622012351, doi:10.1017/s1431927622012351.\nXavier Llovet, Claude Merlet, Jos\u00e9 M. Fern\u00e1ndez-Varea, and Francesc Salvat. Relative cross sections for l- and m-shell ionization by electron impact. Microchimica Acta, 132:163-171, Apr 2000. URL: https://doi.org/10.1007/s006040050058, doi:10.1007/s006040050058.\nR. Mayol and F. Salvat. Cross sections for k-shell ionisation by electron impact. Journal of Physics B, 23:2117-2130, Jun 1990. URL: https://doi.org/10.1088/0953-4075/23/12/020, doi:10.1088/0953-4075/23/12/020.\nE. Acosta, X. Llovet, E. Coleoni, J. A. Riveros, and F. Salvat. Monte carlo simulation of x-ray emission by kilovolt electron bombardment. Journal of Applied Physics, 83:6038-6049, Oct 1998. URL: https://doi.org/10.1063/1.367473, doi:10.1063/1.367473.\nAur\u00e9lien Moy and John Fournelle. <i>\u03d5</i>(<i>\u03c1z</i>) distributions in bulk and thin film samples for epma. part 1: a modified <i>\u03d5</i>(<i>\u03c1z</i>) distribution for bulk materials, including characteristic and bremsstrahlung fluorescence. Microscopy and Microanalysis, 27:266-283, Feb 2021. URL: https://doi.org/10.1017/s1431927620024915, doi:10.1017/s1431927620024915.\nFrancesc Salvat, Jos\ufffd M. Fernnndez-Varea, and Xavier Llovet. Monte carlo simulation of electron transport and x-ray generation. i. electron elastic and inelastic scattering. Apr 2004. URL: https://doi.org/10.1007/s00604-003-0153-7, doi:10.1007/s00604-003-0153-7.\nNicholas W.M. Ritchie. Spectrum simulation in dtsa-ii. Microscopy and Microanalysis, 15:454-468, Sep 2009. URL: https://doi.org/10.1017/s1431927609990407, doi:10.1017/s1431927609990407.\nRaynald Gauvin. What remains to be done to allow quantitative x-ray microanalysis performed with eds to become a true characterization technique? Microscopy and Microanalysis, 18:915-940, Oct 2012. URL: https://doi.org/10.1017/s1431927612001468, doi:10.1017/s1431927612001468.\nZihang Zhang, Bo Da, Jiamin Gong, and Z. J. Ding. Calculation of backscattering correction factors in aes for compounds: unraveling matrix effects. Journal of Applied Physics, Aug 2026. URL: https://doi.org/10.1063/5.0342873, doi:10.1063/5.0342873.\nFrancesc Salvat, Laia Barjuan, and Pedro Andreo. Inelastic collisions of fast charged particles with atoms: bethe asymptotic formulas and shell corrections. Physical Review A, Apr 2022. URL: https://doi.org/10.1103/physreva.105.042813, doi:10.1103/physreva.105.042813.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052]\n\nStatus: Paper Count=23 | Relevant Papers=15 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=53 | Current Cost=$0.2725 | Disease-Target Evidence=0",
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+                "content": "## 1. rinaldi2015electronprobemicroanalysis pages 2-4 (Context ID: pqac-00000050)\n\n a world of\nlarge data sets needed for such projects.                       innovation in electron microprobe analysis, so much so\n   Upon returning to my Alma Mater, the University of     that it became dif\ufb01cult to keep the pace of automation and\nModena, a few years later (in 1975), I was charged with the    software development with the existing hardware, still cap-\nresponsibility of running the \ufb01rst automated and computer-    able of excellent performance as to both wavelength (WDS)\ncontrolled electron microprobe in Italy, and I dedicated the    and energy (EDS) dispersive systems.\nnext 10 years or so to the probe lab and to promoting       Those were the years when the study of minerals and\nthe self-catering access to EPMA after training colleagues    rocks received an impulse comparable with that caused,\nand students from all over Italy (Rinaldi, 1978, 1979, 1980,   some 120 years earlier, by the introduction of the polarizing\n1981, 1985).                                                 petrographic microscope for the study of rocks in thin\n   The moon-shot technological jump had also had  its     sections. This is also testi\ufb01ed by the peak that occurred in the\nimpact on EPMA technology, and a totally new generation of    discovery of new minerals. Thanks to the micro-analytical                                                                                                Electron Probe Microanalysis  1055\n\n\n\n\n\n        Figure 2. A more modern American microprobe of the mid-1970s (ARL-SEMQ), at the beginning of computer con-\n          trolled automaton. Note the Programmable Data Processor of the Digital Equipment Corporation next to the printer.\n        There is no computer video display. Note the dual cathode ray tube screens\u2014one for photos (slow scan) and the other\n          for visual inspection, capable of TV scan mode (courtesy of Fritz Priziwarra).\n\n\ncapabilities, many new phases, generally crystallized as small      Raymond was recounting the story of when, during his\ngrains, could be fully characterized. Just looking at my own   PhD thesis work, under the supervision of Professor Andr\u00e9\ndirect experience, eight new minerals were discovered in    Guinier some 32 years before (Castaing, 1951), he was faced\nthose years at my laboratory alone [mazzite, merlinoite,    with great dif\ufb01culties and a good dose of skepticism while\namicite, saneroite, cascandite, jervisite, katoite, and wake-     trying to obtain a measurable X-ray signal with Guinier\u2019s\n\ufb01eldite-(Ce)]. This means that the 300 or so probe labs in    spectrometer from the primary excitation of a stationary\nEarth Science research establishments around the world    electron beam impinging on a metal sample in an electro-\nincreased the number of known natural species of minerals     static transmission electron microscope (TEM) adapted for\nby many hundreds, something like 1/3 more of all species of     that purpose. His gut feelings at the time were rather mixed,\nminerals known until then.                              and he recounted that many times he got totally discouraged.\n   The large throughput of accurate analytical data also    Despite that, he carried on improving the set-up until he\nmade it possible to undertake projects of systematic crystal-   managed to make his supervisor (and himself) quite happy\nchemical studies of complex isomorphic  series of rock-     in the end. Incidentally, Andr\u00e9 Guinier was also sitting at\nforming minerals (feldspars, pyroxenes, amphiboles, spinels,     that same dinner table and found Raymond\u2019s description of\netc.); thereby, vastly extending the knowledge of petrogenetic    those early days quite amusing. After dinner, I had the\nfactors underlying the dynamics of the Earth\u2019s interior. The    courage to go up to Professor Guinier and ask for his auto-\nneed and desire to \ufb01nd all possible nuances in the very rare    graph on the book of abstracts, which he was happy to sign\nand precious moon rock samples induced  scientists  to     for me; a very fond memory to be recalled in this year, the\nundertake very detailed investigations on terrestrial minerals    centennial of X-ray crystallography, of which Guinier had\nand rocks. This way, the lunar exploration helped discover a     also been one of the leading \ufb01gures in the  early days\nlarge quantity of unknown features related to Earth materi-    (Duncumb, 2001; Grillon & Philibert, 2002).\nals, thus greatly improving the knowledge of our planet. On         Besides  his  ingenuity  with  those  rather  primitive\nthe other hand, the complexity of natural materials called for    instruments, Castaing had the great merit to demonstrate the\never improved analytical capabilities. Another example of    proportionality between the intensity of the emitted X-ray\nhow basic research is the most effective driver of technol-     signal and the concentration of the emitting element, once\nogical development.                                        account  is taken (by empirical factors) of the nature of\n                                                              the sample (matrix effect). Castaing had actually formulated\n                                                    two approximations, one regarding the proportionality and\nMore Recent Times                                        the other regarding the matrix effects; the combination of\nIt was during those years, in 1983, that I had the fortune to    these two approximations form the core of what is known\nmeet the founding father of the technique, Professor Ray-    as Castaing\u2019s Principle\u2014the fundamental law of EPMA.\nmond Castaing. The occasion was the 10th International    Curiously enough, Castaing\u2019s basic principle, together with\nCongress on X-Ray Optics and Microanalysis in Toulouse,    the  use  of  appropriate  standards,  is nowadays  being\nwhere I happened to sit at his table during dinner.              re-discovered for the latest quantitative applications of EDS1056  Romano Rinaldi and Xavier Llovet\n\nspectrometry with the latest generation of detectors (Newbury    few years, this assessment proved to be very wrong as will\n& Ritchie, 2013), despite over 60 years of development in    become clear in the following sections.\nmethods for calculating all possible matrix effects from \ufb01rst\nprinciples.                               THE LATEST DEVELOPMENTS AND THE NEW\n    At that same Congress, in 1983, several novelties that\n                                AGE OF EPMA: A BRIEF OVERVIEWwere to become important stepping stones in the advance-\nment of the technique were presented. With no claim to                                                  The constant search for low detection limits and high spatial\ncompleteness,  I will mention just a few that are  still of                                                                resolution has recently given EPMA a whole new scope. The\ninterest to this day. A new approach to matrix effects for                                                               idea of trace element analysis, which has been emerging\nquantitative analysis, the \u03a6-\u03c1-z correction, applied to both,                                                 more and more frequently as a favorite issue, is now con-\nbulk and  layered samples (Pouchou &  Pichoir, 1983a,                                                               sidered almost common place with the new generation of\n1983b), later referred to as the PAP method from the initials                                                                electron probes with both WDS and EDS spectrometers. The\nof the two authors. The application of Monte Carlo (MC)                                                         paper on age dating through EPMA of U, Th, and Pb by John\nsimulation methods to the analysis (Murata et al., 1983) and                                                       Bowles in this issue (Bowles, 2015) is a good example of the\nthickness determination (Armigliato et al., 1979, 1983) of                                                                 possible applications of reliable low and trace element con-\nthin \ufb01lms on substrates. An improved absorption correction                                                               centration analysis by EPMA. Ultimately, the capability of\n(Love et al., 1983) derived by MC \ufb01tting of \u03a6-\u03c1-z curves                                                                   trace element analysis by electron microprobe has become a\ncovering a wide range of experimental conditions. The latest                                                                        reality with present-day instruments and data processing\ndevelopments of some of these themes will be treated in the                                                                 software, reaching well below the 0.1 wt% level and into the\nfollowing sections of this paper.                                                                 parts per million (ppm) range (Jerci\n\n## 2. rinaldi2015electronprobemicroanalysis pages 4-5 (Context ID: pqac-00000051)\n\n centration analysis by EPMA. Ultimately, the capability of\n(Love et al., 1983) derived by MC \ufb01tting of \u03a6-\u03c1-z curves                                                                   trace element analysis by electron microprobe has become a\ncovering a wide range of experimental conditions. The latest                                                                        reality with present-day instruments and data processing\ndevelopments of some of these themes will be treated in the                                                                 software, reaching well below the 0.1 wt% level and into the\nfollowing sections of this paper.                                                                 parts per million (ppm) range (Jercinovic et al., 2012).\n   The instrumental complexities and theoretical chal-                                           On the other hand, high spatial resolution has always\nlenges that Castaing had to overcome initially were only the                                                       been the specialty of the technique. However, when account\nbeginning of a constant challenge that had to be met by                                                                                     is taken of the actual interaction volume which everybody has\npeople running the instruments that were made commercially                                                               learned to appreciate from MC simulations at least from a\navailable starting in the early 60s and until the mid-70s of the                                                                 graphical point of view,  it becomes quite evident that the\nlast century. This favored a constant exchange between users                                                               search for better resolution is essential, as shown in Figure 3.\nand manufactures, which, to this day, enjoy a special kind of                                                                       Traditionally, pushing the limit of the lowest detection\nsymbiosis on the subject, as can be strongly felt during meetings                                                                    limit with a WDS spectrometer has meant increasing the\ndedicated to the technique and its applications.                                                                   collection time, as suggested for instance by the classical\n      It was in this period (early-1960s\u2013mid-1970s) that the                                                             expression proposed by Ziebold (1967):\nanalysis of \u201cplatinoids\u201d (now platinum group minerals, or\nPGM), usually occurring as very small grains dispersed                  CDL>3:29a=\u00f0ntP \u00b4 P=B\u00de1=2\nin rocks, was undertaken by Professor Eugen F. Stump\ufb02, a\npioneer in EPMA of minerals (Stump\ufb02, 1961; Stump\ufb02&    where the limit of detectable concentration (CDL) depends on\nClark, 1965) and the founding father of the lab hosting the    a factor (a) relating to composition and intensity, on the\n2014 EMAS Workshop from which the collection of papers   number of observations (n), and on the counting time (t);\nin this special issue has been derived.                      and where P  is the peak count rate and P/B the peak-\n   As a matter of fact, the beginning of the use of the    to-background ratio.\nelectron microprobe for the analysis of minerals and rocks       More advanced statistical expressions have introduced\nas an established and almost mandatory technique in this    con\ufb01dence levels and standard deviations on the measure-\n\ufb01eld can be traced to around 1964, when some 60 papers    ments and  considerations on  precision and  accuracy,\nwere published worldwide, reporting mineralogical analyses    depending on the peculiarity of the sample examined, such\nobtained by  this technique  (Keil, 1973). Therefore, we\ncan safely assume that this year (2014) marks the 50th\nanniversary of the application of the technique in Earth\nSciences. The year 1964 also coincides with the \ufb01rst meeting\nof the Microbeam Analysis Society in the United States\nof America.\n   Around the mid to  late 1990s  (e.g., Rinaldi, 1997),\nthanks  to  the huge improvements  in  microelectronics,\nautomation, and informatics, EPMA tended more and more\nto become a \u201cblack box\u201d routine for a vast number of users,\nand the general consensus was that it had developed towards\na \u201cmature\u201d technology. In other words, not many more\nimprovements could be expected in the medium term, or at    Figure 3. Electron trajectories in Si with E0 = 1, 5, and 10 keV,\nleast advances  at the same rate as during the previous    computed using Monte Carlo simulations. The penetration range\n10 years or so, could no longer be expected. Within only a     of electrons reduces considerably with decreasing beam energy.                                                                                                Electron Probe Microanalysis  1057\n\n\n\n\n\n        Figure 4. Electron micrographs from Au particles. Left images obtained with a \ufb01eld-emission gun, center with a LaB6\n         cathode, and right with a W \ufb01lament. Top beam current of 10 nA; bottom, 100 nA. Accelerating voltage 10 kV, magni-\n         \ufb01cation 5,000\u00d7 (reproduced with permission of JEOL).\n\n\nas small particles, sensitive material, etc. (Jercinovic et al.,     (current density) almost three orders of magnitude greater than\n2012), and taking into account the stochastic nature of the     that produced by a conventional thermionic emitter such as\ngeneration.                                                 a tungsten \ufb01lament or a lanthanum hexaboride cathode. The\n    In any case, the limit is reached when statistical \ufb02uc-     result is a great improvement in signal-to-noise ratio, spatial\ntuations due to instabilities intrinsic to the system approach     resolution, emitter  life, and  reliability. Each one of these\nthe same level as the signal. The key to improving the    improvements has a bearing on extending the capabilities of the\ndetection limit is, therefore, a strong signal with high stabi-     electron beam instrument as to both image and analysis. The\nlity. The latter  is clearly where the advancement in fast     latter being the most important aspect in EPMA. Figure 4\nresponse (picosecond) electronics comes into play. As to the    provides a visual comparison of the image resolution obtained\nnumber of counts produced, this can be improved by a    with the three kinds of emitters (FEG, LaB6, and W).\nvariety of measures that include high re\ufb02ectivity large crys-         All manufacturers of EPMA instruments and electron\ntals, improved vacuum systems, and, last but not least, a new    microscopes (both SEM and TEM) currently offer the \ufb01eld\nkind of electron emitter making use of the \ufb01eld effect as    emission alternative, and this is seen in the names of the\nopposed to the traditional thermionic emission.               instruments that may have an \u201cFE\u201d or an \u201cF\u201d as suf\ufb01x\n   The \ufb01eld-emission gun (FEG)  is probably the most    or pre\ufb01x. The improved emission from a point source\nremarkable of the latest improvements. When compared    allows sub-micrometer analytical probe sizes (10\u201380 nm;\nwith a W-\ufb01lament emitter, its brilliance is several 100-fold      e.g., Berger & Nissen, 2014), again an improvement of three\nbetter, and  stability, once a dif\ufb01cult requirement to be    orders of magnitude over a traditional emitter. When com-\nobtained, is no longer a nightmare, thanks to fast electronics.    bined with low voltage operation (5\u20137 kV), this results in a\nThe design in itself is quite simple, the emitter cathode is    very shallow penetration depth, and therefore a dramatic\nagain tungsten, but in the form of a solid single crystal cone    reduction of the analytical volume (volume of interaction, as\ntapered into a very \ufb01ne point upon which a strong magnetic   shown in Fig. 3), and a generated signal (thanks to the high\n\ufb01eld extracts the electron beam by a principle as old as that     brilliance), which is still strong enough to provide full ana-\non which the lightening rod was conceived by Benjamin     lytical capabilities for both spectroscopies (WDS and EDS).\nFranklin 265 years ago! As a matter of fact, the theory of \ufb01eld        Although the negative trade-offs for low voltage opera-\nemission kept several eminent physicists busy for a good part    tion may require special care and a whole new approach for\nof the 20th century until its practical application was \ufb01nally     quantitative  analysis (Merlet &  Llovet, 2012; Pinard &\nintroduced as a commercial alternative in electron micro-     Richter, 2014), the advantage of a greatly reduced interaction\nscopy during this last decade. As is often the case, there are    volume opens up a large variety of new applications in the\nseveral different designs of FEG\u2019s, but their description is    characterization of thin \ufb01lms and nanomaterials. The pros\nbeyond the scope of this brief account. It is suf\ufb01cient to note    and cons\n\n## 3. rinaldi2015electronprobemicroanalysis pages 5-7 (Context ID: pqac-00000052)\n\nlthough the negative trade-offs for low voltage opera-\nemission kept several eminent physicists busy for a good part    tion may require special care and a whole new approach for\nof the 20th century until its practical application was \ufb01nally     quantitative  analysis (Merlet &  Llovet, 2012; Pinard &\nintroduced as a commercial alternative in electron micro-     Richter, 2014), the advantage of a greatly reduced interaction\nscopy during this last decade. As is often the case, there are    volume opens up a large variety of new applications in the\nseveral different designs of FEG\u2019s, but their description is    characterization of thin \ufb01lms and nanomaterials. The pros\nbeyond the scope of this brief account. It is suf\ufb01cient to note    and cons of these new avenues offered by the FEG in EPMA\nhere that the electron beam produced by an FEG is much    are discussed in more detail in the Analytical Capabilities\nsmaller in diameter, more coherent, and has a brightness    Today: Advantages and Disadvantages section.1058  Romano Rinaldi and Xavier Llovet\n\n    Another instrumental development has recently pro-    response to different crystal orientations of the sample (and\nvided great improvement in EDS with the introduction,    reference standard) under the beam. Some of these have\nduring the last decade, of a new device\u2014the silicon drift     recently been reviewed (Donovan, 2011). The usual strate-\ndetector (SDD)\u2014the development of which has been as fast     gies to avert or limit these effects include the careful choice of\nas to have already reached its 6th generation. When com-    instrumental parameters, the use of an anti-contamination\npared with the traditional lithium drifted silicon detector (Si    device and/or of a cryostage, careful monitoring of the\n(Li) detector), this new kind of device, although working on     effects, and use of empirical correction coef\ufb01cients as a\nexactly the same principle, provides a considerable number    function of dwell time.\nof advantages. The \ufb01rst and the most noticeable, even to the        Other caveats, especially when working with low-energy\nuntrained eye, is the lack of the cumbersome and incon-     lines (low voltage excitation), include the need to revisit the\nvenient liquid nitrogen cryostat and the reduction in main-    mass attenuation coef\ufb01cients (MACs) (e.g., Gopon et  al.,\ntenance activity this implies. The detector can in fact operate    2013) and the effects due to secondary \ufb02uorescence (SF) at\nat room temperature or with moderate cooling, such as that    grain boundaries (e.g., Llovet et al., 2012; Wade & Wood,\nprovided by the thermoelectric (Peltier) effect, thanks to the    2012). Some of these aspects are treated in more detail in the\nvery  low  leakage  current  generated  within  the  device.    following section, with a few examples of applications.\nThe other main advantage is the count rate performance, which\nis up to two orders of magnitude greater than that of a Si(Li)\ndetector (Newbury & Ritchie, 2013). All this, combined with an   ANALYTICAL CAPABILITIES TODAY:\nenergy resolution close to the theoretical value of 120 eV for a  ADVANTAGES AND DISADVANTAGES\nsilicon device, makes the SDD a desirable analytical tool for all\nkinds of electron microscopy. A comparison of performance   Improved Detection Limits for Trace Analysis\nbetween EDS and WDS spectroscopies now has to take into    Use of electron microprobes for trace element analysis has\naccount the great improvements one can obtain with this latest    increased over the years, mainly because of the improved\ngeneration of solid-state detectors where a de\ufb01nite advantage     stability of electron columns operated at high-beam currents\ncan be scored, for instance, in the acquisition speed of X-ray    and the development of new crystal analyzers with larger\nmaps. However, when energy resolution and low detection     areas. Figure 5 provides a comparison between these newly\nlimits are at stake, WDS detectors remain as the technique of\nchoice for quantitative analysis, especially for trace and light\nelements (Maniguet et al., 2012).\n    In the \ufb01eld of WDS spectroscopy, a very recently\nintroduced device provides considerable improvement in the\nanalysis of very soft X-rays, including Li and Be among the\nelements that can be quantitatively analyzed. This type of\nspectrometer makes use of a new grazing incidence grating\ntechnology, whereby dispersion of the incident X-rays  is\nobtained by Bragg re\ufb02ection over a physical grating rather\nthan a crystal lattice. The combination of a laminar-type\nvaried-line-spaced (VLS)  grating with a  high-sensitivity\nX-ray CCD detector allows simultaneous collection of a full\nspectrum (within a limited wavelength range), thus making\nthe device somewhat comparable with EDS. Having been\nintroduced only very recently, testing of the device is still\nlimited to a few emblematic examples that have been pro-\nvided by the manufacturers. However, there is no reason to\ndoubt the promise to considerably expand the capabilities of\nEPMA, as discussed is more detail in the last section dealing\nwith the envisaged future.\n    Most, if not all, of the above-mentioned advances are\nextending the limits of EPMA toward higher spatial resolu-\ntion and lower detection limits. The trade-off is normally the\nincreasing importance of some adverse effects that the ana-\nlyst has to take into account. Among these effects, a few are\nworth mentioning here even if they will not be discussed in\ndetail according to the nature of this brief review. Carbon    Figure  5. Sensitivity  of  newly  developed LDE2 and LDE2H\ncontamination and sample \u201cdamage\u201d by the electron beam      crystals, as compared with  traditional STE,  for the  analysis  of\nboth merit attention here. The latter comprises effects such     C. Detection limits are 12 (LDE2H), 23 (LDE2), and 49 ppm (STE)\nas migration of elements from the analytical volume, also in      (after Mori et al., 2011). Reproduced with the permission of JEOL.                                                                                                Electron Probe Microanalysis  1059\n\n                                                                Instrumental and sample stability during long acquisi-\n                                                                tion times can be monitored by means of statistical tests (e.g.,\n                                                                \u03c72 test along with Dixon and Grubss \ufb01lters), as discussed by\n                                                           Merlet & Bodinier (1990). This procedure requires the long\n                                                          counting times to be divided into many short counting times\n                                                    and alternating peak and background measurements to\n                                                      minimize instrumental drift.\n                                                      The problem of SF across phase boundaries arises from the\n                                                                          fact that characteristic X-rays and bremsstrahlung produced by\n                                                          primary electrons can ionize atoms at much larger distances\n                                                      from the point of impact than primary electrons. Indeed,\n                                                             although the range of primary electrons is of the order of a\n                                                         few micrometers, that of the generated  characteristic and\n                                                            bremsstrahlung X-rays can be one-to-two orders of magnitude\nFigure 6. Detection limit for Mn in a San Carlos olivine standard     larger. This means that, even for electron beams impacting\nas a function of probe current and peak counting time. Typical     quite a distance from a phase boundary, there can be a \ufb02uor-\nconditions for routine, precision, and high-precision analysis are    escence contribution arising from the neighboring phase. This\nmarked (after Sobolev et  al., 2007). Reprinted with permission     contribution is important for trace analysis, especially when the\nfrom AAAS.                                                  neighboring phase contains an appreciable concentration of the\n                                                           element of interest. This effect will be discussed in more detail\n                                                                  in the Limitations and Problems subsection.\ndeveloped crystals and the traditional one (STE) in C ana-        Examples of improved methods for the analysis of trace\nlysis. These developments have made it possible to decrease    elements include those developed by Merlet & Bodinier\nthe detection limits of the technique down to a few ppm by    (1990) and Fialin et al. (1999). The latter auth\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052]\n\nStatus: Paper Count=23 | Relevant Papers=15 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=53 | Current Cost=$0.2725 | Disease-Target Evidence=0",
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+                "content": "Now let me update the plan and read a few more key texts, particularly for the measurement uncertainty paper and the Guyett SEM-EDX optimization paper:",
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+                "content": "## 1. tong2026measurementuncertaintiesof pages 8-11 (Context ID: pqac-00000053)\n\nRVIEW\nWhen electrons of sufficient energy hit a sample, they generate X-rays of specific energies\ncharacteristic of the elements present. The main challenge of qualitative analysis is to ensure\nthat all X-ray peaks are detected and correctly labelled as a sample element or a detector\nartefact peak. The intensity of the X-ray peaks are not interpreted, although in complex or\nnoisy spectra, low intensities may cause low concentration elements to be missed. Accurate\nqualitative EDX is a prerequisite of any quantitative EDX.\n\n\nPage 1 of 20NPL Report MAT 135\n\n\nAn example of a periodic table that lists the characteristic X-ray emission energies (K\u03b1, L\u03b1,\nand M peaks) for each element can be found at: https://www.edax.com/resources/interactive-\nperiodic-table. X-ray techniques with higher energy resolution, such as X-ray photoelectron\nspectroscopy (XPS) or SEM wavelength dispersive X-ray spectroscopy (SEM-WDS) can split\nthese into multiple lines (e.g. K\u03b11, K\u03b12, K\u03b21, etc.), but since the energy resolution of EDX\ndetectors are usually \u2265 100 eV, only a single broader peak is measured.\n\nElemental assignment of X-ray peaks might be ambiguous if the peaks from multiple\nelements have similar energies (within 30 eV of each other). ISO 22309:2011 Annex B lists\ngroups of elements with ambiguous X-ray peaks.\n\nElectrons can only generate characteristic X-rays with considerably lower energy than the\nprimary electron energy. The ratio between the incident electron energy and the\ncharacteristic X-ray energy is called the electron overvoltage. An electron overvoltage of at\nleast 1.8 is specified for quantitative analysis in ISO 22309:2011. It is not absolutely required\nbut still recommended for qualitative analysis, as X-ray peaks close to the primary electron\nenergy may be hidden or very weak. It is impossible to generate X-rays that have a higher\nenergy than the primary electron energy.\n\nArtefact peaks are not characteristic X-ray peaks of the sample. They need to be identified\nand corrected. EDX analysis software packages generally have features built in to do this,\nbut it is still the operator\u2019s responsibility to check that this has been done correctly and no\npeaks have been mislabelled.\nSum peaks (also known as pile-up peaks) happen when two X-ray photons hit the detector\nat the same time, and are mistakenly detected as a single X-ray whose energy is the sum of\nthe two original photons. These appear as small peaks at higher energies that are the sum of\nmultiple X-ray emission peak energies, e.g. at double the energy of the highest intensity\npeak.\nEscape peaks are caused by X-ray fluorescence of the detector material, usually made of\nsilicon, so that the detected X-ray energy is the X-ray emission peak. Escape peaks appear\nas small peaks at higher energies, e.g. at double the energy of the highest intensity peak.\nThe noise peak at near-zero energy is when electronic noise in the detector is mistaken for\nnear-zero energy photons.\n\n1.2 QUANTITATIVE EDX METHOD OVERVIEW\nEDX quantification is based on the principle that X-ray peak intensities for an element\nincrease with concentration of that element in a sample. However, there are two problems:\n   (1) X-ray detector efficiency is not constant, so identical X-ray intensities hitting the EDX\n      detector at, for example, 1 keV and 8 keV will not lead to identical peak areas at 1 keV\n     and 8 keV; and\n   (2) the generated characteristic X-ray intensities are not linear with concentration, so\n     doubling the atomic concentration of an element does not necessarily double the\n      intensity of characteristic X-rays hitting the EDX detector.\n\nAll quantitative analysis considers the characteristic X-ray peaks only, which means it is\nnecessary to remove the intensity contribution of background X-rays generated by\nBrehmsstralung radiation. Background correction is important in quantification, but different\nEDX analysis software packages use different methods and this usually cannot be tuned by\nthe user. However, a poor background fit (Figure 1b), which leads to inadequate peak area\ndetermination, is still a useful warning sign to the operator that that the quantitative results\nhave high uncertainty.\n\n\n\n\nPage 2 of 20NPL Report MAT 135\n\n\n\n              (a)\n\n\n\n\n\n              (b)\n\n\n\n\n\n      Figure 1: Example spectra with (a) good and (b) bad background fit.\n\nProblem (1) explains why elemental standards are needed for full quantitative analysis, so\nthat differences in detector efficiency can be cancelled out. The detector window material\naffects detector efficiency, especially in the low X-ray energy range (see Figure 9 in [5]).\nBeryllium windows absorb the majority of X-rays below 1 keV and therefore are not suitable\nfor use with low-Z elements below Na (Na K = 1.04 keV). Si3N4 or polymer thin windows\nperform better, but the efficiency drops off significantly and is discontinuous in this energy\nrange. Windowless detectors would be preferable but are not currently available at NPL in\n2024. Contamination buildup in the SEM can also affect efficiency for all detector\nconfigurations.\n\nProblem (2) is why background subtraction and matrix corrections are needed (also known\nas ZAF corrections: Z = atomic number, A = X-ray absorption, F = X-ray fluorescence).\nThese account for the effects of:\n -   Electron backscattering (which increases with atomic number Z), where incoming\n    electrons are either scattered back out of the sample without generating an X-ray, and\n    electron stopping power, which describes how electrons lose energy (and the\n    corresponding ability to excite atoms and generate X-rays) as they penetrate the sample.\n -   X-ray Absorption, which means that X-rays generated by the sample are absorbed\n    before they leave the sample and never make it to the detector.\n -  Secondary X-ray Fluorescence, which means that high-energy X-rays generated in the\n    sample generate lower-energy X-rays. As a result, the high-energy X-ray is not detected,\n    but extra low-energy X-rays are detected by EDX.\n\n\nPage 3 of 20NPL Report MAT 135\n\n\nThe theory relating to ZAF matrix corrections are more naturally described by weight\nfractions instead of atomic fractions. This is why EDX compositions are calculated as\nweight % even though the k-ratios are more naturally expressed in atom %.\n\nNot every X-ray line is in the standards database, so for example the Fe-L peaks (0.705 keV)\nmay not be used for quantification if only the Fe-K peaks (6.403 keV) are included in the\ndatabase. This must then be taken into account when selecting SEM accelerating voltage \u2013\nfor example, the Fe-K peak requires at least 12 kV electron energy to be adequately excited\nfor quantitative analysis.\n\n\n\n\n\nPage 4 of 20NPL Report MAT 135\n\n\n\n                                                                                                                                                                                              (4) All elements in                             (1) Conductive and                                          (2) Flat, polished,                                                                                                                                             (3) All sample                         sample (incl. trace                         stable in vacuum and                          homogeneous surface,                                                                                                           elements are Z > 11?                        elements) already                           electron beam?                              normal to electron beam?                                                                                                                                       known?\n\n                Yes          No                       Yes       No             Yes          No                Yes        No\n\n                    Qualitative                                                                                                                               Consider                                                                                                                            low                                       Try                                    10                             nm C                                                                Any                                                                                                                                                                      over-                                                                                                                           \u2265 1.8 \u00d7                                                                                                                                                                                                                 Unnormalised                                                                                               Qualitative            \n\n## 2. guyett2024optimizingsemedxfor pages 4-6 (Context ID: pqac-00000054)\n\n     0.00          0.07\n           Cl         <LOD     <LOD     <LOD     <LOD     <LOD     <LOD      <LOD     <LOD        0.02          0.03\n           Total         97.00        98.16        98.48        98.74        98.82        99.15        99.25        99.18        100.04       99.24\n\n\n      NMNH 72854\n          SiO2          76.3         76.9         77.1         77.3         77.3         77.4          77.4         77.9          77.9          78.1\n           Al2O3         11.9        12           12.1         12.2         12.2         12.2          12.1         12.2          12.2          12.2\n         K2O           4.95         4.84         4.94         5.01         4.93         4.94          4.95         5.07          5.08          5.08\n         Na2O         3.67         3.5          3.44         3.37         3.17         3.7           3.53         2.99          2.91          3.28\n           FeO(t)        1.02         1.11         1.22         1.12         1.15         1.2           1.17         1.18          1.18          1.18\n        CaO          0.00         0.00         0.26         0.44         0.47         0.47          0.45         0.48          0.48          0.47\n           Cl         <LOD     <LOD     <LOD       0.02         0.04         0.11          0.12         0.12          0.11          0.11\n          TiO2       <LOD     <LOD     <LOD     <LOD     <LOD     <LOD        0.01         0.05          0.08          0.09\n       MgO       <LOD     <LOD     <LOD     <LOD     <LOD     <LOD      <LOD       0.01          0.01          0.01\n       MnO       <LOD     <LOD     <LOD     <LOD     <LOD     <LOD      <LOD     <LOD      <LOD        0.01\n          P2O5       <LOD     <LOD     <LOD     <LOD     <LOD     <LOD      <LOD     <LOD      <LOD      <LOD\n           Total         97.84        98.35        99.06        99.46        99.26        100.02       99.73        100.00       99.95        100.53\n\n\n\n        2568  | J. Anal. At. Spectrom., 2024, 39, 2565\u20132579                                       This journal is \u00a9 The Royal Society of Chemistry 2024                                                                                                                                        View Article Online\n\n        Paper                                                                           JAAS\n\n\n        and  counts  per  analysis.  However,  these  analyses  were   analyses in rhyolite glass NMNH 72854 was adversely a\ufb00ected\n         completed with a scanning FoV of 1 mm to avoid partial analysis   only at high counts ($5M). Even lower beam currents can result\n          of microlites. An EDX map and BSE image were collected to   in Na-loss over an extended period  of  time.16 Hence,  to\n          highlight the  microlite  density. The  voltage and working\n          distance remained  as  before  but  the beam  current was\n         increased to 3 nA to o\ufb00set the e\ufb00ect of the smaller FoV on the\n           total number of counts and the process time was set to 2. This\n         increased beam current increases the SEM counts per second to\n         approximately 800 kcps. For the map, the \ue103eld of view was set to\n         50 mm. Both a BSE image and an EDX map were collected withPM. Licence.    a resolution of 2048 \u00d7 1557, with a pixel dwell time of 10 ms per\n           pixel for the BSE image and 200 ms per pixel for the EDX map.\n          The cryptotephra from the Laki 1783-84 AD eruption was7:38:13 Unported\n         analysed using a wavelength-dispersive JEOL 8600 electron\n   3.0\n         microprobe in 2016. This analysis was completed using an7/23/2025          accelerating voltage of 15 kV, a 6 nA current and a beam\non\n         diameter of 10 mm. Peak count times were 30 s for most           Attribution         elements and 10 s for Na. Due to the small size (25\u201340 mm long\n         but with analyzable areas of <20 mm) of the cryptotephra, onlyDownloaded      one EPMA analysis was acquired successfully.42 The crypto-       Commons\n2024.       tephrausing asamplesTescan wereMira reanalysedXMU FE-SEMin theequippedsame yearwithbyanSEM-EDXOxford        Creative    Instruments X-Max 80 mm2 EDX detector and Oxford Inca\n a    so\ue09dware. In total, nine basaltic shards were analysed.42September     under\n03\non licensed   4.4.1  OptimalResultsnumberandof countsdiscussion\n  is\n        The number of counts per analysis  is a trade-o\ufb00betweenPublished       article     sensitivity on the one hand and acquisition runtime and cation\n          mobilisation on the other. Fig. 2 shows the relative standardArticle. This\n          deviations (RSD%) of SEM-EDX glass analyses conducted over\n         a range of total counts (complete data can be found in Table 1Access\n        and ESI Table 1\u2020). For almost all elements the most precise\nOpen        results came from the analyses that collected the highest\n        number of counts. The quickest analyses, those acquired with\n        10k and 20k counts (below one second analysis time), displayed\n           relative standard deviation (RSD%) >5% on elements over 10 wt\n         oxide%, and RSD% >10% on elements above 1 wt oxide%. Once\n         the number of counts per analysis is above 100k (one to three\n         second analysis time), all elements over 1.5 wt oxide% exhibited\n         a RSD% of <5%. These results here may have implications on\n            fully quanti\ue103able alternative SEM-EDX applications such as\n         element mapping, where analysis of large cumulative areas\n          necessitates rapid analysis. When >1M counts were acquired,\n         the RSD% for major element oxides was <2% for both basaltic\n          glass VG-2 and rhyolitic glass NMNH 72854. For fully quanti-\n           tative EDX analysis, we recommend collecting a minimum of\n      1M counts, as this will result in rapid acquisition (approxi-\n         mately 15 seconds using the above SEM parameters) of accurate\n         major element data. It is possible to attain data of similar    Fig. 3  Repeat analyses on basaltic NMNH VG-2 and rhyolitic glass\n                                                  NMNH 72854 to investigate potential beam-induced elemental loss on\n          precision  for  higher  concentration  trace  elements  (those\n                                                                      Na2O, K2O and Cl. Each glass is analysed in four separate areas up to\n         present at >0.1 wt% or above) in both glasses, but this requires   a total of 20M counts. Analyses comprised either 1M, 2M, 5M and 10M\n          analyses of c. 10M counts.                                      count intervals. Panels (a)\u2013(e) display analyses on elements in decreasing\n            Certain elements (e.g., Na, K and Cl), are known to display   abundance. K2O in NMNH 72854 and Na2O in both glasses are major\n          mobility  during beam  interaction  due  to  heating.15,16,25   elements (panels (a)\u2013(c)), and the remaining K2O (NMNH VG-2) and Cl\n                                                         (NMNH 72854) analyses are minor elements (panels (d) and (e)).\n         However,  it is evident from Fig. 2 that the precision of Na\n\n\n\n           This journal is \u00a9 The Royal Society of Chemistry 2024                                                    J. Anal. At. Spectrom., 2024, 39, 2565\u20132579  | 2569                                                                                                                                        View Article Online\n\n      JAAS                                                                                        Paper\n\n\n           Table 2  Repeated spot analysis on NMNH VG-2 and NMNH 72854. For each glass four separate areas were analysed summing up to a total of\n       20M counts\n\n\n          Counts (million)    1        1        1        1        1        1        1        1        1        1        1        1\n\n      NMNH VG-2       33a      33b      33c      33d      33e       33f      33g      33h       33i        33j      33k       33l\n          SiO2                50.7      50.8      51.0      51.1      50.8      51.0      51.0      51.0      51.0      51.1      51.1      51.1\n           Al2O3               14.1      14.2      14.2      14.1      14.1      14.1      14.2      14.1      14.1      14.2      14.1      14.2\n           FeO(t)              11.7      11.7      11.6      11.7      11.8      11.6      11.6      11.4      11.7      11.8      11.6      11.6\n        CaO                11.1      11.1      11.1      11.2      11.1      11.1      11.1      11.2      11.1      11.2      11.2      11.2\n       MgO               7.00      6.93      6.93      7.06      7.02      6.89      6.96      6.86      7.00      6.94      6.94      6.91\n                               2.63                                         2.76                                                    2.67                                                              2.65                                                             \n\n## 3. guyett2024optimizingsemedxfor pages 3-4 (Context ID: pqac-00000055)\n\nf which may be too small for  from komatiite to rhyolite and with a range of alkali contents\n       WDS-EPMA.                                                         (SiO2: 45.5\u201376.7; Na2O: 0.83\u20134.44; K2O: 0.19\u20135.10 wt%). These\n\n\n\n        2566  | J. Anal. At. Spectrom., 2024, 39, 2565\u20132579                                       This journal is \u00a9 The Royal Society of Chemistry 2024                                                                                                                                        View Article Online\n\n        Paper                                                                           JAAS\n\n\n          glasses include the Smithsonian National Museum of Natural  so\ue09dware version 5.1 (and subsequently version 6.1) at the iCRAG\n          History (NMNH) glasses NMNH VG-2, NMNH 72854, NMNH   Laboratory in Trinity College Dublin. Additional analyses were\n         113498-1 and NMNH 113716-1,30 MPI-DING glasses ATHO-G,  undertaken using a Tescan Tiger Mira3 FE-SEM operating\n         T1-G, StHs6/80-G and GOR132-G,31 as well as rhyolitic glasses  under high vacuum conditions, \ue103tted with two XMaxn 150 mm2\n         ID3506 (ref. 32) and Oregon Obsidian from the MINM25-53  EDX detectors running Oxford Instruments AZtec microanalysis\n         standard mount (ESI Table 1\u2020). The glass samples employed  so\ue09dware version 3.2. Unless otherwise speci\ue103ed, analyses were\n          in this study are of known composition and are widely used as  undertaken with a voltage of 20 kV, a 4.5 nm wide beam with\n          reference materials in WDS-EPMA analyses of glasses (e.g., ref.  beam current of 300 pA, and a process time of \ue103ve, following the\n         33 and 34). The two glasses initially investigated to determine  SEM-EDX protocol de\ue103ned in Ubide et al. (2017).8 Beam current\n         optimal experimental setup are the basaltic glass NMNH VG-2  dri\ue09dwas controlled by analysis of cobalt a\ue09der each samplePM. Licence.    and the rhyolitic glass NMNH 72854.30 These were selected as   change, however it is worth noting that modern FE-SEMs show\n         two homogenous end members which span a broad composi-   considerably lower dri\ue09dcompared to older W-SEM systems.43\n          tional range. The MINM25-53 mount contains a suite of silicate   Process time is a dimensionless time index between one and six7:38:13 Unported\n        and sulphide minerals, produced by Astimex Standards Ltd,   within the AZtec so\ue09dware. It is a time index where a lower\n   3.0\n         Canada.                                           number prioritises analysis time and a higher number priori-7/23/2025          The study chose to focus on glass because  it  is non-   tizes energy resolution.\non\n          stoichiometric, and thus presents a greater challenge than      Fully quanti\ue103ed SEM-EDX analysis requires the microscope           Attribution         minerals for which stoichiometry provides an additional check   to be set up correctly and to have the highly-polished and \ue104at\n        on data quality (e.g., ref. 35) and also because of the potential for  sample under the beam at an appropriate working distanceDownloaded      beam-induced elemental mobility. Fully quantitative SEM-EDX  (WD) which herein is 15 mm. There are two main ways to collect       Commons\n2024.       analysiswhile preciseon  glasssamplethuspreparationrequires  carefulis neededinstrumentto accountset-upfor  SEM-EDXAnalysis modespectracollectsthroughdataAZtec;by rasteringAnalysisa 4.5Modenm beamor Pointover& theID.        Creative     issues with specimen geometry. Samples were polished on an   scanning window for a determined runtime and collecting all X-\n a    automatic lap using progressively \ue103ner diamond grits down to 1   ray information within this \ue103eld of view at a high magni\ue103cationSeptember     under    micron to ensure a \ue104at and highly polished surface to attain   while Point & ID collects a reference image such as back-\n03            fully quantitative SEM-EDX results. The samples also need to be   scattered electron (BSE) at a lower magni\ue103cation and analysis is\non\n            fully conductive to avoid charging of electrons on the surface,   acquired from selected areas within this image. The selected        licensed\n  is     typically this will require specimens to be coated in a thin layer   area can be a selected point or a shape (e.g., a circle, rectangle,\n          of carbon or gold. All samples were coated with 12 nm of carbon   or user-de\ue103ned polygon). The acquisition of an image showingPublished       article    before being introduced into the SEM chamber for analysis.   the location of the SEM-EDX spot analyses when using the Point\n           Finally,  additional  analyses  were  undertaken on  natural  & ID method makes it initially quite appealing; however, thereArticle. This\n          volcanic glass shards to further highlight SEM-EDX data quality   are drawbacks with this approach. In practice, due to the\n        and to demonstrate some of the advantages o\ufb00ered by this   resolution of the acquired image at lower magni\ue103cation, it isAccess\n          technique. These samples include:                            not always possible to ensure that the sample  is polished\nOpen           Tephra layer TM-24-3b from an eruption of Ischia and   completely \ue104at. In mineral samples, there may be material\n         deposited at Lago Grande di Monticchio, Italy (LGdM) (ref. 36  removed along grain boundaries or along cleavage planes and\n        and 37) 80 km to the east. This sample was previously analysed  such areas need to be avoided. Accurate and fully quantitative\n         by EPMA37 and  is reanalysed here by SEM-EDX  to allow  SEM-EDX analysis requires \ue104at, polished samples that are in-\n         comparison of the data quality achieved by the two techniques.   focus which is not always possible during Point & ID spot\n           Ma\ue103c tephra from the PdB (Pomici di Base) eruption of   analysis; a very well-polished geologic sample may still have\n        Somma-Vesuvius which is challenging to analyse because the   varying topography. Analysis Mode ensures that the sample is\n         tephra is microlite rich38 and the spacing between microlites is   in-focus, thus providing more con\ue103dence in the quality of the\n          smaller than the interaction volume produced by a 10 mm beam.   analysis. In both methods it is possible to collect the data using\n         This resulted in the acquisition of mixed compositions (glass   a set runtime or until a set number of counts has been attained.\n        and crystal phases) with the EPMA method (ref. 39: their Fig. 7).      X-ray peak  energies  for each peak were  calibrated  to\n                Basaltic cryptotephra shards from the Laki 1783-84 AD   concentrations using a range of mineral and glass standards.\n         eruption identi\ue103ed in Brackloon Wood, Co. Mayo, Ireland (ref.   For optimal matrix matching of silicate glasses, we used the\n         40 and 41). Analysis of these tephra presents a challenge   following phases on the Astimex MINM25-53 standard mount\n         because of their extremely small size (<40 mm vesicular shards   for standardisation:  apatite, chromite, diopside, kaersutite,\n         with analyzable areas of <20 mm) and only two out of 24 were   magnetite, olivine, orthoclase, pentlandite, rhodonite, rutile\n          successfully analysed by EPMA.42                          and tugtupite (ESI Table 1\u2020). All chemical data presented in this\n                                                                       study are presented as oxide weight percent where oxygen has\n       3.  Methodology                               been calculated by stoichiometry in AZtec, with the exception of\n                                                                       Cl (element %). Standard phases were analysed for 2M counts,\n         This study uses a Tescan S-8000 FE-SEM operating under high  and as the instrument is collecting 100k counts per second, and\n        vacuum conditions, \ue103tted with four 170 mm2 Ultim Max EDX  has a dead time of c. 15%, each analysis took approximately 25\n          detectors running the Oxford Instruments AZtec microanalysis\n\n\n\n           This journal is \u00a9 The Royal Society of Chemistry 2024                                                    J. Anal. At. Spectrom., 2024, 39, 2565\u20132579  | 2567                                                                                                                                        View Article Online\n\n      JAAS                                                                                        Paper\n\n\n         seconds. Standardisation is undertaken at the start of each day/   K, Cl). To quantify the risk of loss of mobile and volatile\n          session.                                                      elements, consecutive analysis under increasing count times on\n            Following SEM setup for  fully quanti\ue103ed EDX analysis,  both the basaltic and rh\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052, pqac-00000053, pqac-00000054, pqac-00000055]\n\nStatus: Paper Count=23 | Relevant Papers=17 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=56 | Current Cost=$0.2725 | Disease-Target Evidence=0",
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+                  "end_ts": 3110.060027675
+                }
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+              {
+                "role": "tool",
+                "content": "No relevant evidence found for your question.\n\nArtifact IDs that may be injected into the answer: []\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052, pqac-00000053, pqac-00000054, pqac-00000055]\n\nStatus: Paper Count=23 | Relevant Papers=17 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=56 | Current Cost=$0.3082 | Disease-Target Evidence=0",
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+                }
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+              {
+                "role": "assistant",
+                "content": "I have extensive evidence now. Let me update my plan and start creating artifacts and the final answer. Let me mark objectives as completed and gather any remaining gaps:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01LvbMj9QNiv1dUfwumiuitp",
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+                      "arguments": "{\"plan_objective_id\": 1, \"updated_plan_objective_json\": \"{\\\"id\\\": 1, \\\"objective\\\": \\\"Research ionization cross-section physics and overvoltage ratio optimization\\\", \\\"rationale\\\": \\\"Need to trace the physics basis for the U0 ~ 2-3 recommendation\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\\\", \\\"evaluation\\\": \\\"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\\\"}\"}",
+                      "name": "update_plan"
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+              },
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+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models (paralyzable/non-paralyzable) and the derivation of the 20-40% dead-time guidance for optimal throughput\",\n      \"rationale\": \"Need to explain the counting-rate optimization that yields the dead-time recommendation\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\",\n      \"rationale\": \"Need to explain the detector electronics basis for process time recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_01LvbMj9QNiv1dUfwumiuitp",
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+                  "start_ts": 3171.64280487,
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+                      "arguments": "{\"plan_objective_id\": 2, \"updated_plan_objective_json\": \"{\\\"id\\\": 2, \\\"objective\\\": \\\"Research dead-time models and throughput optimization\\\", \\\"rationale\\\": \\\"Need to explain the counting-rate optimization\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\\\", \\\"evaluation\\\": \\\"Comprehensive coverage of dead-time models with both physics and practical recommendations.\\\"}\"}",
+                      "name": "update_plan"
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+                  {
+                    "id": "toolu_01LAfPYdGfcVfrw8uwURVK9w",
+                    "type": "function",
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+                      "arguments": "{\"plan_objective_id\": 3, \"updated_plan_objective_json\": \"{\\\"id\\\": 3, \\\"objective\\\": \\\"Research pulse shaping/process time trade-offs\\\", \\\"rationale\\\": \\\"Need to explain detector electronics basis for process time recommendations\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\\\", \\\"evaluation\\\": \\\"Good evidence on the noise components and practical trade-off.\\\"}\"}",
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+                      "name": "update_plan"
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+                    "id": "toolu_01LjHXC2RdKS4eFATSnriEaW",
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+                      "name": "update_plan"
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+                    "id": "toolu_013cjc4ZTDfJeRTWB8b8TZJn",
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+                      "arguments": "{\"plan_objective_id\": 6, \"updated_plan_objective_json\": \"{\\\"id\\\": 6, \\\"objective\\\": \\\"Research low-voltage microanalysis and trace-element quantification shifts\\\", \\\"rationale\\\": \\\"Need to explain how parameter optima shift for low-kV and trace analysis\\\", \\\"status\\\": \\\"completed\\\", \\\"result\\\": \\\"Found Newbury 2019 discussion of 5 keV beam energy as lowest for all elements, requirement to use unfamiliar X-ray families (Ba M-family), challenges with absorption and surface layers. Rinaldi 2015 discusses systematic errors in transition element analysis at low kV. Wuhrer 2016 covers reduced interaction volume and shift to L/M lines. Golla-Schindler 2026 on lithium detection. Newbury shows CDL of 200-500 ppm achievable in <500s at conventional voltages.\\\", \\\"evaluation\\\": \\\"Good coverage of low-kV challenges and trace analysis capabilities.\\\"}\"}",
+                      "name": "update_plan"
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+                      "arguments": "{\"plan_objective_id\": 7, \"updated_plan_objective_json\": \"{\\\"id\\\": 7, \\\"objective\\\": \\\"Create summary artifacts and submit final answer\\\", \\\"rationale\\\": \\\"Synthesize all findings into a comprehensive answer\\\", \\\"status\\\": \\\"in-progress\\\", \\\"result\\\": null, \\\"evaluation\\\": null}\"}",
+                      "name": "update_plan"
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+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs in Si(Li) and SDD detectors - electronic noise vs. series noise, ballistic deficit, resolution vs. throughput\",\n      \"rationale\": \"Need to explain the detector electronics basis for process time recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
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+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics for precision (10^4 counts \u2192 1% RSD) and Currie's 1968 derivation of detection limits (3.29-sigma criterion)\",\n      \"rationale\": \"Need to trace the statistical foundations of count-time and detection-limit recommendations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
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+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics and Currie detection limits\",\n      \"rationale\": \"Need to trace statistical foundations\",\n      \"status\": \"completed\",\n      \"result\": \"Found Currie 1999 review paper with full derivation of detection decisions: LC = 1.645*sigma0, LD = 2*LC = 3.29*sigma0 (for alpha=beta=0.05, Gaussian), LQ = 10*sigma0. Also found Newbury 2019 CDL formula CDL = [3*NB^0.5/(NS-NB)]*CS. Rinaldi quotes Ziebold 1967 CDL formula. These trace back to Currie's 1968 Analytical Chemistry paper.\",\n      \"evaluation\": \"Excellent coverage with primary source (Currie) and application in EDS context.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards development process and round-robin studies that validated these parameter choices\",\n      \"rationale\": \"Need to distinguish genuine optima from committee conventions\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_0176umtLhJ54syS43ZRxDp2i",
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+                  "start_ts": 3241.666356741,
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+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics and Currie detection limits\",\n      \"rationale\": \"Need to trace statistical foundations\",\n      \"status\": \"completed\",\n      \"result\": \"Found Currie 1999 review paper with full derivation of detection decisions: LC = 1.645*sigma0, LD = 2*LC = 3.29*sigma0 (for alpha=beta=0.05, Gaussian), LQ = 10*sigma0. Also found Newbury 2019 CDL formula CDL = [3*NB^0.5/(NS-NB)]*CS. Rinaldi quotes Ziebold 1967 CDL formula. These trace back to Currie's 1968 Analytical Chemistry paper.\",\n      \"evaluation\": \"Excellent coverage with primary source (Currie) and application in EDS context.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards and round-robin studies\",\n      \"rationale\": \"Distinguish optima from conventions\",\n      \"status\": \"completed\",\n      \"result\": \"Found ISO 22309:2011 specifies overvoltage of at least 1.8 for quantitative analysis from Tong 2026. Newbury 2015 shows that the k-ratio/matrix correction protocol achieves ~2.5% relative standard deviation accuracy based on 1975 WDS data. Guyett 2024 recommends minimum 1M counts for major elements. No specific round-robin studies for EDS parameter settings were found - these are largely physics-derived optima codified by committees.\",\n      \"evaluation\": \"Partial coverage - clear that standards draw on physics models rather than systematic round-robin validation of parameter ranges.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis (\u22645 kV) and trace-element quantification shifts, especially Newbury & Ritchie work on low-voltage SEM/EDS\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis scenarios like Mg K\u03b1 in AlSi10Mg at 5 kV\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
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+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics and Currie detection limits\",\n      \"rationale\": \"Need to trace statistical foundations\",\n      \"status\": \"completed\",\n      \"result\": \"Found Currie 1999 review paper with full derivation of detection decisions: LC = 1.645*sigma0, LD = 2*LC = 3.29*sigma0 (for alpha=beta=0.05, Gaussian), LQ = 10*sigma0. Also found Newbury 2019 CDL formula CDL = [3*NB^0.5/(NS-NB)]*CS. Rinaldi quotes Ziebold 1967 CDL formula. These trace back to Currie's 1968 Analytical Chemistry paper.\",\n      \"evaluation\": \"Excellent coverage with primary source (Currie) and application in EDS context.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards and round-robin studies\",\n      \"rationale\": \"Distinguish optima from conventions\",\n      \"status\": \"completed\",\n      \"result\": \"Found ISO 22309:2011 specifies overvoltage of at least 1.8 for quantitative analysis from Tong 2026. Newbury 2015 shows that the k-ratio/matrix correction protocol achieves ~2.5% relative standard deviation accuracy based on 1975 WDS data. Guyett 2024 recommends minimum 1M counts for major elements. No specific round-robin studies for EDS parameter settings were found - these are largely physics-derived optima codified by committees.\",\n      \"evaluation\": \"Partial coverage - clear that standards draw on physics models rather than systematic round-robin validation of parameter ranges.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis and trace-element quantification shifts\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis\",\n      \"status\": \"completed\",\n      \"result\": \"Found Newbury 2019 discussion of 5 keV beam energy as lowest for all elements, requirement to use unfamiliar X-ray families (Ba M-family), challenges with absorption and surface layers. Rinaldi 2015 discusses systematic errors in transition element analysis at low kV. Wuhrer 2016 covers reduced interaction volume and shift to L/M lines. Golla-Schindler 2026 on lithium detection. Newbury shows CDL of 200-500 ppm achievable in <500s at conventional voltages.\",\n      \"evaluation\": \"Good coverage of low-kV challenges and trace analysis capabilities.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer with proper citations\",\n      \"status\": \"pending\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_013cjc4ZTDfJeRTWB8b8TZJn",
+                "info": {
+                  "start_ts": 3241.667201719,
+                  "end_ts": 3241.667556316
+                }
+              },
+              {
+                "role": "tool",
+                "content": "Updated plan:\n{\n  \"objectives\": [\n    {\n      \"id\": 1,\n      \"objective\": \"Research ionization cross-section physics and overvoltage ratio optimization\",\n      \"rationale\": \"Need to trace the physics basis for the U0 ~ 2-3 recommendation\",\n      \"status\": \"completed\",\n      \"result\": \"Found information from Rinaldi & Llovet review, Goldstein textbook, Newbury & Ritchie papers, and Tong & Mingard measurement uncertainty report. ISO 22309:2011 specifies overvoltage of at least 1.8. Goldstein text mentions E0/Ec > 1.5 as minimum and E0=20 keV providing sufficient overvoltage for K-shell to Br and L-shell to Bi. The Bethe cross-section formula is well documented in the primary literature (Powell et al.). Green & Cosslett measured X-ray production efficiencies. The competing electron-range growth (Kanaya-Okayama) reduces spatial resolution with increasing voltage.\",\n      \"evaluation\": \"Good coverage of the trade-off physics, supplemented by established references from the Goldstein textbook and review papers.\"\n    },\n    {\n      \"id\": 2,\n      \"objective\": \"Research dead-time models and throughput optimization\",\n      \"rationale\": \"Need to explain the counting-rate optimization\",\n      \"status\": \"completed\",\n      \"result\": \"Found detailed dead-time discussion in Goldstein 2018 (EDS chapter showing OCR vs ICR plots, dead-time percentage formula, anti-coincidence function), Donovan 2023 (dead-time correction expressions including traditional linear, Willis 2-term, 6-term, and logarithmic models), and Goldstein quantitative chapter (noting Si(Li)-EDS classic strategy of 30% DT, SDD-EDS recommendation of <10% DT to avoid coincidence peaks). The paralyzable behavior where OCR eventually falls to zero is shown in Fig. 16.9.\",\n      \"evaluation\": \"Comprehensive coverage of dead-time models with both physics and practical recommendations.\"\n    },\n    {\n      \"id\": 3,\n      \"objective\": \"Research pulse shaping/process time trade-offs\",\n      \"rationale\": \"Need to explain detector electronics basis for process time recommendations\",\n      \"status\": \"completed\",\n      \"result\": \"Found SDD noise equation from Lechner 2004 (ENC^2 = serial white + 1/f + parallel noise), Goldstein 2018 discussion of process time trade-off (resolution vs throughput vs coincidence rate), Blaj 2017 on waveform fitting alternatives, Niculae 2006 on readout configurations, and Schlosser 2010 on optimizing shaping time. The 3-way trade-off between resolution, throughput, and coincidence rate is well documented.\",\n      \"evaluation\": \"Good evidence on the noise components and practical trade-off.\"\n    },\n    {\n      \"id\": 4,\n      \"objective\": \"Research Poisson counting statistics and Currie detection limits\",\n      \"rationale\": \"Need to trace statistical foundations\",\n      \"status\": \"completed\",\n      \"result\": \"Found Currie 1999 review paper with full derivation of detection decisions: LC = 1.645*sigma0, LD = 2*LC = 3.29*sigma0 (for alpha=beta=0.05, Gaussian), LQ = 10*sigma0. Also found Newbury 2019 CDL formula CDL = [3*NB^0.5/(NS-NB)]*CS. Rinaldi quotes Ziebold 1967 CDL formula. These trace back to Currie's 1968 Analytical Chemistry paper.\",\n      \"evaluation\": \"Excellent coverage with primary source (Currie) and application in EDS context.\"\n    },\n    {\n      \"id\": 5,\n      \"objective\": \"Research ISO/ASTM standards and round-robin studies\",\n      \"rationale\": \"Distinguish optima from conventions\",\n      \"status\": \"completed\",\n      \"result\": \"Found ISO 22309:2011 specifies overvoltage of at least 1.8 for quantitative analysis from Tong 2026. Newbury 2015 shows that the k-ratio/matrix correction protocol achieves ~2.5% relative standard deviation accuracy based on 1975 WDS data. Guyett 2024 recommends minimum 1M counts for major elements. No specific round-robin studies for EDS parameter settings were found - these are largely physics-derived optima codified by committees.\",\n      \"evaluation\": \"Partial coverage - clear that standards draw on physics models rather than systematic round-robin validation of parameter ranges.\"\n    },\n    {\n      \"id\": 6,\n      \"objective\": \"Research low-voltage microanalysis and trace-element quantification shifts\",\n      \"rationale\": \"Need to explain how parameter optima shift for low-kV and trace analysis\",\n      \"status\": \"completed\",\n      \"result\": \"Found Newbury 2019 discussion of 5 keV beam energy as lowest for all elements, requirement to use unfamiliar X-ray families (Ba M-family), challenges with absorption and surface layers. Rinaldi 2015 discusses systematic errors in transition element analysis at low kV. Wuhrer 2016 covers reduced interaction volume and shift to L/M lines. Golla-Schindler 2026 on lithium detection. Newbury shows CDL of 200-500 ppm achievable in <500s at conventional voltages.\",\n      \"evaluation\": \"Good coverage of low-kV challenges and trace analysis capabilities.\"\n    },\n    {\n      \"id\": 7,\n      \"objective\": \"Create summary artifacts and submit final answer\",\n      \"rationale\": \"Synthesize all findings into a comprehensive answer\",\n      \"status\": \"in-progress\",\n      \"result\": null,\n      \"evaluation\": null\n    }\n  ]\n}",
+                "name": "update_plan",
+                "tool_call_id": "toolu_014nQAVXyspk8reByMm6jy2f",
+                "info": {
+                  "start_ts": 3241.667926566,
+                  "end_ts": 3241.668201184
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me create the summary artifact:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01HPJEhVJGXA7Cf94zmw4US7",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"artifact_type\": \"table\", \"description\": \"Create a comprehensive summary table of the five main SEM-EDS acquisition parameters (overvoltage ratio, dead time, process/shaping time, counting statistics/live time, and detection limit criterion), showing for each: the recommended value, the underlying physics model or derivation, the key primary literature reference, whether it represents a true optimum or an empirical convention, and how it shifts for low-voltage/trace analysis.\"}",
+                      "name": "create_artifact"
+                    }
+                  }
+                ],
+                "info": null
+              },
+              {
+                "role": "tool",
+                "content": "### Artifact (ID artifact-00)\n\n| Parameter | Common recommended value | How the number was derived | Key primary literature / anchor reference | True optimum or convention? | Shift at low-kV / trace analysis |\n|---|---|---|---|---|---|\n| Overvoltage ratio U0 = E0/Ec | Typically ~2\u20133; ISO floor for quant often stated as \u22651.8 | From the inner-shell ionization cross-section rising steeply just above threshold and then flattening or declining in benefit per added kV, as described by Bethe-type formulations and later evaluated by Powell, Llovet, and Salvat; thick-target X-ray production efficiency measurements by Green and Cosslett showed characteristic yield peaking broadly near modest overvoltage, not at the highest beam energy. The competing penalty is that electron range and interaction volume grow strongly with E0, approximately by Kanaya\u2013Okayama scaling, while phi(rho-z) depth distributions show X-ray generation moving deeper, increasing absorption and reducing spatial resolution. Thus the rule came from maximizing useful characteristic production per unit interaction volume, not from committee preference alone. (pqac-00000007, pqac-00000008, pqac-00000028, pqac-00000043, pqac-00000050, pqac-00000053) | Bethe theory; Green and Cosslett 1961, 1968 measurements; Kanaya and Okayama 1972; Castaing-origin phi(rho-z) framework as summarized in later reviews | Mostly a genuine physics optimum, but broad rather than sharp; committees codified a robust operating zone | At \u22645 keV the optimum is often driven by line accessibility and spatial resolution rather than by the classic 2\u20133 rule alone; one may accept lower overvoltage (~1.25\u20131.8) to keep the interaction volume small or to reach only available L or M lines, with increased sensitivity to absorption, surface films, and matrix-correction error. For Mg K-alpha at 5 keV, U0 \u2248 5/1.254 \u2248 4.0: excitation is ample, but the practical limit becomes background, absorption, and overlap handling rather than insufficient ionization. (pqac-00000043, pqac-00000045, pqac-00000028, pqac-00000029, pqac-00000030) |\n| Detector dead time / throughput | Historically ~20\u201340% for Si(Li); modern standards-based SDD quant often kept much lower, commonly <10\u201315% on the most intense peak if coincidence artifacts matter | Derived from counting-system dead-time theory. For a paralyzable model, stored rate behaves approximately as OCR = ICR \u00d7 exp(-ICR \u00d7 tau), which peaks at ICR \u00d7 tau = 1, i.e. 36.8% dead time; for a non-paralyzable model OCR = ICR/(1 + ICR \u00d7 tau), throughput keeps rising but with diminishing returns. Real EDS electronics also have anti-coincidence rejection and pile-up artifacts, so the practical maximum useful throughput occurs before the mathematical maximum if sum peaks will compromise quantification. Goldstein shows OCR\u2013ICR curves and coincidence-peak growth; Donovan shows why simple linear dead-time correction breaks down at higher rates. (pqac-00000009, pqac-00000011, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049) | Classic dead-time theory; modern microanalysis implementation in Goldstein and Donovan | A real throughput optimum exists mathematically, but the widely taught 20\u201340% band is partly a practical convention balancing throughput against pile-up; with SDD quantitative work the optimum for accuracy often shifts lower | For low-kV and trace work, keep dead time lower because weak trace peaks can be hidden by coincidence peaks and by calibration or resolution drift at high rates. Modern SDDs can run at high OCR, but if looking for 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, a conservative dead time (~10\u201320%, or even lower if sum peaks intrude) is usually preferable to maximize spectral cleanliness. (pqac-00000009, pqac-00000046, pqac-00000054, pqac-00000055) |\n| Pulse processor shaping / process time | Choose a moderate setting: a few eV worse than best resolution, but far better throughput; avoid adaptive shaping for standards-based quant | Derived from the equivalent-noise-charge minimum. Lechner gives ENC^2 = serial white term proportional to 1/tau + a 1/f term + a parallel-noise term proportional to tau: short shaping times increase series white noise and ballistic-deficit sensitivity; long shaping times increase parallel-noise contribution and pile-up probability. Therefore the optimum is at the broad minimum of ENC versus shaping time, then adjusted upward or downward depending on count-rate needs. Goldstein describes the three-way trade-off among resolution, throughput, and coincidence rate; Schlosser and Niculae show measured FWHM versus shaping time for SDDs. (pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027) | Semiconductor-detector noise theory; Lechner 2004; Niculae 2006; Schlosser 2010; later digital-pulse work such as Blaj 2017 | Genuine electronics optimum, but broad; the exact chosen setting is instrument-specific and thus partly conventional in practice | At low-kV, low-energy peaks are narrow and often crowded, so somewhat longer shaping than for fast mapping may be justified if resolving Mg, Al, Si low-energy structure matters. For trace analysis, prioritize stability and peak shape over absolute OCR; sacrificing a small amount of throughput for cleaner low-energy deconvolution is often worthwhile. (pqac-00000015, pqac-00000016, pqac-00000025, pqac-00000030) |\n| Live time / counts for precision | Rule of thumb: ~10,000 net counts in a peak of interest gives ~1% counting RSD; major-element whole-spectrum quant often uses 10^6 total counts or more | Pure Poisson statistics: for net peak counts N, sigma/N \u2248 1/sqrt(N). Thus N = 10^4 gives 1% relative standard deviation from counting alone. Real net-peak precision is worse when background subtraction is needed, so standards and unknowns both require sufficient dose. Newbury and Goldstein tables separate counting error from matrix-correction error; Guyett empirically found >10^5 counts gives <5% RSD for >1.5 wt% oxides and recommends ~10^6 counts for robust quantitative SEM-EDX of majors. (pqac-00000006, pqac-00000008, pqac-00000034, pqac-00000041, pqac-00000043, pqac-00000054) | Poisson counting law; Ziebold 1967 sensitivity framework; Currie 1968 and 1999 for limits; Newbury and Ritchie applications | This is a true statistical relationship, not convention; the exact count targets are practical translations of desired precision | Low-kV reduces continuum volume but often lowers usable peak-to-background and can worsen matrix sensitivity for low-energy lines, so more counts may be needed than the simple 10^4 rule suggests. For 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, several 10^5 to ~10^6 total counts, or repeated acquisitions summed after drift or damage checks, is more realistic if one wants robust sub-wt% precision. (pqac-00000034, pqac-00000036, pqac-00000038, pqac-00000054) |\n| Detection criterion | Currie 3-sigma family: LC = 1.645 sigma0, LD = 3.29 sigma0 for alpha = beta = 0.05; often simplified in practice to 3 sigma detection | Currie\u2019s 1968 hypothesis-testing framework separated the decision threshold LC from the true minimum detectable amount LD. Under Gaussian, homoscedastic approximation and equal Type-I and Type-II risks of 0.05, LC = 1.645 sigma0, and LD = LC + 1.645 sigmaD \u2248 3.29 sigma0. For counting data, sigma is usually controlled by blank or background counts, which is why detection capability depends on the background under the peak. Newbury expresses the same idea in concentration form as CDL = [3 \u00d7 sqrt(NB)/(NS \u2212 NB)] \u00d7 CS. (pqac-00000018, pqac-00000021, pqac-00000022, pqac-00000034, pqac-00000051) | Currie 1968; Currie 1999 retrospective; Ziebold 1967 concentration sensitivity expression | A genuine statistical derivation; the casual phrase 3-sigma is a simplified convention for Currie\u2019s more exact 3.29-sigma detection limit | At low-kV the blank and low-energy artifacts become more dominant, so sigma is often set by background modeling, contamination, and deconvolution residuals rather than by raw peak counts alone. For Mg K-alpha at 0.5\u20131 wt% in AlSi10Mg at 5 keV, formal detectability is usually not the bottleneck; reliable quantification is limited more by standards and matrix-correction quality, low-energy peak fitting, and reproducibility than by passing the Currie decision threshold. (pqac-00000030, pqac-00000034, pqac-00000043, pqac-00000053) |\n\n\n*Table: This table summarizes how the standard SEM-EDS acquisition parameters were justified from physics, electronics, and counting statistics rather than merely adopted by standards committees. It also shows which values are true optima, which are practical conventions, and how they shift for low-voltage and trace-level analysis.*\n\nArtifact IDs that may be injected into the answer: [artifact-00]\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052, pqac-00000053, pqac-00000054, pqac-00000055]\n\nStatus: Paper Count=23 | Relevant Papers=17 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=56 | Current Cost=$0.3082 | Disease-Target Evidence=0",
+                "name": "create_artifact",
+                "tool_call_id": "toolu_01HPJEhVJGXA7Cf94zmw4US7",
+                "info": {
+                  "start_ts": 3286.524676973,
+                  "end_ts": 3330.060917384
+                }
+              },
+              {
+                "role": "assistant",
+                "content": "Now let me submit the final answer:",
+                "function_call": null,
+                "tool_calls": [
+                  {
+                    "id": "toolu_01To6D5aZkas3GaXaK16pA6C",
+                    "type": "function",
+                    "function": {
+                      "arguments": "{\"answer\": \"## Derivation of Recommended Acquisition Parameters in SEM-EDS: From Physics Models to Standard Practice\\n\\n### 1. Overvoltage Ratio (U\\u2080 \\u2248 2\\u20133)\\n\\nThe recommendation to set the accelerating voltage E\\u2080 at roughly two to three times the critical excitation energy Ec of the highest-energy line of interest (i.e., overvoltage U\\u2080 = E\\u2080/Ec \\u2248 2\\u20133) derives from the interplay of three physics models.\\n\\n**Ionization cross-section.** The Bethe (1930) formulation of the inner-shell ionization cross-section Q predicts that Q rises steeply from the threshold (U = 1), passes through a broad maximum at overvoltages of a few (typically U \\u2248 2\\u20134 depending on the shell and the specific formulation), and then decreases slowly as ln(U)/U at high overvoltages. Green and Cosslett (1961, 1968) validated this behavior experimentally by measuring K-, L-, and M-shell X-ray production efficiencies from thick pure-element targets bombarded by electrons, confirming that characteristic X-ray yield per unit beam current rises rapidly above threshold but saturates at modest overvoltages. Powell, Llovet, and Salvat (2016) later evaluated the accuracy of the Bethe equation against distorted-wave Born-approximation calculations and experiment, finding that the Bethe formula provides a useful approximation in the overvoltage range relevant to microanalysis. These studies collectively established that the marginal gain in ionization efficiency diminishes above U \\u2248 2\\u20133.\\n\\n**Electron range and interaction volume.** Countering the benefit of higher overvoltage, the electron range R in a solid scales approximately as E\\u2080^1.67/\\u03c1 in the Kanaya\\u2013Okayama (1972) formulation. This means that raising E\\u2080 expands the interaction volume roughly as R\\u00b3, degrading lateral and depth spatial resolution. As Goldstein et al. (2018) note, the beam energy of 20 keV provides sufficient overvoltage (E\\u2080/Ec > 1.5) for K-shell excitation up to Br and L-shell excitation up to Bi, with photon energies up to ~12 keV (pqac-00000007). Reducing E\\u2080 from 20 to 10 keV substantially reduces the absorption correction factor uncertainty, as demonstrated for the FeS system where the S absorption factor dropped from 1.118 to 1.04, improving the relative error from 1.0% to 0.59% (pqac-00000008).\\n\\n**Depth distribution \\u03d5(\\u03c1z).** Castaing's original tracer experiments (1951 onward) measured the distribution of X-ray production with depth by sandwiching a thin marker layer of known composition at varying depths within a substrate, establishing the \\u03d5(\\u03c1z) function that forms the basis of ZAF and \\u03d5(\\u03c1z) matrix corrections. The \\u03d5(\\u03c1z) function shows that at high overvoltage, X-ray production extends deeper into the specimen, increasing absorption losses and reducing the fraction of generated X-rays that escape to the detector. This provides the physics basis for the practical rule: the overvoltage of ~2\\u20133 sits near the broad maximum of the ratio of useful (escaped) characteristic signal to interaction volume. ISO 22309:2011 codified this as a minimum overvoltage of 1.8 for quantitative analysis (pqac-00000053). Goldstein et al. recommend E\\u2080/Ec > 1.5 as a minimum and note that a beam energy of 5 keV is the lowest at which at least one characteristic X-ray peak can be excited for all elements except H and He (pqac-00000043).\\n\\n### 2. Dead-Time and Throughput Optimization (20\\u201340% Historical; \\u226410% for Modern SDD)\\n\\nThe dead-time recommendation comes directly from detector counting-rate theory. X-rays arrive randomly, but the EDS can process only one photon at a time. The dead-time percentage is defined as DT(%) = (ICR \\u2212 OCR)/ICR \\u00d7 100%, where ICR is the input count rate and OCR is the output count rate (pqac-00000046, pqac-00000011).\\n\\n**Paralyzable model.** For a truly paralyzable (extending) dead-time system, the output count rate is OCR = ICR \\u00d7 exp(\\u2212ICR \\u00d7 \\u03c4), where \\u03c4 is the dead-time constant per event. This function has a maximum at ICR = 1/\\u03c4, corresponding to a dead-time fraction of 1 \\u2212 1/e \\u2248 63.2%. Beyond this point, further increases in ICR actually decrease OCR\\u2014the system paralyzes. In practice, the useful operating range is well below this mathematical maximum because (a) the dead-time correction accuracy degrades at high rates, and (b) coincidence (sum/pile-up) peaks grow rapidly.\\n\\n**Non-paralyzable model.** For a non-paralyzable system, OCR = ICR/(1 + ICR \\u00d7 \\u03c4). The OCR rises monotonically but with diminishing returns, and dead-time correction is mathematically straightforward. Real EDS systems exhibit behavior between these two limits, with modern SDD digital pulse processors closer to non-paralyzable at moderate rates.\\n\\n**Practical optimum.** The classic Si(Li)-EDS strategy was to operate at \\u226430% dead-time on a strongly excited pure element standard (pqac-00000009). With modern SDD-EDS, Goldstein et al. recommend a more conservative approach: keeping dead-time below 10% on the most highly excited standard because coincidence peaks become significant above this threshold, particularly when trace constituents must be measured in spectral regions affected by sum peaks (pqac-00000009). At 3% dead-time, coincidence artifacts are minimal; at 29% dead-time on the same glass K412, extensive coincidence peaks (Al+Al, Si+O, Si+Mg, Si+Si, Si+Ca, Mg+Ca) become visible (pqac-00000009). Donovan et al. (2023) showed that the traditional linear dead-time correction expression Icps = icps/(1 \\u2212 icps\\u00b7\\u03c4) becomes inaccurate above ~50 kcps, requiring higher-order correction expressions (Willis 2-term, 6-term expansion, or logarithmic models) for accurate quantification at higher count rates (pqac-00000048, pqac-00000047).\\n\\nThus the 20\\u201340% guidance for Si(Li) detectors was a practical compromise maximizing stored counts while keeping dead-time correction errors tolerable; the shift to \\u226410% for SDD-based quantitative work reflects the greater throughput capacity of SDDs and the more stringent demands of modern peak fitting for trace analysis.\\n\\n### 3. Pulse Process Time (Shaping Time): Electronic Noise Trade-off\\n\\nThe choice of process time (also called shaping time, time constant, or throughput setting) in EDS is governed by a fundamental noise trade-off in the front-end electronics (pqac-00000015, pqac-00000002).\\n\\n**Noise components.** Lechner et al. (2004) express the equivalent noise charge (ENC) of an SDD as:\\n\\nENC\\u00b2 = (2k\\u1d66T/g\\u2098)\\u00b7C\\u00b2\\u00b7A\\u2081/\\u03c4 + afC\\u00b2\\u00b7A\\u2082 + q\\u00b7Il\\u00b7A\\u2083\\u00b7\\u03c4\\n\\nwhere the three terms represent serial white noise (proportional to 1/\\u03c4, dominated by detector capacitance C and FET transconductance g\\u2098), 1/f noise (independent of \\u03c4), and parallel noise (proportional to \\u03c4, dominated by leakage current Il) (pqac-00000026). At short shaping times, the serial (voltage) noise dominates and energy resolution degrades hyperbolically; at long shaping times, the parallel (current) noise and pile-up probability increase. The optimal shaping time sits at the broad minimum of ENC versus \\u03c4, typically around 0.5\\u20133 \\u03bcs for SDDs depending on detector area, temperature, and capacitance (pqac-00000025, pqac-00000027).\\n\\n**Practical implementation.** Goldstein et al. describe the trade-off as three-way: throughput, resolution, and coincidence rate. Longer process times achieve better resolution but poor throughput; shorter process times maximize throughput but increase coincidence events. The optimal setting for quantitative analysis is a moderate process time that degrades resolution by only a few percent (e.g., from 122\\u2013128 eV to 130\\u2013135 eV FWHM at Mn K\\u03b1) while substantially increasing throughput (pqac-00000015, pqac-00000014). Modern SDDs with 500 ns time constants can achieve resolution below 130 eV at Mn K\\u03b1 while maintaining maximum OCR of ~130 kHz per detector chip (pqac-00000016). The precision of quantitative analysis is more determined by the number of measured X-rays than by spectral resolution alone (pqac-00000015). Critically, for standards-based analysis, the same process time must be used for all standards and unknowns; adaptive process times that change resolution with throughput make spectrum fitting challenging and less accurate (pqac-00000002).\\n\\n### 4. Counting Statistics: Why ~10\\u2074 Counts Gives ~1% RSD\\n\\nThe count-time recommendation derives directly from Poisson counting statistics. For a measured number of counts N drawn from a Poisson process, the standard deviation is \\u03c3 = \\u221aN, so the relative standard deviation (RSD) is \\u03c3/N = 1/\\u221aN. Thus:\\n\\n- N = 10\\u2074 \\u2192 RSD = 1%\\n- N = 10\\u2076 \\u2192 RSD = 0.1%\\n- N = 10\\u00b2 \\u2192 RSD = 10%\\n\\nThis is a mathematical identity, not an empirical convention. Newbury and Ritchie (2019) tabulate the separate contributions of counting error, absorption-factor error, and atomic-number-factor error to the combined uncertainty budget for standards-based SDD-EDS analysis. For example, in the analysis of FeS at 20 keV with 7 \\u00d7 10\\u2076 integrated spectrum counts, the counting error for the standard contributes \\u00b10.0002 mass fraction and for the unknown \\u00b10.0007, while the absorption factor error dominates at \\u00b10.0017 (pqac-00000006). This demonstrates that at sufficiently high counts, counting statistics become a minor contributor and systematic errors (matrix corrections) dominate.\\n\\nGuyett et al. (2024) empirically validated the counting precision relationship for glass analyses: with only 10k\\u201320k total counts (<1 s acquisition), RSD exceeded 5% even for major element oxides above 10 wt%; above 100k counts, all elements above 1.5 wt% exhibited RSD < 5%; and above 1M counts, major element oxide RSD was consistently below 2% (pqac-00000054). They recommended a minimum of 1M total spectrum counts for fully quantitative major-element SEM-EDX analysis, achievable in approximately 15 seconds with modern multi-detector SDD systems.\\n\\n### 5. Currie's Detection-Limit Framework (the \\\"3-sigma\\\" Criterion)\\n\\nThe widely used \\\"3-sigma\\\" detection criterion traces to Currie's seminal 1968 paper in Analytical Chemistry, which rigorously separated three quantities using hypothesis-testing theory (pqac-00000021, pqac-00000022):\\n\\n1. **Critical value (decision threshold) Lc = z\\u2081\\u208b\\u03b1\\u00b7\\u03c3\\u2080 = 1.645\\u03c3\\u2080** (for \\u03b1 = 0.05): the threshold above which the analyst decides \\\"detected.\\\" This controls only the false-positive rate.\\n\\n2. **Detection limit Ld = Lc + z\\u2081\\u208b\\u03b2\\u00b7\\u03c3d \\u2248 2\\u00d7Lc = 3.29\\u03c3\\u2080** (for \\u03b1 = \\u03b2 = 0.05, homoscedastic Gaussian): the true signal level at which the probability of a false negative is also limited to \\u03b2 = 0.05. The factor 3.29 (not 3) arises from the sum of two one-sided z-quantiles: 1.645 + 1.645 = 3.29.\\n\\n3. **Quantification limit Lq = kq\\u00b7\\u03c3\\u2080 = 10\\u03c3\\u2080** (for 10% RSD at the quantification limit).\\n\\nThe casual shorthand \\\"3-sigma detection limit\\\" conflates the decision threshold (1.645\\u03c3) with the detection limit (3.29\\u03c3) and slightly misquotes the coefficient. Currie (1999) reviewed this confusion, noting that prior approaches ignoring false negatives effectively set \\u03b2 = 0.50, yielding detection capability estimates that differed by up to three orders of magnitude from the hypothesis-testing result (pqac-00000022, pqac-00000018).\\n\\nIn the EDS microanalysis context, Newbury and Ritchie (2019) express the concentration detection limit as CDL = [3\\u221aNB/(NS \\u2212 NB)]\\u00b7CS, where NB is the background counts under the peak, NS is the total peak integral counts, and CS is the known concentration (pqac-00000034). This functional form traces directly to Ziebold's (1967) sensitivity expression CDL > 3.29a/(ntP \\u00d7 P/B)^(1/2), where a relates composition to intensity, n is the number of observations, tP is counting time, and P/B is the peak-to-background ratio (pqac-00000051). Both formulations encode the same Poisson-statistics\\u2013based detection theory.\\n\\n### 6. Standards vs. Genuine Optima vs. Committee Convention\\n\\nThe table below synthesizes how each parameter was derived and whether it represents a true optimum or a codified convention:\\n\\n<artifact id=\\\"artifact-00\\\"/>\\n\\nSeveral observations emerge regarding the nature of these recommendations:\\n\\n- The **overvoltage ratio** of ~2\\u20133 reflects a genuine but broad physics optimum: the Bethe cross-section maximum is broad, and the exact best value depends on whether one prioritizes intensity, spatial resolution, or matrix-correction accuracy. ISO 22309:2011 codified a floor of 1.8, which is a conservative standardization of the physics (pqac-00000053).\\n\\n- The **dead-time** guidance evolved from 20\\u201340% (Si(Li) era, optimizing stored-count rate) to <10% (SDD era, minimizing coincidence peaks for trace analysis) as detector technology changed. No published round-robin explicitly validated the 20\\u201340% range; it was derived from dead-time throughput curves and practical experience (pqac-00000009).\\n\\n- The **process time** setting has a genuine electronics optimum (the ENC minimum), but the commercially available settings and naming conventions differ between vendors, making the specific recommendation partly instrument-dependent (pqac-00000015, pqac-00000026).\\n\\n- The **10,000-count rule** is a direct mathematical consequence of Poisson statistics and is not convention. The translation into specific live-times depends entirely on count rates, which depend on all other parameters.\\n\\n- **Currie's 3.29\\u03c3 detection limit** is a rigorous derivation from Neyman-Pearson hypothesis testing at specified error rates, not an empirical guess. The common simplification to \\\"3\\u03c3\\\" is a minor approximation that has become conventional shorthand (pqac-00000021).\\n\\nRegarding interlaboratory validation, Newbury and Ritchie (2015) demonstrated that the k-ratio/matrix correction protocol with SDD-EDS achieves accuracy matching the WDS distribution established in 1975 (approximately 2.5% relative standard deviation for major constituents, with ~95% of analyses falling within \\u00b15% relative error) (pqac-00000041). However, no published round-robin study was identified that systematically varied EDS acquisition parameters (overvoltage, dead-time, process time) across laboratories to validate the specific recommended ranges. The standards appear to have been written by codifying well-understood physics relationships and experienced practitioners' consensus within ISO TC 202 and ASTM E04 committees.\\n\\n### 7. Shifts for Low-Voltage Microanalysis and Trace Quantification\\n\\n**Low beam energy (\\u22645 keV).** At low voltage, the conventional parameter optima shift significantly. A beam energy of 5 keV represents the lowest value at which at least one characteristic X-ray peak can be excited for all elements of the periodic table except H and He (pqac-00000043). At lower voltages, an increasing number of elements becomes inaccessible. The analyst is forced to use unfamiliar X-ray families (e.g., Ba M-family instead of Ba L-family) which may suffer severe mutual interferences, as demonstrated for YBa\\u2082Cu\\u2083O\\u2087 analyzed at 5 keV where O K, Cu L, and Ba M families overlap (pqac-00000045). Rinaldi and Llovet (2015) documented systematic deviations in transition-element analysis at low voltages (5\\u20136 keV), including Cr underestimation (\\u22120.7% to \\u221217%) and Fe/Ni overestimation (+14% to +42%), attributed to problems with mass absorption coefficients and low fluorescence yields for L-lines (pqac-00000028). The interaction volume reduction (approximately 100-fold decrease from 20 keV to 1 keV) improves spatial resolution to the sub-micrometer scale but reduces absolute X-ray yield per electron, requiring higher beam currents or longer counting times (pqac-00000031). Surface contamination layers and native oxides, which are negligible at 20 keV, become significant contributors to the measured spectrum at low voltage (pqac-00000043).\\n\\n**Trace-element quantification near 0.5\\u20131 wt%.** For Mg K\\u03b1 (1.254 keV) at 0.5\\u20131 wt% in AlSi10Mg measured at 5 keV with an SDD, the overvoltage is generous (U\\u2080 \\u2248 4.0), so excitation efficiency is not limiting. The challenges are instead: (a) the Mg K peak sits in a crowded low-energy region where Al K (1.486 keV) is a dominant neighboring peak; (b) peak-to-background ratios for the Mg peak depend on the continuum modeling and the detector response at low energies; (c) the absorption correction for low-energy photons becomes large and uncertain; and (d) surface contamination carbon deposition can increase absorption of X-rays near the carbon K-edge (0.284 keV) and affect quantification of light elements. Newbury and Ritchie showed that detection limits of 200\\u2013500 ppm (0.02\\u20130.05 wt%) are achievable at conventional voltages within 500 s counting time (pqac-00000034), but at low voltage the effective detection limit for a given counting time may be worse due to increased background relative to peak and poorer matrix-correction accuracy (pqac-00000030). For reliable quantification of 0.5\\u20131 wt% Mg, standards-based analysis with well-characterized standards and careful peak fitting is essential; standardless methods showed ~95% of results within \\u00b125% relative deviation in early testing, an unacceptable error for trace-level work (pqac-00000039). The practical recommendation is to collect substantially more counts than the simple 10\\u2074-count rule would suggest (several 10\\u2075 to 10\\u2076 total spectrum counts), use a moderate process time prioritizing spectral stability over maximum throughput, keep dead time conservatively low to avoid pile-up artifacts in the energy region of interest, and employ multiple replicate measurements with statistical quality-control tests to monitor drift and damage (pqac-00000038, pqac-00000054).\"}",
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+              "content": "### Artifact (ID artifact-00)\n\n| Parameter | Common recommended value | How the number was derived | Key primary literature / anchor reference | True optimum or convention? | Shift at low-kV / trace analysis |\n|---|---|---|---|---|---|\n| Overvoltage ratio U0 = E0/Ec | Typically ~2\u20133; ISO floor for quant often stated as \u22651.8 | From the inner-shell ionization cross-section rising steeply just above threshold and then flattening or declining in benefit per added kV, as described by Bethe-type formulations and later evaluated by Powell, Llovet, and Salvat; thick-target X-ray production efficiency measurements by Green and Cosslett showed characteristic yield peaking broadly near modest overvoltage, not at the highest beam energy. The competing penalty is that electron range and interaction volume grow strongly with E0, approximately by Kanaya\u2013Okayama scaling, while phi(rho-z) depth distributions show X-ray generation moving deeper, increasing absorption and reducing spatial resolution. Thus the rule came from maximizing useful characteristic production per unit interaction volume, not from committee preference alone. (pqac-00000007, pqac-00000008, pqac-00000028, pqac-00000043, pqac-00000050, pqac-00000053) | Bethe theory; Green and Cosslett 1961, 1968 measurements; Kanaya and Okayama 1972; Castaing-origin phi(rho-z) framework as summarized in later reviews | Mostly a genuine physics optimum, but broad rather than sharp; committees codified a robust operating zone | At \u22645 keV the optimum is often driven by line accessibility and spatial resolution rather than by the classic 2\u20133 rule alone; one may accept lower overvoltage (~1.25\u20131.8) to keep the interaction volume small or to reach only available L or M lines, with increased sensitivity to absorption, surface films, and matrix-correction error. For Mg K-alpha at 5 keV, U0 \u2248 5/1.254 \u2248 4.0: excitation is ample, but the practical limit becomes background, absorption, and overlap handling rather than insufficient ionization. (pqac-00000043, pqac-00000045, pqac-00000028, pqac-00000029, pqac-00000030) |\n| Detector dead time / throughput | Historically ~20\u201340% for Si(Li); modern standards-based SDD quant often kept much lower, commonly <10\u201315% on the most intense peak if coincidence artifacts matter | Derived from counting-system dead-time theory. For a paralyzable model, stored rate behaves approximately as OCR = ICR \u00d7 exp(-ICR \u00d7 tau), which peaks at ICR \u00d7 tau = 1, i.e. 36.8% dead time; for a non-paralyzable model OCR = ICR/(1 + ICR \u00d7 tau), throughput keeps rising but with diminishing returns. Real EDS electronics also have anti-coincidence rejection and pile-up artifacts, so the practical maximum useful throughput occurs before the mathematical maximum if sum peaks will compromise quantification. Goldstein shows OCR\u2013ICR curves and coincidence-peak growth; Donovan shows why simple linear dead-time correction breaks down at higher rates. (pqac-00000009, pqac-00000011, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049) | Classic dead-time theory; modern microanalysis implementation in Goldstein and Donovan | A real throughput optimum exists mathematically, but the widely taught 20\u201340% band is partly a practical convention balancing throughput against pile-up; with SDD quantitative work the optimum for accuracy often shifts lower | For low-kV and trace work, keep dead time lower because weak trace peaks can be hidden by coincidence peaks and by calibration or resolution drift at high rates. Modern SDDs can run at high OCR, but if looking for 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, a conservative dead time (~10\u201320%, or even lower if sum peaks intrude) is usually preferable to maximize spectral cleanliness. (pqac-00000009, pqac-00000046, pqac-00000054, pqac-00000055) |\n| Pulse processor shaping / process time | Choose a moderate setting: a few eV worse than best resolution, but far better throughput; avoid adaptive shaping for standards-based quant | Derived from the equivalent-noise-charge minimum. Lechner gives ENC^2 = serial white term proportional to 1/tau + a 1/f term + a parallel-noise term proportional to tau: short shaping times increase series white noise and ballistic-deficit sensitivity; long shaping times increase parallel-noise contribution and pile-up probability. Therefore the optimum is at the broad minimum of ENC versus shaping time, then adjusted upward or downward depending on count-rate needs. Goldstein describes the three-way trade-off among resolution, throughput, and coincidence rate; Schlosser and Niculae show measured FWHM versus shaping time for SDDs. (pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027) | Semiconductor-detector noise theory; Lechner 2004; Niculae 2006; Schlosser 2010; later digital-pulse work such as Blaj 2017 | Genuine electronics optimum, but broad; the exact chosen setting is instrument-specific and thus partly conventional in practice | At low-kV, low-energy peaks are narrow and often crowded, so somewhat longer shaping than for fast mapping may be justified if resolving Mg, Al, Si low-energy structure matters. For trace analysis, prioritize stability and peak shape over absolute OCR; sacrificing a small amount of throughput for cleaner low-energy deconvolution is often worthwhile. (pqac-00000015, pqac-00000016, pqac-00000025, pqac-00000030) |\n| Live time / counts for precision | Rule of thumb: ~10,000 net counts in a peak of interest gives ~1% counting RSD; major-element whole-spectrum quant often uses 10^6 total counts or more | Pure Poisson statistics: for net peak counts N, sigma/N \u2248 1/sqrt(N). Thus N = 10^4 gives 1% relative standard deviation from counting alone. Real net-peak precision is worse when background subtraction is needed, so standards and unknowns both require sufficient dose. Newbury and Goldstein tables separate counting error from matrix-correction error; Guyett empirically found >10^5 counts gives <5% RSD for >1.5 wt% oxides and recommends ~10^6 counts for robust quantitative SEM-EDX of majors. (pqac-00000006, pqac-00000008, pqac-00000034, pqac-00000041, pqac-00000043, pqac-00000054) | Poisson counting law; Ziebold 1967 sensitivity framework; Currie 1968 and 1999 for limits; Newbury and Ritchie applications | This is a true statistical relationship, not convention; the exact count targets are practical translations of desired precision | Low-kV reduces continuum volume but often lowers usable peak-to-background and can worsen matrix sensitivity for low-energy lines, so more counts may be needed than the simple 10^4 rule suggests. For 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, several 10^5 to ~10^6 total counts, or repeated acquisitions summed after drift or damage checks, is more realistic if one wants robust sub-wt% precision. (pqac-00000034, pqac-00000036, pqac-00000038, pqac-00000054) |\n| Detection criterion | Currie 3-sigma family: LC = 1.645 sigma0, LD = 3.29 sigma0 for alpha = beta = 0.05; often simplified in practice to 3 sigma detection | Currie\u2019s 1968 hypothesis-testing framework separated the decision threshold LC from the true minimum detectable amount LD. Under Gaussian, homoscedastic approximation and equal Type-I and Type-II risks of 0.05, LC = 1.645 sigma0, and LD = LC + 1.645 sigmaD \u2248 3.29 sigma0. For counting data, sigma is usually controlled by blank or background counts, which is why detection capability depends on the background under the peak. Newbury expresses the same idea in concentration form as CDL = [3 \u00d7 sqrt(NB)/(NS \u2212 NB)] \u00d7 CS. (pqac-00000018, pqac-00000021, pqac-00000022, pqac-00000034, pqac-00000051) | Currie 1968; Currie 1999 retrospective; Ziebold 1967 concentration sensitivity expression | A genuine statistical derivation; the casual phrase 3-sigma is a simplified convention for Currie\u2019s more exact 3.29-sigma detection limit | At low-kV the blank and low-energy artifacts become more dominant, so sigma is often set by background modeling, contamination, and deconvolution residuals rather than by raw peak counts alone. For Mg K-alpha at 0.5\u20131 wt% in AlSi10Mg at 5 keV, formal detectability is usually not the bottleneck; reliable quantification is limited more by standards and matrix-correction quality, low-energy peak fitting, and reproducibility than by passing the Currie decision threshold. (pqac-00000030, pqac-00000034, pqac-00000043, pqac-00000053) |\n\n\n*Table: This table summarizes how the standard SEM-EDS acquisition parameters were justified from physics, electronics, and counting statistics rather than merely adopted by standards committees. It also shows which values are true optima, which are practical conventions, and how they shift for low-voltage and trace-level analysis.*\n\nArtifact IDs that may be injected into the answer: [artifact-00]\n\nContext IDs that may be cited: [pqac-00000000, pqac-00000001, pqac-00000002, pqac-00000003, pqac-00000004, pqac-00000005, pqac-00000006, pqac-00000007, pqac-00000008, pqac-00000009, pqac-00000010, pqac-00000011, pqac-00000012, pqac-00000013, pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000017, pqac-00000018, pqac-00000019, pqac-00000020, pqac-00000021, pqac-00000022, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027, pqac-00000028, pqac-00000029, pqac-00000030, pqac-00000031, pqac-00000032, pqac-00000033, pqac-00000034, pqac-00000035, pqac-00000036, pqac-00000037, pqac-00000038, pqac-00000039, pqac-00000040, pqac-00000041, pqac-00000042, pqac-00000043, pqac-00000044, pqac-00000045, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049, pqac-00000050, pqac-00000051, pqac-00000052, pqac-00000053, pqac-00000054, pqac-00000055]\n\nStatus: Paper Count=23 | Relevant Papers=17 | Clinical Trial Count=0 | Relevant Clinical Trials=0 | Current Evidence=56 | Current Cost=$0.3082 | Disease-Target Evidence=0",
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+                    "arguments": "{\"answer\": \"## Derivation of Recommended Acquisition Parameters in SEM-EDS: From Physics Models to Standard Practice\\n\\n### 1. Overvoltage Ratio (U\\u2080 \\u2248 2\\u20133)\\n\\nThe recommendation to set the accelerating voltage E\\u2080 at roughly two to three times the critical excitation energy Ec of the highest-energy line of interest (i.e., overvoltage U\\u2080 = E\\u2080/Ec \\u2248 2\\u20133) derives from the interplay of three physics models.\\n\\n**Ionization cross-section.** The Bethe (1930) formulation of the inner-shell ionization cross-section Q predicts that Q rises steeply from the threshold (U = 1), passes through a broad maximum at overvoltages of a few (typically U \\u2248 2\\u20134 depending on the shell and the specific formulation), and then decreases slowly as ln(U)/U at high overvoltages. Green and Cosslett (1961, 1968) validated this behavior experimentally by measuring K-, L-, and M-shell X-ray production efficiencies from thick pure-element targets bombarded by electrons, confirming that characteristic X-ray yield per unit beam current rises rapidly above threshold but saturates at modest overvoltages. Powell, Llovet, and Salvat (2016) later evaluated the accuracy of the Bethe equation against distorted-wave Born-approximation calculations and experiment, finding that the Bethe formula provides a useful approximation in the overvoltage range relevant to microanalysis. These studies collectively established that the marginal gain in ionization efficiency diminishes above U \\u2248 2\\u20133.\\n\\n**Electron range and interaction volume.** Countering the benefit of higher overvoltage, the electron range R in a solid scales approximately as E\\u2080^1.67/\\u03c1 in the Kanaya\\u2013Okayama (1972) formulation. This means that raising E\\u2080 expands the interaction volume roughly as R\\u00b3, degrading lateral and depth spatial resolution. As Goldstein et al. (2018) note, the beam energy of 20 keV provides sufficient overvoltage (E\\u2080/Ec > 1.5) for K-shell excitation up to Br and L-shell excitation up to Bi, with photon energies up to ~12 keV (pqac-00000007). Reducing E\\u2080 from 20 to 10 keV substantially reduces the absorption correction factor uncertainty, as demonstrated for the FeS system where the S absorption factor dropped from 1.118 to 1.04, improving the relative error from 1.0% to 0.59% (pqac-00000008).\\n\\n**Depth distribution \\u03d5(\\u03c1z).** Castaing's original tracer experiments (1951 onward) measured the distribution of X-ray production with depth by sandwiching a thin marker layer of known composition at varying depths within a substrate, establishing the \\u03d5(\\u03c1z) function that forms the basis of ZAF and \\u03d5(\\u03c1z) matrix corrections. The \\u03d5(\\u03c1z) function shows that at high overvoltage, X-ray production extends deeper into the specimen, increasing absorption losses and reducing the fraction of generated X-rays that escape to the detector. This provides the physics basis for the practical rule: the overvoltage of ~2\\u20133 sits near the broad maximum of the ratio of useful (escaped) characteristic signal to interaction volume. ISO 22309:2011 codified this as a minimum overvoltage of 1.8 for quantitative analysis (pqac-00000053). Goldstein et al. recommend E\\u2080/Ec > 1.5 as a minimum and note that a beam energy of 5 keV is the lowest at which at least one characteristic X-ray peak can be excited for all elements except H and He (pqac-00000043).\\n\\n### 2. Dead-Time and Throughput Optimization (20\\u201340% Historical; \\u226410% for Modern SDD)\\n\\nThe dead-time recommendation comes directly from detector counting-rate theory. X-rays arrive randomly, but the EDS can process only one photon at a time. The dead-time percentage is defined as DT(%) = (ICR \\u2212 OCR)/ICR \\u00d7 100%, where ICR is the input count rate and OCR is the output count rate (pqac-00000046, pqac-00000011).\\n\\n**Paralyzable model.** For a truly paralyzable (extending) dead-time system, the output count rate is OCR = ICR \\u00d7 exp(\\u2212ICR \\u00d7 \\u03c4), where \\u03c4 is the dead-time constant per event. This function has a maximum at ICR = 1/\\u03c4, corresponding to a dead-time fraction of 1 \\u2212 1/e \\u2248 63.2%. Beyond this point, further increases in ICR actually decrease OCR\\u2014the system paralyzes. In practice, the useful operating range is well below this mathematical maximum because (a) the dead-time correction accuracy degrades at high rates, and (b) coincidence (sum/pile-up) peaks grow rapidly.\\n\\n**Non-paralyzable model.** For a non-paralyzable system, OCR = ICR/(1 + ICR \\u00d7 \\u03c4). The OCR rises monotonically but with diminishing returns, and dead-time correction is mathematically straightforward. Real EDS systems exhibit behavior between these two limits, with modern SDD digital pulse processors closer to non-paralyzable at moderate rates.\\n\\n**Practical optimum.** The classic Si(Li)-EDS strategy was to operate at \\u226430% dead-time on a strongly excited pure element standard (pqac-00000009). With modern SDD-EDS, Goldstein et al. recommend a more conservative approach: keeping dead-time below 10% on the most highly excited standard because coincidence peaks become significant above this threshold, particularly when trace constituents must be measured in spectral regions affected by sum peaks (pqac-00000009). At 3% dead-time, coincidence artifacts are minimal; at 29% dead-time on the same glass K412, extensive coincidence peaks (Al+Al, Si+O, Si+Mg, Si+Si, Si+Ca, Mg+Ca) become visible (pqac-00000009). Donovan et al. (2023) showed that the traditional linear dead-time correction expression Icps = icps/(1 \\u2212 icps\\u00b7\\u03c4) becomes inaccurate above ~50 kcps, requiring higher-order correction expressions (Willis 2-term, 6-term expansion, or logarithmic models) for accurate quantification at higher count rates (pqac-00000048, pqac-00000047).\\n\\nThus the 20\\u201340% guidance for Si(Li) detectors was a practical compromise maximizing stored counts while keeping dead-time correction errors tolerable; the shift to \\u226410% for SDD-based quantitative work reflects the greater throughput capacity of SDDs and the more stringent demands of modern peak fitting for trace analysis.\\n\\n### 3. Pulse Process Time (Shaping Time): Electronic Noise Trade-off\\n\\nThe choice of process time (also called shaping time, time constant, or throughput setting) in EDS is governed by a fundamental noise trade-off in the front-end electronics (pqac-00000015, pqac-00000002).\\n\\n**Noise components.** Lechner et al. (2004) express the equivalent noise charge (ENC) of an SDD as:\\n\\nENC\\u00b2 = (2k\\u1d66T/g\\u2098)\\u00b7C\\u00b2\\u00b7A\\u2081/\\u03c4 + afC\\u00b2\\u00b7A\\u2082 + q\\u00b7Il\\u00b7A\\u2083\\u00b7\\u03c4\\n\\nwhere the three terms represent serial white noise (proportional to 1/\\u03c4, dominated by detector capacitance C and FET transconductance g\\u2098), 1/f noise (independent of \\u03c4), and parallel noise (proportional to \\u03c4, dominated by leakage current Il) (pqac-00000026). At short shaping times, the serial (voltage) noise dominates and energy resolution degrades hyperbolically; at long shaping times, the parallel (current) noise and pile-up probability increase. The optimal shaping time sits at the broad minimum of ENC versus \\u03c4, typically around 0.5\\u20133 \\u03bcs for SDDs depending on detector area, temperature, and capacitance (pqac-00000025, pqac-00000027).\\n\\n**Practical implementation.** Goldstein et al. describe the trade-off as three-way: throughput, resolution, and coincidence rate. Longer process times achieve better resolution but poor throughput; shorter process times maximize throughput but increase coincidence events. The optimal setting for quantitative analysis is a moderate process time that degrades resolution by only a few percent (e.g., from 122\\u2013128 eV to 130\\u2013135 eV FWHM at Mn K\\u03b1) while substantially increasing throughput (pqac-00000015, pqac-00000014). Modern SDDs with 500 ns time constants can achieve resolution below 130 eV at Mn K\\u03b1 while maintaining maximum OCR of ~130 kHz per detector chip (pqac-00000016). The precision of quantitative analysis is more determined by the number of measured X-rays than by spectral resolution alone (pqac-00000015). Critically, for standards-based analysis, the same process time must be used for all standards and unknowns; adaptive process times that change resolution with throughput make spectrum fitting challenging and less accurate (pqac-00000002).\\n\\n### 4. Counting Statistics: Why ~10\\u2074 Counts Gives ~1% RSD\\n\\nThe count-time recommendation derives directly from Poisson counting statistics. For a measured number of counts N drawn from a Poisson process, the standard deviation is \\u03c3 = \\u221aN, so the relative standard deviation (RSD) is \\u03c3/N = 1/\\u221aN. Thus:\\n\\n- N = 10\\u2074 \\u2192 RSD = 1%\\n- N = 10\\u2076 \\u2192 RSD = 0.1%\\n- N = 10\\u00b2 \\u2192 RSD = 10%\\n\\nThis is a mathematical identity, not an empirical convention. Newbury and Ritchie (2019) tabulate the separate contributions of counting error, absorption-factor error, and atomic-number-factor error to the combined uncertainty budget for standards-based SDD-EDS analysis. For example, in the analysis of FeS at 20 keV with 7 \\u00d7 10\\u2076 integrated spectrum counts, the counting error for the standard contributes \\u00b10.0002 mass fraction and for the unknown \\u00b10.0007, while the absorption factor error dominates at \\u00b10.0017 (pqac-00000006). This demonstrates that at sufficiently high counts, counting statistics become a minor contributor and systematic errors (matrix corrections) dominate.\\n\\nGuyett et al. (2024) empirically validated the counting precision relationship for glass analyses: with only 10k\\u201320k total counts (<1 s acquisition), RSD exceeded 5% even for major element oxides above 10 wt%; above 100k counts, all elements above 1.5 wt% exhibited RSD < 5%; and above 1M counts, major element oxide RSD was consistently below 2% (pqac-00000054). They recommended a minimum of 1M total spectrum counts for fully quantitative major-element SEM-EDX analysis, achievable in approximately 15 seconds with modern multi-detector SDD systems.\\n\\n### 5. Currie's Detection-Limit Framework (the \\\"3-sigma\\\" Criterion)\\n\\nThe widely used \\\"3-sigma\\\" detection criterion traces to Currie's seminal 1968 paper in Analytical Chemistry, which rigorously separated three quantities using hypothesis-testing theory (pqac-00000021, pqac-00000022):\\n\\n1. **Critical value (decision threshold) Lc = z\\u2081\\u208b\\u03b1\\u00b7\\u03c3\\u2080 = 1.645\\u03c3\\u2080** (for \\u03b1 = 0.05): the threshold above which the analyst decides \\\"detected.\\\" This controls only the false-positive rate.\\n\\n2. **Detection limit Ld = Lc + z\\u2081\\u208b\\u03b2\\u00b7\\u03c3d \\u2248 2\\u00d7Lc = 3.29\\u03c3\\u2080** (for \\u03b1 = \\u03b2 = 0.05, homoscedastic Gaussian): the true signal level at which the probability of a false negative is also limited to \\u03b2 = 0.05. The factor 3.29 (not 3) arises from the sum of two one-sided z-quantiles: 1.645 + 1.645 = 3.29.\\n\\n3. **Quantification limit Lq = kq\\u00b7\\u03c3\\u2080 = 10\\u03c3\\u2080** (for 10% RSD at the quantification limit).\\n\\nThe casual shorthand \\\"3-sigma detection limit\\\" conflates the decision threshold (1.645\\u03c3) with the detection limit (3.29\\u03c3) and slightly misquotes the coefficient. Currie (1999) reviewed this confusion, noting that prior approaches ignoring false negatives effectively set \\u03b2 = 0.50, yielding detection capability estimates that differed by up to three orders of magnitude from the hypothesis-testing result (pqac-00000022, pqac-00000018).\\n\\nIn the EDS microanalysis context, Newbury and Ritchie (2019) express the concentration detection limit as CDL = [3\\u221aNB/(NS \\u2212 NB)]\\u00b7CS, where NB is the background counts under the peak, NS is the total peak integral counts, and CS is the known concentration (pqac-00000034). This functional form traces directly to Ziebold's (1967) sensitivity expression CDL > 3.29a/(ntP \\u00d7 P/B)^(1/2), where a relates composition to intensity, n is the number of observations, tP is counting time, and P/B is the peak-to-background ratio (pqac-00000051). Both formulations encode the same Poisson-statistics\\u2013based detection theory.\\n\\n### 6. Standards vs. Genuine Optima vs. Committee Convention\\n\\nThe table below synthesizes how each parameter was derived and whether it represents a true optimum or a codified convention:\\n\\n<artifact id=\\\"artifact-00\\\"/>\\n\\nSeveral observations emerge regarding the nature of these recommendations:\\n\\n- The **overvoltage ratio** of ~2\\u20133 reflects a genuine but broad physics optimum: the Bethe cross-section maximum is broad, and the exact best value depends on whether one prioritizes intensity, spatial resolution, or matrix-correction accuracy. ISO 22309:2011 codified a floor of 1.8, which is a conservative standardization of the physics (pqac-00000053).\\n\\n- The **dead-time** guidance evolved from 20\\u201340% (Si(Li) era, optimizing stored-count rate) to <10% (SDD era, minimizing coincidence peaks for trace analysis) as detector technology changed. No published round-robin explicitly validated the 20\\u201340% range; it was derived from dead-time throughput curves and practical experience (pqac-00000009).\\n\\n- The **process time** setting has a genuine electronics optimum (the ENC minimum), but the commercially available settings and naming conventions differ between vendors, making the specific recommendation partly instrument-dependent (pqac-00000015, pqac-00000026).\\n\\n- The **10,000-count rule** is a direct mathematical consequence of Poisson statistics and is not convention. The translation into specific live-times depends entirely on count rates, which depend on all other parameters.\\n\\n- **Currie's 3.29\\u03c3 detection limit** is a rigorous derivation from Neyman-Pearson hypothesis testing at specified error rates, not an empirical guess. The common simplification to \\\"3\\u03c3\\\" is a minor approximation that has become conventional shorthand (pqac-00000021).\\n\\nRegarding interlaboratory validation, Newbury and Ritchie (2015) demonstrated that the k-ratio/matrix correction protocol with SDD-EDS achieves accuracy matching the WDS distribution established in 1975 (approximately 2.5% relative standard deviation for major constituents, with ~95% of analyses falling within \\u00b15% relative error) (pqac-00000041). However, no published round-robin study was identified that systematically varied EDS acquisition parameters (overvoltage, dead-time, process time) across laboratories to validate the specific recommended ranges. The standards appear to have been written by codifying well-understood physics relationships and experienced practitioners' consensus within ISO TC 202 and ASTM E04 committees.\\n\\n### 7. Shifts for Low-Voltage Microanalysis and Trace Quantification\\n\\n**Low beam energy (\\u22645 keV).** At low voltage, the conventional parameter optima shift significantly. A beam energy of 5 keV represents the lowest value at which at least one characteristic X-ray peak can be excited for all elements of the periodic table except H and He (pqac-00000043). At lower voltages, an increasing number of elements becomes inaccessible. The analyst is forced to use unfamiliar X-ray families (e.g., Ba M-family instead of Ba L-family) which may suffer severe mutual interferences, as demonstrated for YBa\\u2082Cu\\u2083O\\u2087 analyzed at 5 keV where O K, Cu L, and Ba M families overlap (pqac-00000045). Rinaldi and Llovet (2015) documented systematic deviations in transition-element analysis at low voltages (5\\u20136 keV), including Cr underestimation (\\u22120.7% to \\u221217%) and Fe/Ni overestimation (+14% to +42%), attributed to problems with mass absorption coefficients and low fluorescence yields for L-lines (pqac-00000028). The interaction volume reduction (approximately 100-fold decrease from 20 keV to 1 keV) improves spatial resolution to the sub-micrometer scale but reduces absolute X-ray yield per electron, requiring higher beam currents or longer counting times (pqac-00000031). Surface contamination layers and native oxides, which are negligible at 20 keV, become significant contributors to the measured spectrum at low voltage (pqac-00000043).\\n\\n**Trace-element quantification near 0.5\\u20131 wt%.** For Mg K\\u03b1 (1.254 keV) at 0.5\\u20131 wt% in AlSi10Mg measured at 5 keV with an SDD, the overvoltage is generous (U\\u2080 \\u2248 4.0), so excitation efficiency is not limiting. The challenges are instead: (a) the Mg K peak sits in a crowded low-energy region where Al K (1.486 keV) is a dominant neighboring peak; (b) peak-to-background ratios for the Mg peak depend on the continuum modeling and the detector response at low energies; (c) the absorption correction for low-energy photons becomes large and uncertain; and (d) surface contamination carbon deposition can increase absorption of X-rays near the carbon K-edge (0.284 keV) and affect quantification of light elements. Newbury and Ritchie showed that detection limits of 200\\u2013500 ppm (0.02\\u20130.05 wt%) are achievable at conventional voltages within 500 s counting time (pqac-00000034), but at low voltage the effective detection limit for a given counting time may be worse due to increased background relative to peak and poorer matrix-correction accuracy (pqac-00000030). For reliable quantification of 0.5\\u20131 wt% Mg, standards-based analysis with well-characterized standards and careful peak fitting is essential; standardless methods showed ~95% of results within \\u00b125% relative deviation in early testing, an unacceptable error for trace-level work (pqac-00000039). The practical recommendation is to collect substantially more counts than the simple 10\\u2074-count rule would suggest (several 10\\u2075 to 10\\u2076 total spectrum counts), use a moderate process time prioritizing spectral stability over maximum throughput, keep dead time conservatively low to avoid pile-up artifacts in the energy region of interest, and employ multiple replicate measurements with statistical quality-control tests to monitor drift and damage (pqac-00000038, pqac-00000054).\"}",
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+        "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+            "id": "2a23935c-f686-488e-a0a6-0faada1cb90f",
+            "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
+            "answer": "## Derivation of Recommended Acquisition Parameters in SEM-EDS: From Physics Models to Standard Practice\n\n### 1. Overvoltage Ratio (U\u2080 \u2248 2\u20133)\n\nThe recommendation to set the accelerating voltage E\u2080 at roughly two to three times the critical excitation energy Ec of the highest-energy line of interest (i.e., overvoltage U\u2080 = E\u2080/Ec \u2248 2\u20133) derives from the interplay of three physics models.\n\n**Ionization cross-section.** The Bethe (1930) formulation of the inner-shell ionization cross-section Q predicts that Q rises steeply from the threshold (U = 1), passes through a broad maximum at overvoltages of a few (typically U \u2248 2\u20134 depending on the shell and the specific formulation), and then decreases slowly as ln(U)/U at high overvoltages. Green and Cosslett (1961, 1968) validated this behavior experimentally by measuring K-, L-, and M-shell X-ray production efficiencies from thick pure-element targets bombarded by electrons, confirming that characteristic X-ray yield per unit beam current rises rapidly above threshold but saturates at modest overvoltages. Powell, Llovet, and Salvat (2016) later evaluated the accuracy of the Bethe equation against distorted-wave Born-approximation calculations and experiment, finding that the Bethe formula provides a useful approximation in the overvoltage range relevant to microanalysis. These studies collectively established that the marginal gain in ionization efficiency diminishes above U \u2248 2\u20133.\n\n**Electron range and interaction volume.** Countering the benefit of higher overvoltage, the electron range R in a solid scales approximately as E\u2080^1.67/\u03c1 in the Kanaya\u2013Okayama (1972) formulation. This means that raising E\u2080 expands the interaction volume roughly as R\u00b3, degrading lateral and depth spatial resolution. As Goldstein et al. (2018) note, the beam energy of 20 keV provides sufficient overvoltage (E\u2080/Ec > 1.5) for K-shell excitation up to Br and L-shell excitation up to Bi, with photon energies up to ~12 keV (goldstein2018quantitativeanalysisthe pages 4-6). Reducing E\u2080 from 20 to 10 keV substantially reduces the absorption correction factor uncertainty, as demonstrated for the FeS system where the S absorption factor dropped from 1.118 to 1.04, improving the relative error from 1.0% to 0.59% (goldstein2018quantitativeanalysisthe pages 9-11).\n\n**Depth distribution \u03d5(\u03c1z).** Castaing's original tracer experiments (1951 onward) measured the distribution of X-ray production with depth by sandwiching a thin marker layer of known composition at varying depths within a substrate, establishing the \u03d5(\u03c1z) function that forms the basis of ZAF and \u03d5(\u03c1z) matrix corrections. The \u03d5(\u03c1z) function shows that at high overvoltage, X-ray production extends deeper into the specimen, increasing absorption losses and reducing the fraction of generated X-rays that escape to the detector. This provides the physics basis for the practical rule: the overvoltage of ~2\u20133 sits near the broad maximum of the ratio of useful (escaped) characteristic signal to interaction volume. ISO 22309:2011 codified this as a minimum overvoltage of 1.8 for quantitative analysis (tong2026measurementuncertaintiesof pages 8-11). Goldstein et al. recommend E\u2080/Ec > 1.5 as a minimum and note that a beam energy of 5 keV is the lowest at which at least one characteristic X-ray peak can be excited for all elements except H and He (newbury2019electronexcitedxraymicroanalysis pages 13-15).\n\n### 2. Dead-Time and Throughput Optimization (20\u201340% Historical; \u226410% for Modern SDD)\n\nThe dead-time recommendation comes directly from detector counting-rate theory. X-rays arrive randomly, but the EDS can process only one photon at a time. The dead-time percentage is defined as DT(%) = (ICR \u2212 OCR)/ICR \u00d7 100%, where ICR is the input count rate and OCR is the output count rate (goldstein2018energydispersivexray pages 9-10).\n\n**Paralyzable model.** For a truly paralyzable (extending) dead-time system, the output count rate is OCR = ICR \u00d7 exp(\u2212ICR \u00d7 \u03c4), where \u03c4 is the dead-time constant per event. This function has a maximum at ICR = 1/\u03c4, corresponding to a dead-time fraction of 1 \u2212 1/e \u2248 63.2%. Beyond this point, further increases in ICR actually decrease OCR\u2014the system paralyzes. In practice, the useful operating range is well below this mathematical maximum because (a) the dead-time correction accuracy degrades at high rates, and (b) coincidence (sum/pile-up) peaks grow rapidly.\n\n**Non-paralyzable model.** For a non-paralyzable system, OCR = ICR/(1 + ICR \u00d7 \u03c4). The OCR rises monotonically but with diminishing returns, and dead-time correction is mathematically straightforward. Real EDS systems exhibit behavior between these two limits, with modern SDD digital pulse processors closer to non-paralyzable at moderate rates.\n\n**Practical optimum.** The classic Si(Li)-EDS strategy was to operate at \u226430% dead-time on a strongly excited pure element standard (goldstein2018quantitativeanalysisthe pages 6-8). With modern SDD-EDS, Goldstein et al. recommend a more conservative approach: keeping dead-time below 10% on the most highly excited standard because coincidence peaks become significant above this threshold, particularly when trace constituents must be measured in spectral regions affected by sum peaks (goldstein2018quantitativeanalysisthe pages 6-8). At 3% dead-time, coincidence artifacts are minimal; at 29% dead-time on the same glass K412, extensive coincidence peaks (Al+Al, Si+O, Si+Mg, Si+Si, Si+Ca, Mg+Ca) become visible (goldstein2018quantitativeanalysisthe pages 6-8). Donovan et al. (2023) showed that the traditional linear dead-time correction expression Icps = icps/(1 \u2212 icps\u00b7\u03c4) becomes inaccurate above ~50 kcps, requiring higher-order correction expressions (Willis 2-term, 6-term expansion, or logarithmic models) for accurate quantification at higher count rates (donovan2023anewmethod pages 2-3, donovan2023anewmethod pages 3-4).\n\nThus the 20\u201340% guidance for Si(Li) detectors was a practical compromise maximizing stored counts while keeping dead-time correction errors tolerable; the shift to \u226410% for SDD-based quantitative work reflects the greater throughput capacity of SDDs and the more stringent demands of modern peak fitting for trace analysis.\n\n### 3. Pulse Process Time (Shaping Time): Electronic Noise Trade-off\n\nThe choice of process time (also called shaping time, time constant, or throughput setting) in EDS is governed by a fundamental noise trade-off in the front-end electronics (goldstein2018energydispersivexray pages 14-15).\n\n**Noise components.** Lechner et al. (2004) express the equivalent noise charge (ENC) of an SDD as:\n\nENC\u00b2 = (2k\u1d66T/g\u2098)\u00b7C\u00b2\u00b7A\u2081/\u03c4 + afC\u00b2\u00b7A\u2082 + q\u00b7Il\u00b7A\u2083\u00b7\u03c4\n\nwhere the three terms represent serial white noise (proportional to 1/\u03c4, dominated by detector capacitance C and FET transconductance g\u2098), 1/f noise (independent of \u03c4), and parallel noise (proportional to \u03c4, dominated by leakage current Il) (lechner2004novelhighresolutionsilicon pages 2-4). At short shaping times, the serial (voltage) noise dominates and energy resolution degrades hyperbolically; at long shaping times, the parallel (current) noise and pile-up probability increase. The optimal shaping time sits at the broad minimum of ENC versus \u03c4, typically around 0.5\u20133 \u03bcs for SDDs depending on detector area, temperature, and capacitance (schlosser2010expandingthedetection pages 2-4, lechner2004novelhighresolutionsilicon pages 4-5).\n\n**Practical implementation.** Goldstein et al. describe the trade-off as three-way: throughput, resolution, and coincidence rate. Longer process times achieve better resolution but poor throughput; shorter process times maximize throughput but increase coincidence events. The optimal setting for quantitative analysis is a moderate process time that degrades resolution by only a few percent (e.g., from 122\u2013128 eV to 130\u2013135 eV FWHM at Mn K\u03b1) while substantially increasing throughput (goldstein2018energydispersivexray pages 14-15, goldstein2018energydispersivexray pages 25-26). Modern SDDs with 500 ns time constants can achieve resolution below 130 eV at Mn K\u03b1 while maintaining maximum OCR of ~130 kHz per detector chip (newbury2011isscanningelectron pages 2-3). The precision of quantitative analysis is more determined by the number of measured X-rays than by spectral resolution alone (goldstein2018energydispersivexray pages 14-15). Critically, for standards-based analysis, the same process time must be used for all standards and unknowns; adaptive process times that change resolution with throughput make spectrum fitting challenging and less accurate (goldstein2018energydispersivexray pages 14-15).\n\n### 4. Counting Statistics: Why ~10\u2074 Counts Gives ~1% RSD\n\nThe count-time recommendation derives directly from Poisson counting statistics. For a measured number of counts N drawn from a Poisson process, the standard deviation is \u03c3 = \u221aN, so the relative standard deviation (RSD) is \u03c3/N = 1/\u221aN. Thus:\n\n- N = 10\u2074 \u2192 RSD = 1%\n- N = 10\u2076 \u2192 RSD = 0.1%\n- N = 10\u00b2 \u2192 RSD = 10%\n\nThis is a mathematical identity, not an empirical convention. Newbury and Ritchie (2019) tabulate the separate contributions of counting error, absorption-factor error, and atomic-number-factor error to the combined uncertainty budget for standards-based SDD-EDS analysis. For example, in the analysis of FeS at 20 keV with 7 \u00d7 10\u2076 integrated spectrum counts, the counting error for the standard contributes \u00b10.0002 mass fraction and for the unknown \u00b10.0007, while the absorption factor error dominates at \u00b10.0017 (goldstein2018quantitativeanalysisthe pages 8-9). This demonstrates that at sufficiently high counts, counting statistics become a minor contributor and systematic errors (matrix corrections) dominate.\n\nGuyett et al. (2024) empirically validated the counting precision relationship for glass analyses: with only 10k\u201320k total counts (<1 s acquisition), RSD exceeded 5% even for major element oxides above 10 wt%; above 100k counts, all elements above 1.5 wt% exhibited RSD < 5%; and above 1M counts, major element oxide RSD was consistently below 2% (guyett2024optimizingsemedxfor pages 4-6). They recommended a minimum of 1M total spectrum counts for fully quantitative major-element SEM-EDX analysis, achievable in approximately 15 seconds with modern multi-detector SDD systems.\n\n### 5. Currie's Detection-Limit Framework (the \"3-sigma\" Criterion)\n\nThe widely used \"3-sigma\" detection criterion traces to Currie's seminal 1968 paper in Analytical Chemistry, which rigorously separated three quantities using hypothesis-testing theory (currie1999detectionandquantification pages 2-4, currie1999detectionandquantification pages 1-2):\n\n1. **Critical value (decision threshold) Lc = z\u2081\u208b\u03b1\u00b7\u03c3\u2080 = 1.645\u03c3\u2080** (for \u03b1 = 0.05): the threshold above which the analyst decides \"detected.\" This controls only the false-positive rate.\n\n2. **Detection limit Ld = Lc + z\u2081\u208b\u03b2\u00b7\u03c3d \u2248 2\u00d7Lc = 3.29\u03c3\u2080** (for \u03b1 = \u03b2 = 0.05, homoscedastic Gaussian): the true signal level at which the probability of a false negative is also limited to \u03b2 = 0.05. The factor 3.29 (not 3) arises from the sum of two one-sided z-quantiles: 1.645 + 1.645 = 3.29.\n\n3. **Quantification limit Lq = kq\u00b7\u03c3\u2080 = 10\u03c3\u2080** (for 10% RSD at the quantification limit).\n\nThe casual shorthand \"3-sigma detection limit\" conflates the decision threshold (1.645\u03c3) with the detection limit (3.29\u03c3) and slightly misquotes the coefficient. Currie (1999) reviewed this confusion, noting that prior approaches ignoring false negatives effectively set \u03b2 = 0.50, yielding detection capability estimates that differed by up to three orders of magnitude from the hypothesis-testing result (currie1999detectionandquantification pages 1-2, currie1999detectionandquantification pages 4-6).\n\nIn the EDS microanalysis context, Newbury and Ritchie (2019) express the concentration detection limit as CDL = [3\u221aNB/(NS \u2212 NB)]\u00b7CS, where NB is the background counts under the peak, NS is the total peak integral counts, and CS is the known concentration (newbury2019electronexcitedxraymicroanalysis pages 13-15). This functional form traces directly to Ziebold's (1967) sensitivity expression CDL > 3.29a/(ntP \u00d7 P/B)^(1/2), where a relates composition to intensity, n is the number of observations, tP is counting time, and P/B is the peak-to-background ratio (rinaldi2015electronprobemicroanalysis pages 4-5). Both formulations encode the same Poisson-statistics\u2013based detection theory.\n\n### 6. Standards vs. Genuine Optima vs. Committee Convention\n\nThe table below synthesizes how each parameter was derived and whether it represents a true optimum or a codified convention:\n\n| Parameter | Common recommended value | How the number was derived | Key primary literature / anchor reference | True optimum or convention? | Shift at low-kV / trace analysis |\n|---|---|---|---|---|---|\n| Overvoltage ratio U0 = E0/Ec | Typically ~2\u20133; ISO floor for quant often stated as \u22651.8 | From the inner-shell ionization cross-section rising steeply just above threshold and then flattening or declining in benefit per added kV, as described by Bethe-type formulations and later evaluated by Powell, Llovet, and Salvat; thick-target X-ray production efficiency measurements by Green and Cosslett showed characteristic yield peaking broadly near modest overvoltage, not at the highest beam energy. The competing penalty is that electron range and interaction volume grow strongly with E0, approximately by Kanaya\u2013Okayama scaling, while phi(rho-z) depth distributions show X-ray generation moving deeper, increasing absorption and reducing spatial resolution. Thus the rule came from maximizing useful characteristic production per unit interaction volume, not from committee preference alone. (goldstein2018quantitativeanalysisthe pages 4-6, goldstein2018quantitativeanalysisthe pages 9-11, rinaldi2015electronprobemicroanalysis pages 7-8, newbury2019electronexcitedxraymicroanalysis pages 13-15, rinaldi2015electronprobemicroanalysis pages 2-4, tong2026measurementuncertaintiesof pages 8-11) | Bethe theory; Green and Cosslett 1961, 1968 measurements; Kanaya and Okayama 1972; Castaing-origin phi(rho-z) framework as summarized in later reviews | Mostly a genuine physics optimum, but broad rather than sharp; committees codified a robust operating zone | At \u22645 keV the optimum is often driven by line accessibility and spatial resolution rather than by the classic 2\u20133 rule alone; one may accept lower overvoltage (~1.25\u20131.8) to keep the interaction volume small or to reach only available L or M lines, with increased sensitivity to absorption, surface films, and matrix-correction error. For Mg K-alpha at 5 keV, U0 \u2248 5/1.254 \u2248 4.0: excitation is ample, but the practical limit becomes background, absorption, and overlap handling rather than insufficient ionization. (newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2019electronexcitedxraymicroanalysis pages 16-18, rinaldi2015electronprobemicroanalysis pages 7-8, wuhrer2016lowvoltageimaging pages 7-10, wuhrer2016lowvoltageimaging pages 10-12) |\n| Detector dead time / throughput | Historically ~20\u201340% for Si(Li); modern standards-based SDD quant often kept much lower, commonly <10\u201315% on the most intense peak if coincidence artifacts matter | Derived from counting-system dead-time theory. For a paralyzable model, stored rate behaves approximately as OCR = ICR \u00d7 exp(-ICR \u00d7 tau), which peaks at ICR \u00d7 tau = 1, i.e. 36.8% dead time; for a non-paralyzable model OCR = ICR/(1 + ICR \u00d7 tau), throughput keeps rising but with diminishing returns. Real EDS electronics also have anti-coincidence rejection and pile-up artifacts, so the practical maximum useful throughput occurs before the mathematical maximum if sum peaks will compromise quantification. Goldstein shows OCR\u2013ICR curves and coincidence-peak growth; Donovan shows why simple linear dead-time correction breaks down at higher rates. (goldstein2018quantitativeanalysisthe pages 6-8, goldstein2018energydispersivexray pages 9-10, donovan2023anewmethod pages 3-4, donovan2023anewmethod pages 2-3, donovan2023anewmethod pages 4-5) | Classic dead-time theory; modern microanalysis implementation in Goldstein and Donovan | A real throughput optimum exists mathematically, but the widely taught 20\u201340% band is partly a practical convention balancing throughput against pile-up; with SDD quantitative work the optimum for accuracy often shifts lower | For low-kV and trace work, keep dead time lower because weak trace peaks can be hidden by coincidence peaks and by calibration or resolution drift at high rates. Modern SDDs can run at high OCR, but if looking for 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, a conservative dead time (~10\u201320%, or even lower if sum peaks intrude) is usually preferable to maximize spectral cleanliness. (goldstein2018quantitativeanalysisthe pages 6-8, goldstein2018energydispersivexray pages 9-10, guyett2024optimizingsemedxfor pages 4-6, guyett2024optimizingsemedxfor pages 3-4) |\n| Pulse processor shaping / process time | Choose a moderate setting: a few eV worse than best resolution, but far better throughput; avoid adaptive shaping for standards-based quant | Derived from the equivalent-noise-charge minimum. Lechner gives ENC^2 = serial white term proportional to 1/tau + a 1/f term + a parallel-noise term proportional to tau: short shaping times increase series white noise and ballistic-deficit sensitivity; long shaping times increase parallel-noise contribution and pile-up probability. Therefore the optimum is at the broad minimum of ENC versus shaping time, then adjusted upward or downward depending on count-rate needs. Goldstein describes the three-way trade-off among resolution, throughput, and coincidence rate; Schlosser and Niculae show measured FWHM versus shaping time for SDDs. (goldstein2018energydispersivexray pages 25-26, goldstein2018energydispersivexray pages 14-15, newbury2011isscanningelectron pages 2-3, niculae2006optimizedreadoutmethods pages 2-3, niculae2006optimizedreadoutmethods pages 3-6, schlosser2010expandingthedetection pages 2-4, lechner2004novelhighresolutionsilicon pages 2-4, lechner2004novelhighresolutionsilicon pages 4-5) | Semiconductor-detector noise theory; Lechner 2004; Niculae 2006; Schlosser 2010; later digital-pulse work such as Blaj 2017 | Genuine electronics optimum, but broad; the exact chosen setting is instrument-specific and thus partly conventional in practice | At low-kV, low-energy peaks are narrow and often crowded, so somewhat longer shaping than for fast mapping may be justified if resolving Mg, Al, Si low-energy structure matters. For trace analysis, prioritize stability and peak shape over absolute OCR; sacrificing a small amount of throughput for cleaner low-energy deconvolution is often worthwhile. (goldstein2018energydispersivexray pages 14-15, newbury2011isscanningelectron pages 2-3, schlosser2010expandingthedetection pages 2-4, wuhrer2016lowvoltageimaging pages 10-12) |\n| Live time / counts for precision | Rule of thumb: ~10,000 net counts in a peak of interest gives ~1% counting RSD; major-element whole-spectrum quant often uses 10^6 total counts or more | Pure Poisson statistics: for net peak counts N, sigma/N \u2248 1/sqrt(N). Thus N = 10^4 gives 1% relative standard deviation from counting alone. Real net-peak precision is worse when background subtraction is needed, so standards and unknowns both require sufficient dose. Newbury and Goldstein tables separate counting error from matrix-correction error; Guyett empirically found >10^5 counts gives <5% RSD for >1.5 wt% oxides and recommends ~10^6 counts for robust quantitative SEM-EDX of majors. (goldstein2018quantitativeanalysisthe pages 8-9, goldstein2018quantitativeanalysisthe pages 9-11, newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2015performingelementalmicroanalysis pages 2-4, guyett2024optimizingsemedxfor pages 4-6) | Poisson counting law; Ziebold 1967 sensitivity framework; Currie 1968 and 1999 for limits; Newbury and Ritchie applications | This is a true statistical relationship, not convention; the exact count targets are practical translations of desired precision | Low-kV reduces continuum volume but often lowers usable peak-to-background and can worsen matrix sensitivity for low-energy lines, so more counts may be needed than the simple 10^4 rule suggests. For 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, several 10^5 to ~10^6 total counts, or repeated acquisitions summed after drift or damage checks, is more realistic if one wants robust sub-wt% precision. (newbury2019electronexcitedxraymicroanalysis pages 13-15, ritchie2018exploringthelimits pages 9-11, ritchie2018exploringthelimits pages 4-5, guyett2024optimizingsemedxfor pages 4-6) |\n| Detection criterion | Currie 3-sigma family: LC = 1.645 sigma0, LD = 3.29 sigma0 for alpha = beta = 0.05; often simplified in practice to 3 sigma detection | Currie\u2019s 1968 hypothesis-testing framework separated the decision threshold LC from the true minimum detectable amount LD. Under Gaussian, homoscedastic approximation and equal Type-I and Type-II risks of 0.05, LC = 1.645 sigma0, and LD = LC + 1.645 sigmaD \u2248 3.29 sigma0. For counting data, sigma is usually controlled by blank or background counts, which is why detection capability depends on the background under the peak. Newbury expresses the same idea in concentration form as CDL = [3 \u00d7 sqrt(NB)/(NS \u2212 NB)] \u00d7 CS. (currie1999detectionandquantification pages 4-6, currie1999detectionandquantification pages 2-4, currie1999detectionandquantification pages 1-2, newbury2019electronexcitedxraymicroanalysis pages 13-15, rinaldi2015electronprobemicroanalysis pages 4-5) | Currie 1968; Currie 1999 retrospective; Ziebold 1967 concentration sensitivity expression | A genuine statistical derivation; the casual phrase 3-sigma is a simplified convention for Currie\u2019s more exact 3.29-sigma detection limit | At low-kV the blank and low-energy artifacts become more dominant, so sigma is often set by background modeling, contamination, and deconvolution residuals rather than by raw peak counts alone. For Mg K-alpha at 0.5\u20131 wt% in AlSi10Mg at 5 keV, formal detectability is usually not the bottleneck; reliable quantification is limited more by standards and matrix-correction quality, low-energy peak fitting, and reproducibility than by passing the Currie decision threshold. (wuhrer2016lowvoltageimaging pages 10-12, newbury2019electronexcitedxraymicroanalysis pages 13-15, tong2026measurementuncertaintiesof pages 8-11) |\n\n\n*Table: This table summarizes how the standard SEM-EDS acquisition parameters were justified from physics, electronics, and counting statistics rather than merely adopted by standards committees. It also shows which values are true optima, which are practical conventions, and how they shift for low-voltage and trace-level analysis.*\n\nSeveral observations emerge regarding the nature of these recommendations:\n\n- The **overvoltage ratio** of ~2\u20133 reflects a genuine but broad physics optimum: the Bethe cross-section maximum is broad, and the exact best value depends on whether one prioritizes intensity, spatial resolution, or matrix-correction accuracy. ISO 22309:2011 codified a floor of 1.8, which is a conservative standardization of the physics (tong2026measurementuncertaintiesof pages 8-11).\n\n- The **dead-time** guidance evolved from 20\u201340% (Si(Li) era, optimizing stored-count rate) to <10% (SDD era, minimizing coincidence peaks for trace analysis) as detector technology changed. No published round-robin explicitly validated the 20\u201340% range; it was derived from dead-time throughput curves and practical experience (goldstein2018quantitativeanalysisthe pages 6-8).\n\n- The **process time** setting has a genuine electronics optimum (the ENC minimum), but the commercially available settings and naming conventions differ between vendors, making the specific recommendation partly instrument-dependent (goldstein2018energydispersivexray pages 14-15, lechner2004novelhighresolutionsilicon pages 2-4).\n\n- The **10,000-count rule** is a direct mathematical consequence of Poisson statistics and is not convention. The translation into specific live-times depends entirely on count rates, which depend on all other parameters.\n\n- **Currie's 3.29\u03c3 detection limit** is a rigorous derivation from Neyman-Pearson hypothesis testing at specified error rates, not an empirical guess. The common simplification to \"3\u03c3\" is a minor approximation that has become conventional shorthand (currie1999detectionandquantification pages 2-4).\n\nRegarding interlaboratory validation, Newbury and Ritchie (2015) demonstrated that the k-ratio/matrix correction protocol with SDD-EDS achieves accuracy matching the WDS distribution established in 1975 (approximately 2.5% relative standard deviation for major constituents, with ~95% of analyses falling within \u00b15% relative error) (newbury2015performingelementalmicroanalysis pages 2-4). However, no published round-robin study was identified that systematically varied EDS acquisition parameters (overvoltage, dead-time, process time) across laboratories to validate the specific recommended ranges. The standards appear to have been written by codifying well-understood physics relationships and experienced practitioners' consensus within ISO TC 202 and ASTM E04 committees.\n\n### 7. Shifts for Low-Voltage Microanalysis and Trace Quantification\n\n**Low beam energy (\u22645 keV).** At low voltage, the conventional parameter optima shift significantly. A beam energy of 5 keV represents the lowest value at which at least one characteristic X-ray peak can be excited for all elements of the periodic table except H and He (newbury2019electronexcitedxraymicroanalysis pages 13-15). At lower voltages, an increasing number of elements becomes inaccessible. The analyst is forced to use unfamiliar X-ray families (e.g., Ba M-family instead of Ba L-family) which may suffer severe mutual interferences, as demonstrated for YBa\u2082Cu\u2083O\u2087 analyzed at 5 keV where O K, Cu L, and Ba M families overlap (newbury2019electronexcitedxraymicroanalysis pages 16-18). Rinaldi and Llovet (2015) documented systematic deviations in transition-element analysis at low voltages (5\u20136 keV), including Cr underestimation (\u22120.7% to \u221217%) and Fe/Ni overestimation (+14% to +42%), attributed to problems with mass absorption coefficients and low fluorescence yields for L-lines (rinaldi2015electronprobemicroanalysis pages 7-8). The interaction volume reduction (approximately 100-fold decrease from 20 keV to 1 keV) improves spatial resolution to the sub-micrometer scale but reduces absolute X-ray yield per electron, requiring higher beam currents or longer counting times (gollaschindler2026edswithlowvoltage pages 3-6). Surface contamination layers and native oxides, which are negligible at 20 keV, become significant contributors to the measured spectrum at low voltage (newbury2019electronexcitedxraymicroanalysis pages 13-15).\n\n**Trace-element quantification near 0.5\u20131 wt%.** For Mg K\u03b1 (1.254 keV) at 0.5\u20131 wt% in AlSi10Mg measured at 5 keV with an SDD, the overvoltage is generous (U\u2080 \u2248 4.0), so excitation efficiency is not limiting. The challenges are instead: (a) the Mg K peak sits in a crowded low-energy region where Al K (1.486 keV) is a dominant neighboring peak; (b) peak-to-background ratios for the Mg peak depend on the continuum modeling and the detector response at low energies; (c) the absorption correction for low-energy photons becomes large and uncertain; and (d) surface contamination carbon deposition can increase absorption of X-rays near the carbon K-edge (0.284 keV) and affect quantification of light elements. Newbury and Ritchie showed that detection limits of 200\u2013500 ppm (0.02\u20130.05 wt%) are achievable at conventional voltages within 500 s counting time (newbury2019electronexcitedxraymicroanalysis pages 13-15), but at low voltage the effective detection limit for a given counting time may be worse due to increased background relative to peak and poorer matrix-correction accuracy (wuhrer2016lowvoltageimaging pages 10-12). For reliable quantification of 0.5\u20131 wt% Mg, standards-based analysis with well-characterized standards and careful peak fitting is essential; standardless methods showed ~95% of results within \u00b125% relative deviation in early testing, an unacceptable error for trace-level work (newbury2019electronexcitedxraymicroanalysis pages 18-20). The practical recommendation is to collect substantially more counts than the simple 10\u2074-count rule would suggest (several 10\u2075 to 10\u2076 total spectrum counts), use a moderate process time prioritizing spectral stability over maximum throughput, keep dead time conservatively low to avoid pile-up artifacts in the energy region of interest, and employ multiple replicate measurements with statistical quality-control tests to monitor drift and damage (ritchie2018exploringthelimits pages 4-5, guyett2024optimizingsemedxfor pages 4-6).",
+            "raw_answer": "## Derivation of Recommended Acquisition Parameters in SEM-EDS: From Physics Models to Standard Practice\n\n### 1. Overvoltage Ratio (U\u2080 \u2248 2\u20133)\n\nThe recommendation to set the accelerating voltage E\u2080 at roughly two to three times the critical excitation energy Ec of the highest-energy line of interest (i.e., overvoltage U\u2080 = E\u2080/Ec \u2248 2\u20133) derives from the interplay of three physics models.\n\n**Ionization cross-section.** The Bethe (1930) formulation of the inner-shell ionization cross-section Q predicts that Q rises steeply from the threshold (U = 1), passes through a broad maximum at overvoltages of a few (typically U \u2248 2\u20134 depending on the shell and the specific formulation), and then decreases slowly as ln(U)/U at high overvoltages. Green and Cosslett (1961, 1968) validated this behavior experimentally by measuring K-, L-, and M-shell X-ray production efficiencies from thick pure-element targets bombarded by electrons, confirming that characteristic X-ray yield per unit beam current rises rapidly above threshold but saturates at modest overvoltages. Powell, Llovet, and Salvat (2016) later evaluated the accuracy of the Bethe equation against distorted-wave Born-approximation calculations and experiment, finding that the Bethe formula provides a useful approximation in the overvoltage range relevant to microanalysis. These studies collectively established that the marginal gain in ionization efficiency diminishes above U \u2248 2\u20133.\n\n**Electron range and interaction volume.** Countering the benefit of higher overvoltage, the electron range R in a solid scales approximately as E\u2080^1.67/\u03c1 in the Kanaya\u2013Okayama (1972) formulation. This means that raising E\u2080 expands the interaction volume roughly as R\u00b3, degrading lateral and depth spatial resolution. As Goldstein et al. (2018) note, the beam energy of 20 keV provides sufficient overvoltage (E\u2080/Ec > 1.5) for K-shell excitation up to Br and L-shell excitation up to Bi, with photon energies up to ~12 keV (pqac-00000007). Reducing E\u2080 from 20 to 10 keV substantially reduces the absorption correction factor uncertainty, as demonstrated for the FeS system where the S absorption factor dropped from 1.118 to 1.04, improving the relative error from 1.0% to 0.59% (pqac-00000008).\n\n**Depth distribution \u03d5(\u03c1z).** Castaing's original tracer experiments (1951 onward) measured the distribution of X-ray production with depth by sandwiching a thin marker layer of known composition at varying depths within a substrate, establishing the \u03d5(\u03c1z) function that forms the basis of ZAF and \u03d5(\u03c1z) matrix corrections. The \u03d5(\u03c1z) function shows that at high overvoltage, X-ray production extends deeper into the specimen, increasing absorption losses and reducing the fraction of generated X-rays that escape to the detector. This provides the physics basis for the practical rule: the overvoltage of ~2\u20133 sits near the broad maximum of the ratio of useful (escaped) characteristic signal to interaction volume. ISO 22309:2011 codified this as a minimum overvoltage of 1.8 for quantitative analysis (pqac-00000053). Goldstein et al. recommend E\u2080/Ec > 1.5 as a minimum and note that a beam energy of 5 keV is the lowest at which at least one characteristic X-ray peak can be excited for all elements except H and He (pqac-00000043).\n\n### 2. Dead-Time and Throughput Optimization (20\u201340% Historical; \u226410% for Modern SDD)\n\nThe dead-time recommendation comes directly from detector counting-rate theory. X-rays arrive randomly, but the EDS can process only one photon at a time. The dead-time percentage is defined as DT(%) = (ICR \u2212 OCR)/ICR \u00d7 100%, where ICR is the input count rate and OCR is the output count rate (pqac-00000046, pqac-00000011).\n\n**Paralyzable model.** For a truly paralyzable (extending) dead-time system, the output count rate is OCR = ICR \u00d7 exp(\u2212ICR \u00d7 \u03c4), where \u03c4 is the dead-time constant per event. This function has a maximum at ICR = 1/\u03c4, corresponding to a dead-time fraction of 1 \u2212 1/e \u2248 63.2%. Beyond this point, further increases in ICR actually decrease OCR\u2014the system paralyzes. In practice, the useful operating range is well below this mathematical maximum because (a) the dead-time correction accuracy degrades at high rates, and (b) coincidence (sum/pile-up) peaks grow rapidly.\n\n**Non-paralyzable model.** For a non-paralyzable system, OCR = ICR/(1 + ICR \u00d7 \u03c4). The OCR rises monotonically but with diminishing returns, and dead-time correction is mathematically straightforward. Real EDS systems exhibit behavior between these two limits, with modern SDD digital pulse processors closer to non-paralyzable at moderate rates.\n\n**Practical optimum.** The classic Si(Li)-EDS strategy was to operate at \u226430% dead-time on a strongly excited pure element standard (pqac-00000009). With modern SDD-EDS, Goldstein et al. recommend a more conservative approach: keeping dead-time below 10% on the most highly excited standard because coincidence peaks become significant above this threshold, particularly when trace constituents must be measured in spectral regions affected by sum peaks (pqac-00000009). At 3% dead-time, coincidence artifacts are minimal; at 29% dead-time on the same glass K412, extensive coincidence peaks (Al+Al, Si+O, Si+Mg, Si+Si, Si+Ca, Mg+Ca) become visible (pqac-00000009). Donovan et al. (2023) showed that the traditional linear dead-time correction expression Icps = icps/(1 \u2212 icps\u00b7\u03c4) becomes inaccurate above ~50 kcps, requiring higher-order correction expressions (Willis 2-term, 6-term expansion, or logarithmic models) for accurate quantification at higher count rates (pqac-00000048, pqac-00000047).\n\nThus the 20\u201340% guidance for Si(Li) detectors was a practical compromise maximizing stored counts while keeping dead-time correction errors tolerable; the shift to \u226410% for SDD-based quantitative work reflects the greater throughput capacity of SDDs and the more stringent demands of modern peak fitting for trace analysis.\n\n### 3. Pulse Process Time (Shaping Time): Electronic Noise Trade-off\n\nThe choice of process time (also called shaping time, time constant, or throughput setting) in EDS is governed by a fundamental noise trade-off in the front-end electronics (pqac-00000015, pqac-00000002).\n\n**Noise components.** Lechner et al. (2004) express the equivalent noise charge (ENC) of an SDD as:\n\nENC\u00b2 = (2k\u1d66T/g\u2098)\u00b7C\u00b2\u00b7A\u2081/\u03c4 + afC\u00b2\u00b7A\u2082 + q\u00b7Il\u00b7A\u2083\u00b7\u03c4\n\nwhere the three terms represent serial white noise (proportional to 1/\u03c4, dominated by detector capacitance C and FET transconductance g\u2098), 1/f noise (independent of \u03c4), and parallel noise (proportional to \u03c4, dominated by leakage current Il) (pqac-00000026). At short shaping times, the serial (voltage) noise dominates and energy resolution degrades hyperbolically; at long shaping times, the parallel (current) noise and pile-up probability increase. The optimal shaping time sits at the broad minimum of ENC versus \u03c4, typically around 0.5\u20133 \u03bcs for SDDs depending on detector area, temperature, and capacitance (pqac-00000025, pqac-00000027).\n\n**Practical implementation.** Goldstein et al. describe the trade-off as three-way: throughput, resolution, and coincidence rate. Longer process times achieve better resolution but poor throughput; shorter process times maximize throughput but increase coincidence events. The optimal setting for quantitative analysis is a moderate process time that degrades resolution by only a few percent (e.g., from 122\u2013128 eV to 130\u2013135 eV FWHM at Mn K\u03b1) while substantially increasing throughput (pqac-00000015, pqac-00000014). Modern SDDs with 500 ns time constants can achieve resolution below 130 eV at Mn K\u03b1 while maintaining maximum OCR of ~130 kHz per detector chip (pqac-00000016). The precision of quantitative analysis is more determined by the number of measured X-rays than by spectral resolution alone (pqac-00000015). Critically, for standards-based analysis, the same process time must be used for all standards and unknowns; adaptive process times that change resolution with throughput make spectrum fitting challenging and less accurate (pqac-00000002).\n\n### 4. Counting Statistics: Why ~10\u2074 Counts Gives ~1% RSD\n\nThe count-time recommendation derives directly from Poisson counting statistics. For a measured number of counts N drawn from a Poisson process, the standard deviation is \u03c3 = \u221aN, so the relative standard deviation (RSD) is \u03c3/N = 1/\u221aN. Thus:\n\n- N = 10\u2074 \u2192 RSD = 1%\n- N = 10\u2076 \u2192 RSD = 0.1%\n- N = 10\u00b2 \u2192 RSD = 10%\n\nThis is a mathematical identity, not an empirical convention. Newbury and Ritchie (2019) tabulate the separate contributions of counting error, absorption-factor error, and atomic-number-factor error to the combined uncertainty budget for standards-based SDD-EDS analysis. For example, in the analysis of FeS at 20 keV with 7 \u00d7 10\u2076 integrated spectrum counts, the counting error for the standard contributes \u00b10.0002 mass fraction and for the unknown \u00b10.0007, while the absorption factor error dominates at \u00b10.0017 (pqac-00000006). This demonstrates that at sufficiently high counts, counting statistics become a minor contributor and systematic errors (matrix corrections) dominate.\n\nGuyett et al. (2024) empirically validated the counting precision relationship for glass analyses: with only 10k\u201320k total counts (<1 s acquisition), RSD exceeded 5% even for major element oxides above 10 wt%; above 100k counts, all elements above 1.5 wt% exhibited RSD < 5%; and above 1M counts, major element oxide RSD was consistently below 2% (pqac-00000054). They recommended a minimum of 1M total spectrum counts for fully quantitative major-element SEM-EDX analysis, achievable in approximately 15 seconds with modern multi-detector SDD systems.\n\n### 5. Currie's Detection-Limit Framework (the \"3-sigma\" Criterion)\n\nThe widely used \"3-sigma\" detection criterion traces to Currie's seminal 1968 paper in Analytical Chemistry, which rigorously separated three quantities using hypothesis-testing theory (pqac-00000021, pqac-00000022):\n\n1. **Critical value (decision threshold) Lc = z\u2081\u208b\u03b1\u00b7\u03c3\u2080 = 1.645\u03c3\u2080** (for \u03b1 = 0.05): the threshold above which the analyst decides \"detected.\" This controls only the false-positive rate.\n\n2. **Detection limit Ld = Lc + z\u2081\u208b\u03b2\u00b7\u03c3d \u2248 2\u00d7Lc = 3.29\u03c3\u2080** (for \u03b1 = \u03b2 = 0.05, homoscedastic Gaussian): the true signal level at which the probability of a false negative is also limited to \u03b2 = 0.05. The factor 3.29 (not 3) arises from the sum of two one-sided z-quantiles: 1.645 + 1.645 = 3.29.\n\n3. **Quantification limit Lq = kq\u00b7\u03c3\u2080 = 10\u03c3\u2080** (for 10% RSD at the quantification limit).\n\nThe casual shorthand \"3-sigma detection limit\" conflates the decision threshold (1.645\u03c3) with the detection limit (3.29\u03c3) and slightly misquotes the coefficient. Currie (1999) reviewed this confusion, noting that prior approaches ignoring false negatives effectively set \u03b2 = 0.50, yielding detection capability estimates that differed by up to three orders of magnitude from the hypothesis-testing result (pqac-00000022, pqac-00000018).\n\nIn the EDS microanalysis context, Newbury and Ritchie (2019) express the concentration detection limit as CDL = [3\u221aNB/(NS \u2212 NB)]\u00b7CS, where NB is the background counts under the peak, NS is the total peak integral counts, and CS is the known concentration (pqac-00000034). This functional form traces directly to Ziebold's (1967) sensitivity expression CDL > 3.29a/(ntP \u00d7 P/B)^(1/2), where a relates composition to intensity, n is the number of observations, tP is counting time, and P/B is the peak-to-background ratio (pqac-00000051). Both formulations encode the same Poisson-statistics\u2013based detection theory.\n\n### 6. Standards vs. Genuine Optima vs. Committee Convention\n\nThe table below synthesizes how each parameter was derived and whether it represents a true optimum or a codified convention:\n\n| Parameter | Common recommended value | How the number was derived | Key primary literature / anchor reference | True optimum or convention? | Shift at low-kV / trace analysis |\n|---|---|---|---|---|---|\n| Overvoltage ratio U0 = E0/Ec | Typically ~2\u20133; ISO floor for quant often stated as \u22651.8 | From the inner-shell ionization cross-section rising steeply just above threshold and then flattening or declining in benefit per added kV, as described by Bethe-type formulations and later evaluated by Powell, Llovet, and Salvat; thick-target X-ray production efficiency measurements by Green and Cosslett showed characteristic yield peaking broadly near modest overvoltage, not at the highest beam energy. The competing penalty is that electron range and interaction volume grow strongly with E0, approximately by Kanaya\u2013Okayama scaling, while phi(rho-z) depth distributions show X-ray generation moving deeper, increasing absorption and reducing spatial resolution. Thus the rule came from maximizing useful characteristic production per unit interaction volume, not from committee preference alone. (pqac-00000007, pqac-00000008, pqac-00000028, pqac-00000043, pqac-00000050, pqac-00000053) | Bethe theory; Green and Cosslett 1961, 1968 measurements; Kanaya and Okayama 1972; Castaing-origin phi(rho-z) framework as summarized in later reviews | Mostly a genuine physics optimum, but broad rather than sharp; committees codified a robust operating zone | At \u22645 keV the optimum is often driven by line accessibility and spatial resolution rather than by the classic 2\u20133 rule alone; one may accept lower overvoltage (~1.25\u20131.8) to keep the interaction volume small or to reach only available L or M lines, with increased sensitivity to absorption, surface films, and matrix-correction error. For Mg K-alpha at 5 keV, U0 \u2248 5/1.254 \u2248 4.0: excitation is ample, but the practical limit becomes background, absorption, and overlap handling rather than insufficient ionization. (pqac-00000043, pqac-00000045, pqac-00000028, pqac-00000029, pqac-00000030) |\n| Detector dead time / throughput | Historically ~20\u201340% for Si(Li); modern standards-based SDD quant often kept much lower, commonly <10\u201315% on the most intense peak if coincidence artifacts matter | Derived from counting-system dead-time theory. For a paralyzable model, stored rate behaves approximately as OCR = ICR \u00d7 exp(-ICR \u00d7 tau), which peaks at ICR \u00d7 tau = 1, i.e. 36.8% dead time; for a non-paralyzable model OCR = ICR/(1 + ICR \u00d7 tau), throughput keeps rising but with diminishing returns. Real EDS electronics also have anti-coincidence rejection and pile-up artifacts, so the practical maximum useful throughput occurs before the mathematical maximum if sum peaks will compromise quantification. Goldstein shows OCR\u2013ICR curves and coincidence-peak growth; Donovan shows why simple linear dead-time correction breaks down at higher rates. (pqac-00000009, pqac-00000011, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049) | Classic dead-time theory; modern microanalysis implementation in Goldstein and Donovan | A real throughput optimum exists mathematically, but the widely taught 20\u201340% band is partly a practical convention balancing throughput against pile-up; with SDD quantitative work the optimum for accuracy often shifts lower | For low-kV and trace work, keep dead time lower because weak trace peaks can be hidden by coincidence peaks and by calibration or resolution drift at high rates. Modern SDDs can run at high OCR, but if looking for 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, a conservative dead time (~10\u201320%, or even lower if sum peaks intrude) is usually preferable to maximize spectral cleanliness. (pqac-00000009, pqac-00000046, pqac-00000054, pqac-00000055) |\n| Pulse processor shaping / process time | Choose a moderate setting: a few eV worse than best resolution, but far better throughput; avoid adaptive shaping for standards-based quant | Derived from the equivalent-noise-charge minimum. Lechner gives ENC^2 = serial white term proportional to 1/tau + a 1/f term + a parallel-noise term proportional to tau: short shaping times increase series white noise and ballistic-deficit sensitivity; long shaping times increase parallel-noise contribution and pile-up probability. Therefore the optimum is at the broad minimum of ENC versus shaping time, then adjusted upward or downward depending on count-rate needs. Goldstein describes the three-way trade-off among resolution, throughput, and coincidence rate; Schlosser and Niculae show measured FWHM versus shaping time for SDDs. (pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027) | Semiconductor-detector noise theory; Lechner 2004; Niculae 2006; Schlosser 2010; later digital-pulse work such as Blaj 2017 | Genuine electronics optimum, but broad; the exact chosen setting is instrument-specific and thus partly conventional in practice | At low-kV, low-energy peaks are narrow and often crowded, so somewhat longer shaping than for fast mapping may be justified if resolving Mg, Al, Si low-energy structure matters. For trace analysis, prioritize stability and peak shape over absolute OCR; sacrificing a small amount of throughput for cleaner low-energy deconvolution is often worthwhile. (pqac-00000015, pqac-00000016, pqac-00000025, pqac-00000030) |\n| Live time / counts for precision | Rule of thumb: ~10,000 net counts in a peak of interest gives ~1% counting RSD; major-element whole-spectrum quant often uses 10^6 total counts or more | Pure Poisson statistics: for net peak counts N, sigma/N \u2248 1/sqrt(N). Thus N = 10^4 gives 1% relative standard deviation from counting alone. Real net-peak precision is worse when background subtraction is needed, so standards and unknowns both require sufficient dose. Newbury and Goldstein tables separate counting error from matrix-correction error; Guyett empirically found >10^5 counts gives <5% RSD for >1.5 wt% oxides and recommends ~10^6 counts for robust quantitative SEM-EDX of majors. (pqac-00000006, pqac-00000008, pqac-00000034, pqac-00000041, pqac-00000043, pqac-00000054) | Poisson counting law; Ziebold 1967 sensitivity framework; Currie 1968 and 1999 for limits; Newbury and Ritchie applications | This is a true statistical relationship, not convention; the exact count targets are practical translations of desired precision | Low-kV reduces continuum volume but often lowers usable peak-to-background and can worsen matrix sensitivity for low-energy lines, so more counts may be needed than the simple 10^4 rule suggests. For 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, several 10^5 to ~10^6 total counts, or repeated acquisitions summed after drift or damage checks, is more realistic if one wants robust sub-wt% precision. (pqac-00000034, pqac-00000036, pqac-00000038, pqac-00000054) |\n| Detection criterion | Currie 3-sigma family: LC = 1.645 sigma0, LD = 3.29 sigma0 for alpha = beta = 0.05; often simplified in practice to 3 sigma detection | Currie\u2019s 1968 hypothesis-testing framework separated the decision threshold LC from the true minimum detectable amount LD. Under Gaussian, homoscedastic approximation and equal Type-I and Type-II risks of 0.05, LC = 1.645 sigma0, and LD = LC + 1.645 sigmaD \u2248 3.29 sigma0. For counting data, sigma is usually controlled by blank or background counts, which is why detection capability depends on the background under the peak. Newbury expresses the same idea in concentration form as CDL = [3 \u00d7 sqrt(NB)/(NS \u2212 NB)] \u00d7 CS. (pqac-00000018, pqac-00000021, pqac-00000022, pqac-00000034, pqac-00000051) | Currie 1968; Currie 1999 retrospective; Ziebold 1967 concentration sensitivity expression | A genuine statistical derivation; the casual phrase 3-sigma is a simplified convention for Currie\u2019s more exact 3.29-sigma detection limit | At low-kV the blank and low-energy artifacts become more dominant, so sigma is often set by background modeling, contamination, and deconvolution residuals rather than by raw peak counts alone. For Mg K-alpha at 0.5\u20131 wt% in AlSi10Mg at 5 keV, formal detectability is usually not the bottleneck; reliable quantification is limited more by standards and matrix-correction quality, low-energy peak fitting, and reproducibility than by passing the Currie decision threshold. (pqac-00000030, pqac-00000034, pqac-00000043, pqac-00000053) |\n\n\n*Table: This table summarizes how the standard SEM-EDS acquisition parameters were justified from physics, electronics, and counting statistics rather than merely adopted by standards committees. It also shows which values are true optima, which are practical conventions, and how they shift for low-voltage and trace-level analysis.*\n\nSeveral observations emerge regarding the nature of these recommendations:\n\n- The **overvoltage ratio** of ~2\u20133 reflects a genuine but broad physics optimum: the Bethe cross-section maximum is broad, and the exact best value depends on whether one prioritizes intensity, spatial resolution, or matrix-correction accuracy. ISO 22309:2011 codified a floor of 1.8, which is a conservative standardization of the physics (pqac-00000053).\n\n- The **dead-time** guidance evolved from 20\u201340% (Si(Li) era, optimizing stored-count rate) to <10% (SDD era, minimizing coincidence peaks for trace analysis) as detector technology changed. No published round-robin explicitly validated the 20\u201340% range; it was derived from dead-time throughput curves and practical experience (pqac-00000009).\n\n- The **process time** setting has a genuine electronics optimum (the ENC minimum), but the commercially available settings and naming conventions differ between vendors, making the specific recommendation partly instrument-dependent (pqac-00000015, pqac-00000026).\n\n- The **10,000-count rule** is a direct mathematical consequence of Poisson statistics and is not convention. The translation into specific live-times depends entirely on count rates, which depend on all other parameters.\n\n- **Currie's 3.29\u03c3 detection limit** is a rigorous derivation from Neyman-Pearson hypothesis testing at specified error rates, not an empirical guess. The common simplification to \"3\u03c3\" is a minor approximation that has become conventional shorthand (pqac-00000021).\n\nRegarding interlaboratory validation, Newbury and Ritchie (2015) demonstrated that the k-ratio/matrix correction protocol with SDD-EDS achieves accuracy matching the WDS distribution established in 1975 (approximately 2.5% relative standard deviation for major constituents, with ~95% of analyses falling within \u00b15% relative error) (pqac-00000041). However, no published round-robin study was identified that systematically varied EDS acquisition parameters (overvoltage, dead-time, process time) across laboratories to validate the specific recommended ranges. The standards appear to have been written by codifying well-understood physics relationships and experienced practitioners' consensus within ISO TC 202 and ASTM E04 committees.\n\n### 7. Shifts for Low-Voltage Microanalysis and Trace Quantification\n\n**Low beam energy (\u22645 keV).** At low voltage, the conventional parameter optima shift significantly. A beam energy of 5 keV represents the lowest value at which at least one characteristic X-ray peak can be excited for all elements of the periodic table except H and He (pqac-00000043). At lower voltages, an increasing number of elements becomes inaccessible. The analyst is forced to use unfamiliar X-ray families (e.g., Ba M-family instead of Ba L-family) which may suffer severe mutual interferences, as demonstrated for YBa\u2082Cu\u2083O\u2087 analyzed at 5 keV where O K, Cu L, and Ba M families overlap (pqac-00000045). Rinaldi and Llovet (2015) documented systematic deviations in transition-element analysis at low voltages (5\u20136 keV), including Cr underestimation (\u22120.7% to \u221217%) and Fe/Ni overestimation (+14% to +42%), attributed to problems with mass absorption coefficients and low fluorescence yields for L-lines (pqac-00000028). The interaction volume reduction (approximately 100-fold decrease from 20 keV to 1 keV) improves spatial resolution to the sub-micrometer scale but reduces absolute X-ray yield per electron, requiring higher beam currents or longer counting times (pqac-00000031). Surface contamination layers and native oxides, which are negligible at 20 keV, become significant contributors to the measured spectrum at low voltage (pqac-00000043).\n\n**Trace-element quantification near 0.5\u20131 wt%.** For Mg K\u03b1 (1.254 keV) at 0.5\u20131 wt% in AlSi10Mg measured at 5 keV with an SDD, the overvoltage is generous (U\u2080 \u2248 4.0), so excitation efficiency is not limiting. The challenges are instead: (a) the Mg K peak sits in a crowded low-energy region where Al K (1.486 keV) is a dominant neighboring peak; (b) peak-to-background ratios for the Mg peak depend on the continuum modeling and the detector response at low energies; (c) the absorption correction for low-energy photons becomes large and uncertain; and (d) surface contamination carbon deposition can increase absorption of X-rays near the carbon K-edge (0.284 keV) and affect quantification of light elements. Newbury and Ritchie showed that detection limits of 200\u2013500 ppm (0.02\u20130.05 wt%) are achievable at conventional voltages within 500 s counting time (pqac-00000034), but at low voltage the effective detection limit for a given counting time may be worse due to increased background relative to peak and poorer matrix-correction accuracy (pqac-00000030). For reliable quantification of 0.5\u20131 wt% Mg, standards-based analysis with well-characterized standards and careful peak fitting is essential; standardless methods showed ~95% of results within \u00b125% relative deviation in early testing, an unacceptable error for trace-level work (pqac-00000039). The practical recommendation is to collect substantially more counts than the simple 10\u2074-count rule would suggest (several 10\u2075 to 10\u2076 total spectrum counts), use a moderate process time prioritizing spectral stability over maximum throughput, keep dead time conservatively low to avoid pile-up artifacts in the energy region of interest, and employ multiple replicate measurements with statistical quality-control tests to monitor drift and damage (pqac-00000038, pqac-00000054).",
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+                "context": "# Summary\n\nThe excerpt does not address the question. It discusses practical aspects of EDS performance measurement, specifically count-rate linearity testing procedures. The text explains that \"dead-time\" is the period when a pulse processor is busy processing X-ray events and unavailable for new events, while \"live-time\" is when it is available. It notes that \"effective probe dose\" equals live-time multiplied by probe current, and that \"effective probe dose is always less than the real probe dose.\" The excerpt describes a testing procedure (Check 5) involving a Faraday cup, picoammeter, and polished copper sample at 15\u201325 keV to verify count-rate linearity.\n\nThe excerpt contains no information about the historical derivation of standard SEM-EDS acquisition parameters, ionization cross-sections, dead-time models, pulse-shaping trade-offs, Poisson statistics, Currie's detection limits, or low-voltage/trace-element considerations requested in the question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                      "John Henry J. Scott",
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+                    "formatted_citation": "Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations."
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+                "context": "# Summary\n\nThe excerpt discusses practical aspects of EDS parameter selection, specifically addressing process time (pulse shaping) and working distance optimization.\n\n**Process Time:** The text explains that process time involves \"balancing good throughput with adequate resolution\"\u2014a trade-off where longer process times reduce throughput but improve spectral resolution, while shorter times increase throughput at resolution's expense. Importantly, \"resolution degrades relatively slowly while throughput increases quickly,\" allowing \"moderate pulse process times\" to degrade resolution by only a few percent while increasing throughput by larger factors. The excerpt recommends compromising ultimate SDD resolution (122\u2013128 eV) to \"130\u2013135 eV will produce an excellent compromise,\" noting that \"precision of spectrum fitting is more determined by the number of measured X-rays than the spectral resolution.\"\n\n**Working Distance:** The optimal working distance should be where \"the axis along the detector snout intersects with the electron beam axis,\" producing \"the largest flux of X-rays\" and minimizing sensitivity to vertical positioning errors.\n\nHowever, **the excerpt does not address** the underlying physics models (ionization cross-sections, Bethe formulation, dead-time models, counting statistics, or Currie's criterion) or low-voltage/trace-element applications requested in the question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "This excerpt does not address the question posed. The excerpt focuses on practical SEM-EDS measurement procedures and quality control: specifically, linearity testing of detector response to probe dose (Figure 16.23 showing counts scaling with probe dose; R\u00b2 = 0.9999923818), energy calibration protocols using characteristic X-ray lines (Mn K-L\u2082,\u2083 or Cu K-L\u2082,\u2083), and consistency of peak position and width across different count rates (Figure 16.24). \n\nThe excerpt describes *how to validate* that acquisition parameters are properly set, but does **not** trace the derivation of recommended parameter values themselves\u2014overvoltage ratios, dead-time fractions, process times, count statistics, or the Currie criterion. It contains no discussion of ionization cross-section physics (Bethe, Green & Cosslett), electron range models (Kanaya-Okayama), pulse-shaping electronics, Poisson statistics, or low-voltage/trace-element considerations. The excerpt is procedural guidance, not foundational scientific justification for the standards.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt does not address the question about how recommended SEM-EDS acquisition parameters are derived from fundamental physics and statistics. Instead, it provides practical operational guidance for SEM-EDS users.\n\nThe excerpt covers: (1) finding optimal working distance by collecting 60-second live-time spectra at different stage positions and plotting total counts versus working distance to identify the inflection point of maximum sensitivity; (2) detector orientation verification using wide field-of-view X-ray spectrum images on copper at 20\u201325 keV to confirm on-axis efficiency peaks; (3) window support grid design (e.g., AP3 and AP5 grids with 76\u201378% open area and rib widths of 45\u201359 \u00b5m); and (4) data processing methods using ImageJ-Fiji to extract and map raw intensities across spectrum images.\n\nThe text emphasizes practical checks and does not derive or justify the canonical parameter values (U\u2080 = 2\u20133, dead time ~20\u201340%, 10,000 net counts, 3-sigma criterion) from underlying physics models, cross-section measurements, counting statistics, or primary literature validation.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThe excerpt demonstrates practical SEM-EDS quantitative analysis at moderate beam energies (10\u201320 keV) for major and minor constituents, emphasizing how high-count spectra enable precise measurements despite severe peak interference.\n\n**Key observations:**\n\n- **Beam energy effects:** Lowering beam energy from 20 to 10 keV reduces absorption correction factors (e.g., A-correction for S in FeS2 from 1.18 to 1.06) and relative errors (0.88% to 0.65%), illustrating the trade-off between overvoltage and absorption.\n\n- **High-count spectra:** PbS and MoS\u2082 analyses used >5 million integrated counts, enabling peak-fitting deconvolution of severely overlapping lines (S K-L\u2082 and Pb M\u2085-N\u2086,\u2087 separated by 36 eV; S K-L\u2082 and Mo L\u2083-M\u2084,\u2085 by 14 eV) with relative deviations \u22641.2%, demonstrating that \"high counts and stable peak structures are critical for successful peak intensity measurements.\"\n\n- **Counting precision:** Replicate analyses show \u03c3_rel values of 0.05\u20130.21% at major-element concentrations, consistent with Poisson statistics and the ~10\u2074-count guidance.\n\nThe excerpt does not directly address the *derivation* of standard parameter recommendations or low-voltage/trace-element optimization.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt addresses dead-time management in SEM-EDS detector operation, providing empirical guidance for beam-current selection:\n\n**Dead-time definition and throughput model:** Dead-time is quantified as `100 \u00d7 (ICR \u2212 OCR) / ICR`, where output count rate (OCR) initially rises linearly with input count rate (ICR) but eventually peaks and falls as photon coincidence increases\u2014characteristic of \"paralyzable dead-time\" behavior.\n\n**Recommended dead-time values:** For Si(Li)-EDS, a \"classic strategy\" targets \u226430% dead-time on highly excited pure elements (Al, Si). For SDD-EDS, a \"more conservative\" approach recommends <10% dead-time \"on the most highly excited standard\" to minimize coincidence peaks, which become visible above ~10% dead-time (Figure 20.3).\n\n**Trade-off logic:** The excerpt explicitly acknowledges a trade-off: lower dead-time reduces coincidence artifacts (important for trace elements), whereas higher dead-time improves counting throughput if coincidence-affected spectral regions are not analytically relevant.\n\n**Validation reference:** The text cites Newbury and Ritchie (2015b) for k-ratio/matrix-correction protocol implementation, linking dead-time strategy to measurement consistency across standards and unknowns.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                      "Joseph I. Goldstein",
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+                      "Joseph R. Michael",
+                      "Nicholas W. M. Ritchie",
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+                "context": "# Summary\n\nThis excerpt from a scanning electron microscopy text discusses instrumental parameters for EDS analysis but does not directly address the historical derivation of recommended values requested in the question.\n\nThe passage covers:\n\n**EDS time constant (shaping time):** Explains the fundamental trade-off: \"A short time constant enables more photons to be processed per unit of real (clock) time, but the trade-off of faster processing is poorer accuracy in assigning the photon energy.\" Example given: Mn K-L\u2082,\u2083 natural width ~7 eV (FWHM) broadens to \"122\u2013150 eV FWHM or more, depending on the choice of time constant.\" States that longer time constants are chosen for quantitative analysis requiring better peak resolution.\n\n**Beam energy selection:** Recommends \"20 keV\" as starting point to \"optimize the excitation of photon energies up to 12 keV\" with \"sufficient overvoltage (E\u2080/E\u2092 > 1.5).\" For low atomic number elements (Be, B, C, N, O) with peaks below 1 keV, recommends \"10 keV or lower.\"\n\n**Solid angle formula:** Provides \u03a9 = A/r\u00b2, noting \"A consistent and reproducible choice must be made for r since this value has such a strong impact on \u03a9.\"\n\nThe excerpt provides operational guidance but lacks the primary literature citations, physics derivations, and historical validation experiments the question specifically requests.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt demonstrates practical SEM-EDS analysis of major constituents (FeS and FeS\u2082) using the k-ratio/matrix-correction protocol with DTSA II software (Newbury and Ritchie 2015b). The analysis shows measurements at E\u2080 = 20 keV with ~10% dead time, yielding well-resolved Fe K/L and S K peaks with integrated spectrum counts of ~7 million (Fig. 20.4). \n\nKey results from Table 20.1 (FeS at 20 keV): relative standard deviation \u03c3_Rel = 0.15%, RDEV = \u00b11.00%, with seven replicates. The excerpt emphasizes that \"careful examination of these factors [ZAF corrections and counting-statistic uncertainties] can be used to refine the analytical strategy to optimize the measurement,\" noting that \"reducing the uncertainty due to counting statistics requires increasing the dose.\" Newbury and Ritchie (2012) quantify individual error components (counting error, A-factor error, Z-factor error) for uncertainty budgeting. Tables 20.3 and 20.4 extend this to lower voltage (10 keV), suggesting energy-dependent optimization strategies, though the excerpt does not detail the derivation of recommended parameter values or trace-element behavior.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt addresses practical EDS detector setup and geometry rather than the derivation of acquisition parameters themselves. It focuses on:\n\n**Detector positioning and solid angle:** The excerpt explains how detector-to-sample distance affects solid angle (\u03a9) and collection efficiency, with procedures to maintain reproducible positioning using lock nuts on motorized or manual mechanisms. It emphasizes that \"characteristic peak intensities are reproducible (to much better than a fraction of a percent) between insertions\" as a precision criterion.\n\n**Elevation and take-off angles:** It distinguishes elevation angle (a fixed instrument property) from take-off angle (dependent on sample tilt and working distance), noting these angles are critical for matrix-correction algorithms that \"calculate the correct absorption.\"\n\n**Al K coincidence peak ratio:** One specific quantitative criterion mentioned is setting the Al K + Al K coincidence-peak ratio below 0.01 (1%), or below 0.001 (0.1%) for trace analysis, to limit spectral artifacts while managing throughput.\n\nHowever, the excerpt does **not** derive the ionization cross-section optimization, dead-time modeling, pulse-shaping physics, Poisson statistics, or Currie's detection-limit criterion that underpin the recommended parameter values.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                      "Joseph I. Goldstein",
+                      "Dale E. Newbury",
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+                "context": "# Summary\n\nThis excerpt from a scanning electron microscopy textbook (Chapter 16 on Energy Dispersive X-ray Spectrometry) focuses on **quality control (QC) programs for EDS detectors** rather than deriving the foundational acquisition parameters themselves.\n\nThe excerpt describes practical QC implementation: maintaining a reference sample (Faraday cup with Cu or Mn), collecting spectra under consistent conditions (working distance, beam energy, probe current, live time), and extracting metrics like K and L-line intensities, energy resolution, zero offset, gain, and total counts plotted on control charts. It specifies one key acquisition principle\u2014\"**The beam energy should be sufficient to adequately excite (overvoltage > 2) all the lines of interest**\"\u2014but does not derive *why* the 2\u20133 overvoltage rule exists.\n\nThe excerpt provides no discussion of ionization cross-sections, dead-time throughput models, pulse shaping trade-offs, Poisson statistics, Currie's 3-sigma criterion, or low-voltage/trace-element optimization. It emphasizes detector calibration and long-term performance monitoring via standardized reference materials, not the underlying physics or counting-statistics derivations that originally justified standard acquisition values.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                    "authors": [
+                      "Joseph I. Goldstein",
+                      "Dale E. Newbury",
+                      "Joseph R. Michael",
+                      "Nicholas W. M. Ritchie",
+                      "John Henry J. Scott",
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+                "context": "# Summary\n\nThis excerpt from Goldstein et al.'s textbook presents the k-ratio/matrix correction protocol for SEM/EDS quantitative analysis but **does not derive the recommended parameter values from first principles**. \n\nThe text discusses instrumentation requirements, including:\n- **Specimen homogeneity** requirements for the interaction volume (0.5\u201310 \u03bcm for primary X-rays; 10\u2013100 \u03bcm for secondary fluorescence)\n- **EDS parameter consistency**: beam energy, electron dose (beam current \u00d7 live time with dead-time correction), detector solid angle, time constant, take-off angle, and tilt angle\n- **Spectrum binning**: recommends 5 eV channel width to adequately span characteristic peaks (e.g., C K at ~50 eV FWHM requires \u226510 channels), with spectrum spanning ~100 eV to the Duane\u2013Hunt limit\n\nHowever, the excerpt provides **no derivation of why U\u2080 \u2248 2\u20133, why dead time should be 20\u201340%, how pulse-shaping time trades resolution against throughput, why 10,000 net counts achieves ~1% precision, or how Currie's 3-sigma criterion was established**. It references the protocol using \"NIST DTSA-II software\" but does not trace the underlying physics models, cross-section data, or counting-statistics foundations requested in the question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "The excerpt describes a new method for dead time calibration in microanalysis using a logarithmic dead time correction expression applicable over a wider range of count rates (8-10 times greater) than traditional linear expressions. The Poisson Monte Carlo modeling approach simulates detector behavior where detection of a photon causes the detector to become dead for a period \u03c4. During this dead time, any additional photons reaching the detector are not detected but are tracked in the total emitted photon count. The simulation requires that the time interval T be much smaller than the detector dead time \u03c4 (ideally 20-200 times smaller) and be a multiple of \u03c4. The method enables calibration of dead time constants and simultaneous k-ratio testing of multiple spectrometers. However, the excerpt does not provide detailed information about the specific relationship between output and input count rates, paralyzable dead-time theory, optimization of dead-time percentages, or anti-coincidence functions.",
+                "question": "What is the dead-time model for EDS detectors? How does output count rate relate to input count rate? What is paralyzable dead-time and why does dead-time of 20-40% or 10% give optimal throughput? What is the anti-coincidence function?",
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+                "snippets": [
+                  "we present a new method for calibration of dead time constants, picoammeter calibration, and simultaneous k-ratio testing of multiple spectrometers",
+                  "we present a new logarithmic dead time correction expression which is applicable over a wide range of count rates, typically 8 to 10 times greater than typically utilized with the traditional linear dead time expression",
+                  "the detector becomes dead for a period of time corresponding to the dead time \u03c4",
+                  "the time interval T must be much smaller than the detector dead time \u03c4 (ideally 20 to 200 times smaller) and T must be a multiple of \u03c4"
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+                "context": "The excerpt mentions that EDS systems utilize hardware electronics-based dead time corrections that extend the acquisition time to account for dead time effects, in contrast to WDS systems which use software-based corrections. However, the excerpt does not provide detailed information about the specific dead-time model for EDS detectors, the relationship between output and input count rates, paralyzable dead-time theory, optimal throughput percentages, or anti-coincidence functions. These topics are mentioned as areas where previous attempts have been made but are not elaborated upon in this excerpt.",
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+                  "the EDS system can measure only one X-ray photon at a time, so that it is effectively unavailable if another photon arrives while the system is \"busy\" measuring the first p",
+                  "as the flux of X-rays increases, an increasing frequency of events will occur in which the time separation between the two events is too short for the anti-coincidence function to recognize and reject the separate photons, resulting in an artifact sum photon",
+                  "Selecting a Beam Current for an Acceptable Level of System Dead-Time",
+                  "X-rays are generated randomly in time with an average rate determined by the flux of electrons striking the specimen, thus scaling with the incident beam current"
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+                  "the EDS system can measure only one X-ray photon at a time, so that it is effectively unavailable if another photon arrives while the system is \"busy\" measuring the first photon",
+                  "Deadtime ( % ) = ( ICR \u2212 OCR ) / ICR \u00d7 100%",
+                  "An automatic correction function measures the time increments when the detector is busy processing photons, and to compensate for possible photon loss during this \"dead-time,\" additional time is added",
+                  "Depending on the separation in the time of arrival of the second photon, the anti-coincidence function will exclude the second photon, but if the measurement of the first photon is not sufficiently advanced, both photons will be excluded from the measurement and effectively lost",
+                  "The relation between the OCR and ICR is shown in Fig. 16.9 for a four-detector SDD-EDS"
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+                  "EDS systems are capable of processing only one photon at a time",
+                  "A conservative count rate that yields a deadtime of approximately 10 % or less is recommended to minimize coincidence artifacts",
+                  "concentrations and detector time constant coincidence becomes visibly significant above 15 % deadtime"
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+                "context": "The excerpt discusses the fundamental trade-off in EDS detectors between pulse process time, energy resolution, and throughput. Longer pulse process times achieve better energy resolution but produce poor ultimate throughput. Conversely, shorter pulse process times maximize throughput but introduce coincidence events (pulse pile-up) that limit quantitative accuracy. The document indicates that optimal detector performance involves a three-way trade-off between throughput, resolution, and coincidence rate. Practically, operators define an acceptable coincidence rate and select a process time that maximizes throughput while maintaining that rate, typically sacrificing only a few eV of resolution quality. This resolution compromise is deemed acceptable since accurate quantitative analysis prioritizes throughput over optimal resolution. However, the excerpt does not specifically address the electronic noise and series noise components or their detailed relationship to determining optimal shaping time.",
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+                  "The quantitative performance of the detector is three-way trade-off between throughput, resolution, and coincidence rate. Typically, this is accomplished by defining an acceptable coincidence rate as discussed in the section on process time and determining the process time that maximizes the throughput at this coincidence rate.",
+                  "This process time will typically be a slight compromise from the one that produces the optimal resolution but typically not by more than a few eV FWHM at Mn K-L2,3 (K\u03b1). A few eV of resolution degradation is usually an acceptable compromise as throughput is far more important than resolution for accurate quantitative EDS microanalysis."
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+                  "At the best resolution settings, throughput is seriously compromised and as a result the precision of quantitative analysis is also compromised. At the highest throughput settings, resolution is compromised and it becomes much more difficult to distinguish interfering peaks.",
+                  "Fortunately, resolution degrades relatively slowly while throughput increases quickly. Moderate pulse process times tend to degrade the ultimate resolution by a few percent, while increasing throughput by much larger factors.",
+                  "While some modern SDD are capable of ultimate resolutions of 122\u2013128 eV, compromising the resolution to 130\u2013135 eV will produce an excellent compromise between resolution and throughput.",
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+                  "In the absence of pulse shaping, these differences in rise times are significant. We show that the signal amplitude (i.e., proportional to the detected energy and obtained from fitting with the pulse function), rise time and pulse height are interrelated; variation in rise times of individual pulses must be taken into account in a function fit for optimal energy resolution in the absence of pulse shaping."
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+                  "Waveform fitting yields simultaneously high energy resolution and high counting rates (2 orders of magnitude higher than current digital pulse processors)",
+                  "signal amplitude and rise time are obtained for each pulse by fitting, thus removing the need for pulse shaping"
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+                "context": "The excerpt discusses the tradeoff between pulse processing parameters and detector performance. It describes a fundamental compromise in typical pulse processing between counting rate (achieved with short rise times) and energy resolution (requiring long rise times through pulse shaping), necessitating selection of an appropriate peaking time. However, the authors present an alternative approach using pulse waveform fitting with pulse functions rather than traditional pulse shaping. This fitting method eliminates the need for pulse shaping while achieving fast pulse onset, improved pulse separation, and the ability to handle multiple overlapping pulses. The method extracts precise amplitude and timing information by fitting each pulse waveform to a combined gradual step function and exponential decay model.",
+                "question": "What is the relationship between pulse process time (shaping time) and energy resolution vs throughput in SDD-EDS detectors? How does electronic noise and series noise trade-off determine optimal shaping time?",
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+                  "Typical pulse processing involves a compromise between counting rate (with short rise times) and energy resolution (long rise times through pulse shaping) by choosing an appropriate peaking time.",
+                  "In the absence of pulse shaping, the pulse height or pulse area are not optimal estimators for the detected photon energy (due to variation in peaking times). Instead, the optimal estimator is signal amplitude, obtained (together with the rise time) by fitting each pulse waveform with the pulse function. This removes the need for pulse shaping, resulting in fast pulse onset and improved pulse separation, allowing fitting of multiple pulse pile-up.",
+                  "We present a pulse processing method based on fitting individual, overlapping pulses with pulse functions (a combination of gradual step function and exponential decay) which allows extracting (in the time domain) precise amplitude and timing information in the presence of pulse pile-up and clipping."
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+                "context": "The excerpt demonstrates the inverse relationship between pulse processing time constant (shaping time) and detector performance metrics in SDD-EDS systems. Shorter time constants enable higher throughput (OCR) but with a resolution trade-off. For example, a 500 ns time constant achieves resolution below 130 eV (MnK\u03b1), while reducing the time constant to 220 ns increases maximum OCR to 270 kHz but degrades resolution to 145 eV. The text illustrates that SDD-EDS detectors significantly outperform Si(Li)-EDS in throughput capability (by a factor of at least 60 for similar resolution), and this improved count rate performance enables collection of statistically robust spectra within practical measurement intervals. However, the excerpt does not explicitly discuss the underlying noise mechanisms (electronic noise vs. series noise) or the theoretical optimization process for determining optimal shaping time based on noise trade-offs.",
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+                  "To achieve resolution below 130 eV (MnK\u03b1) typically requires a time constant of 500 ns or less for SDD-EDS compared to ~30 \u03bcs for Si(Li)-EDS",
+                  "By choosing a shorter time constant (220 ns) that degrades the resolution to 145 eV, the single SDD-EDS detector can reach a maximum OCR of 270 kHz",
+                  "the OCR vs. ICR performance of SDD-EDS greatly exceeds that of Si(Li)-EDS, and this level of performance directly translates into significant improvements in quantitative analysis"
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+                "context": "# Summary\n\nThis excerpt from Currie's foundational 1999 paper on detection and quantification limits addresses the historical confusion surrounding detection limit definitions and terminology in analytical chemistry. \n\nCurrie traces decades of miscommunication, noting that when early detection limit concepts were applied to the same measurement process, \"numerical values that spanned three orders of magnitude\" resulted. He distinguishes two competing schools: the \"signal/noise school\" recognizing only false positives (\u03b1, Type-1 error) with false negative probability defaulting to 50%, versus the \"hypothesis testing school\" employing independent \u03b1 and \u03b2 values, \"commonly each equal to 0.05.\"\n\nThe paper describes how the 1995 IUPAC and ISO harmonization efforts established internationally coordinated standards based on sound statistical foundations. Currie emphasizes the critical distinction between the critical value (LC)\u2014above which a decision of \"detected\" is made\u2014and the true detection capability (LD) of the measurement process itself. The excerpt highlights that proper detection limit calculations require careful attention to statistical assumptions, blank characterization, and the role of measurement process specification.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt from Currie's foundational work on detection and quantification limits addresses the statistical framework for analytical measurements. Key points:\n\n**Detection/Quantification Limits Framework:**\n- Detection limit (LD) and quantification limit (LQ) are derived from hypothesis-testing error rates (\u03b1 = \u03b2 = 0.05), yielding expressions like LC = 1.645\u03c3B and LD = LC + 1.645\u03c3D\n- For linear calibration with 4% asymptotic relative standard deviation, the ratio LQ/LD increases from 3.04 to 4.73\n- The blank variability (\u03c30) is identified as \"the fundamental contributing factor\" to detection performance\n\n**Key Conceptual Issues:**\n- Detection/quantification limits cannot be specified without a \"fully defined measurement process\" including interference types, data reduction algorithms, and all sources of uncertainty\n- \"\u03c30 or its estimate s0\" selection requires accounting for heteroscedasticity and the complete error budget\n- The measurement process specification is \"absolutely essential\"\u2014limits derived in isolation may not reflect actual performance when sampling, separation, interference, and matrix effects are present\n\nThe excerpt emphasizes that detection limits are process-dependent variables requiring rigorous statistical definition rather than universal constants.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "## Summary\n\nThis excerpt from Currie's 1999 paper on detection limits discusses the foundational statistical framework for detection and quantification, but does **not** address the specific SEM-EDS acquisition parameters or their derivations asked about in the question.\n\nThe excerpt focuses on:\n- **Sampled vs. target populations** in measurement processes and interlaboratory variation, explaining how systematic errors (e\u2081) and random errors (e\u2082) affect uncertainty estimates\n- **The critical role of blanks** in trace analysis, particularly near detection limits\u2014requiring ~50 observations to estimate blank standard deviation with 10% relative standard deviation\n- **Three blank types**: instrumental background, baseline (background plus interfering signals), and chemical blank (from contamination)\n- **Blank assessment approaches**: external (ideal/surrogate blanks with identical matrix) and internal (\"propagation of the blank\" examining each process step)\n\nThe excerpt does **not** derive or justify overvoltage ratios, dead-time fractions, process times, count statistics linking peak counts to precision, or the 3-sigma detection criterion itself. It establishes the statistical hypothesis-testing framework within which detection limits operate but stops short of the physics and primary experimental validation underlying specific SEM-EDS parameter recommendations.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThe provided excerpt discusses detection limits and decision criteria in analytical chemistry, particularly Currie's framework for distinguishing detection capability (LD) from requisite limits (LR) using probability density functions and critical values (LC). It references Currie's seminal 1968 paper (\"Limits for qualitative detection and quantitative determination,\" *Anal. Chem.* 40:586) and the subsequent 1995 IUPAC Recommendations on evaluation of analytical methods.\n\nThe text describes error-rate parameters (\u03b1 and \u03b2), noting that \"0.05 is the recommended default value\" but particular circumstances may require more stringent control of one parameter over the other. However, **the excerpt does not provide the detailed derivations of the recommended parameter values for SEM-EDS acquisition parameters** (overvoltage ratio, dead time, shaping time, count statistics, or the 3-sigma criterion). It establishes the conceptual framework for detection decisions but does not trace the physics models, cross-section measurements, counting-statistics calculations, or validation experiments underlying specific SEM-EDS guidance values in ISO 22309 or ASTM E1508.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt from Currie's foundational 1999 paper on detection limits covers the hypothesis-testing framework underlying the 3-sigma detection criterion. Key points:\n\n**Detection limit derivation**: Under normal distribution assumptions with default error rates (\u03b1 = \u03b2 = 0.05), the detection limit is expressed as LD = 2LC + 3.29\u03c3\u2080 (equation 5a), where LC (critical value) = 1.645\u03c3\u2080 and \u03c3\u2080 is the standard deviation under the null hypothesis. This yields the \"3.29-sigma\" criterion commonly approximated as \"3-sigma.\"\n\n**Quantification limit**: LQ = 10\u03c3\u2080 (equation 6), corresponding to ~10% relative standard deviation (RSD).\n\n**Type I vs. Type II errors**: The \"hypothesis testing school\" employs independent \u03b1 and \u03b2 values (commonly 0.05 each), unlike the older \"signal/noise school\" that implicitly set \u03b2 = 50%. This distinction directly determines whether false negatives are accounted for in the detection criterion.\n\nThe excerpt emphasizes that these are *a priori* performance characteristics derived from statistical theory, not empirical observations, and notes heteroscedasticity issues (variance depending on signal level, as in Poisson processes) require adjustment of these simplified relations.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary of Excerpt\n\nThis excerpt describes silicon drift detector (SDD) readout electronics and signal processing, **not SEM-EDS acquisition parameters or their derivation**. \n\nThe text covers two readout configurations:\n\n1. **Source-follower readout** with self-reset mechanism: rise time *t_r* (typically 80\u2013100 ns for 10 pF load) is determined by capacitances (*C_d*, *C_gs*, *C_L*) and transistor parameters (*g_m*, *g_ds*) via equations (1)\u2013(4). The self-reset uses avalanche breakdown in the transistor channel to compensate signal electrons.\n\n2. **Charge-sensitive amplifier (CSA) readout**: Uses parasitic capacitor *C_a-ig* as feedback, overcoming rise-time limitations. The transfer function (equation 5\u20136) depends on time constants *t_1* = *R_d C_a-ig* and *t_2* = *R_fb C_in*, with *t_1* << *t_2*.\n\nThe excerpt does not address ionization cross-sections, overvoltage optimization, dead-time models, Poisson statistics, Currie detection limits, or low-voltage/trace-element considerations requested in the question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                      "H. Soltau",
+                      "G. Lutz",
+                      "L. Str\u00fcder",
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+                    "url": "https://doi.org/10.1016/j.nima.2006.06.025",
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+                "context": "# Summary\n\nThis excerpt describes silicon drift detector (SDD) readout configurations and performance characteristics, focusing on charge-sensitive amplifier (CSA) versus source-follower (SF) readout modes. Key experimental results include:\n\n**Energy Resolution and Count Rate:** At 1 ms shaping time with ~1 kcps input rate, both readout configurations show similar noise performance determined by detector capacitance and input transistor properties. At 250 ns shaping time, energy resolution degrades with increasing input count rate due to reset current effects (Fig. 8).\n\n**Peak Position Stability:** The self-reset mechanism causes peak position shifts with changing input count rate (Fig. 9), explained by capacitance variations (Cd = Cgd + Cafig + Car1 + Cbulk). Peak shift compensation circuits can reduce this to \u00b10.03% (\u00b12 eV at 5.9 keV) up to 400 kcps.\n\n**Pulsed Reset Mode:** The excerpt introduces pulsed reset operation using an integrated reset diode, with CSA readout configuration (Fig. 4), though detailed performance data for this mode appears incomplete in the provided text.\n\nThe excerpt does **not** address the derivation of recommended acquisition parameters (overvoltage, dead time, shaping time, count statistics, or detection limits) from fundamental physics principles or primary literature as requested in your question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt focuses on silicon drift detector (SDD) technology and energy resolution optimization, specifically describing the SD3 chip design. Key technical details include:\n\n**Detector Design & Noise:** The SD3 achieves reduced anode capacitance (~120 fF vs. 200 fF in standard SDDs) by minimizing readout node area. Electronic noise comprises serial white noise, serial 1/f noise, and parallel noise, quantified by equation ENC\u00b2 = A\u2081(2k_BTC\u00b2/g_m) + A\u2082af C\u00b2 + A\u2083qI_l, where shaping time \u03c4 and detector capacitance C are critical parameters.\n\n**Energy Resolution Performance:** At 1.0 \u00b5s shaping time and -15\u00b0C, the SD3 achieves 128 eV energy resolution at Mn K-\u03b1 (5.9 keV) with ~100 cps count rate, approaching the theoretical Fano-noise limit of 118 eV. The excerpt demonstrates the ballistic-deficit trade-off: shorter shaping times (0.25 \u00b5s) worsen resolution; longer times (2.0 \u00b5s) improve it but reduce count-rate capability.\n\nHowever, the excerpt does **not** address the fundamental physics derivations, counting-statistics justifications, or historical origins of the recommended SEM-EDS acquisition parameters (overvoltage ratios, dead-time percentages, peak counts, or Currie detection limits) requested in the question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt addresses SDD (silicon drift detector) optimization for X-ray microanalysis, particularly at low energies. Key technical points include:\n\n**Energy Resolution and Noise:** Electronic noise dominates at low X-ray energies. Reducing total detector capacitance from 150 to 80 fF (via \"droplet SDD\") and lowering leakage current to 200 pA/cm\u00b2 improves FWHM. A pn-Window entrance modification reduces partial charge collection at low energies, achieving FWHM values of 38 eV for Boron (138 eV line) and 42 eV for Carbon (277 eV line).\n\n**Shaping Time Optimization:** Figures 6\u20137 show FWHM at Mn K\u03b1 versus shaping time peaks at optimal values of 2\u20133 \u03bcs, achieving 129 eV FWHM, demonstrating the noise-versus-throughput ballistic trade-off.\n\n**Count Rate Performance:** Charge-sensitive amplifier readout with pulsed reset maintains \"nearly constant energy resolution up to a few hundred kcps,\" and multi-cell SDD arrays handle input rates up to 3 Mcps while preserving ~140 eV energy resolution.\n\n**Detector Geometry:** Peak/background ratio improvements and detection efficiency increase through area maximization, solid-angle optimization, and collimator design.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                    "citation": "D.M. Schlosser, P. Lechner, G. Lutz, A. Niculae, H. Soltau, L. Str\u00fcder, R. Eckhardt, K. Hermenau, G. Schaller, F. Schopper, O. Jaritschin, A. Liebel, A. Simsek, C. Fiorini, and A. Longoni. Expanding the detection efficiency of silicon drift detectors. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 624:270-276, Dec 2010. URL: https://doi.org/10.1016/j.nima.2010.04.038, doi:10.1016/j.nima.2010.04.038.",
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+                    "authors": [
+                      "D.M. Schlosser",
+                      "P. Lechner",
+                      "G. Lutz",
+                      "A. Niculae",
+                      "H. Soltau",
+                      "L. Str\u00fcder",
+                      "R. Eckhardt",
+                      "K. Hermenau",
+                      "G. Schaller",
+                      "F. Schopper",
+                      "O. Jaritschin",
+                      "A. Liebel",
+                      "A. Simsek",
+                      "C. Fiorini",
+                      "A. Longoni"
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+                    "publication_date": "2010-12-11T00:00:00Z",
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+                    "publisher": "Elsevier BV",
+                    "url": "https://doi.org/10.1016/j.nima.2010.04.038",
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+                "context": "# Summary\n\nThis excerpt discusses silicon drift detector (SDD) performance characteristics relevant to EDS analysis, focusing on detector-level optimization rather than the acquisition-parameter derivation requested.\n\n**Key technical content:**\n- Electronic noise quantified via \"ENC\" (equivalent noise charge) formula and measured at 5.7 electrons for 128 eV energy resolution\n- Temperature dependence: room temperature FWHM >200 eV for Mn K-\u03b1; cooling to \u221215 \u00b0C achieves optimal energy resolution\n- Shaping-time trade-offs: shorter times (0.5 \u00b5s) reduce leakage-current noise at room temperature; longer times (0.5\u20131.0 \u00b5s) manage serial noise at low temperature\n- **Count-rate performance:** SD3 detector maintains >180 eV FWHM for Fe K-\u03b1 at 10\u2075 counts/s with 0.5 \u00b5s shaping time\n- Peak-to-background (PTB) values dominated by partial events near the field-effect transistor and detector margins\n\n**Limitation:** This excerpt addresses detector physics and signal processing but does not trace the *historical derivation* of recommended acquisition parameters (overvoltage ratio, dead-time fraction, net-count targets, or Currie criterion), nor does it address low-voltage or trace-element quantification specifics requested in the question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                      "P. Lechner",
+                      "A. Pahlke",
+                      "H. Soltau"
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+                    "publication_date": "2004-07-01T00:00:00Z",
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+                    "journal": "X-Ray Spectrometry",
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+                "context": "The excerpt discusses low-voltage SEM microanalysis and acquisition parameter adjustments. It explains that lowering accelerating voltage improves spatial resolution and image quality, requiring selection of lower excitation energy X-ray lines (L- and M-family lines at 0-4 kV) rather than K-lines. Beyond voltage adjustment, reducing probe current and changing scan speed are necessary acquisition parameter modifications. The excerpt mentions improved detector technology with SDD detectors achieving greater X-ray collection efficiencies and better sensitivity for low-energy X-rays. New soft X-ray spectroscopy systems offer superior energy resolution and detection limits for light elements below 100 ppm. Higher accelerating voltages create larger interaction volumes that degrade spatial resolution, while lower voltages reduce the analytical volume. However, the excerpt does not specifically address overvoltage effects at 5 keV or detailed counting strategies for trace element detection.",
+                "question": "Newbury Ritchie low-voltage SEM EDS trace element detection limits sensitivity, how do acquisition parameters change at low beam energy, overvoltage effects at 5 keV, counting strategy for trace elements",
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+                  "By lowering the accelerating voltage a major improvement in the spatial resolution and image quality occurs. This forces the selection of X-ray lines with low excitation energy such as L- and M-family lines between 0 - 4 kV, rather than using K- and L-lines between 0 - 10 kV",
+                  "low voltage imaging and reducing charge not only involves adjusting the accelerating voltage to a lower value but also involves lowering the probe current and changing the scan speed to acquire the image",
+                  "Just becoming commercially available are new soft X-ray spectroscopy (SXES) systems, with a measurable energy range of 50 to 210 eV, an order of magnitude better energy resolution (with 0.3 eV resolution reported), and detection limits for light elements of less than 100 ppm",
+                  "the use of higher accelerating voltages usually results in larger interaction volumes, which consequently degrades the spatial resolution of the X-ray image and increases the analytical volume"
+                ],
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+                "context": "This excerpt discusses EDS capabilities for trace element detection and general measurement principles. It confirms that EDS can detect low-energy X-rays and perform trace-level measurements at higher mass fractions (0.1-1.0%). The authors explain that detection limits depend on the background-to-signal ratio. For EDS analysis, peak-to-background ratios are determined by channel ranges used for continuum and peak estimation, with optimal results typically achieved by integrating peaks over the central full-width half-max (FWHM) and equivalent continuum ranges. However, the excerpt does not specifically address low-voltage SEM operation at 5 keV, beam energy effects on acquisition parameters, overvoltage effects, or detailed counting strategies for trace elements. The discussion is limited to general principles rather than specific low-beam-energy protocols.",
+                "question": "Newbury Ritchie low-voltage SEM EDS trace element detection limits sensitivity, how do acquisition parameters change at low beam energy, overvoltage effects at 5 keV, counting strategy for trace elements",
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+                    "authors": [
+                      "N W M Ritchie",
+                      "D E Newbury",
+                      "H Lowers",
+                      "M Mengason"
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+                  "Low Z, low energy, and trace element detection have been demonstrated even in the presence of extreme peak interferences.",
+                  "Even higher level trace measurements (1.0 % mass fraction > Cz > 0.1 % mass fraction, where Cz is the mass fraction of element z) can be performed accurately with an SDD.",
+                  "Ultimately, limits of detection are constrained by the magnitude of the background (continuum) level relative to the signal (characteristic) level.",
+                  "The peak-to-background ratio on an EDS is determined by the ranges of channels used to estimate the continuum and peak intensity.",
+                  "Typically, integrating the peak over the central full-width half-max (FWHM) and an equivalent range of the continuum (above and below) produces close to optimal results."
+                ],
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+              {
+                "id": "pqac-00000032",
+                "context": "This paper by Golla-Schindler and Schneider addresses EDS (Energy Dispersive X-ray Spectroscopy) detection capabilities in low-voltage SEM, specifically focused on lithium detection and quantification in lithium-ion batteries. The work discusses how low accelerating voltages improve detection by increasing effective cross-sections for elastic and inelastic interactions, thereby generating more secondary and backscattered electrons. The study presents methods to reduce examination artifacts through lower accelerating voltages and beam currents. Key challenges addressed include contamination, radiation damage, and charging effects that can compromise EDS analysis accuracy. The authors demonstrate the use of a windowless Oxford Extreme EDS detector (100 mm\u00b2 size, 124.7 eV energy resolution for Mn) that enables low-energy X-ray detection. The paper also introduces a novel quantification method called 'Li by difference' for calculating lithium content from non-normalized EDS quantification. However, the excerpt provided does not contain specific information about Newbury-Ritchie detection limits, detailed acquisition parameters at specific beam energies like 5 keV, overvoltage effects, or counting strategies for trace elements.",
+                "question": "Newbury Ritchie low-voltage SEM EDS trace element detection limits sensitivity, how do acquisition parameters change at low beam energy, overvoltage effects at 5 keV, counting strategy for trace elements",
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+                  "The main topic of the paper is the new opportunities and challenges of low energy X-ray detection using EDS in the field of Li-ion battery analysis by using Low-Voltage SEM.",
+                  "This detector allows EDS investigations with lower accelerating voltages and beam currents. This can have a significant impact on the reduction of examination artefacts",
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+                  "If the primary energy of the incident electrons approaches the E2 point, the number of electrons remaining in the sample decreases."
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+                  "lowering the accelerating voltage a major improvement in the spatial resolution and image quality occurs",
+                  "This forces the selection of X-ray lines with low excitation energy such as L- and M-family lines between 0 - 4 kV, rather than using K- and L-lines between 0 - 10 kV",
+                  "measurement of low energy L-line X-rays is complicated by low fluorescence yield, an increase in X-ray absorption, numerous X-ray interferences from other elements within the sample, and less accurately determined mass absorption coefficients",
+                  "The use of transition element L-lines generally results in poor accuracy as well as poor sensitivity",
+                  "operating at low voltages has limitations due to the large quantification errors existing on the lower energy X-ray lines"
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+                  "As the structures under investigation become smaller and smaller, one of the constant challenges in dealing with analytical questions is to improve the resolution that can be achieved. A second important point is the detection limit, i.e., the detectability of increasingly smaller elemental contents. These points are addressed, when lowering the accelerating voltage.",
+                  "the information depth is approximately in between a third and the half of the electron range R",
+                  "This reduces the dimensions of the interaction volume in terms of both information depth and spatial resolution by a factor of approximately 100.",
+                  "The achievable detection limit depends on two main factors the scattering cross-section of the interaction and the signal's detection capabilities.",
+                  "beam damage caused by heating and ionisation is possibly enhanced due to the increasing cross-sections for inelastic and elastic scattering. Lowering the beam current, beam current density will reduce all beam damage effects"
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+                "context": "At low beam energies (<5 keV), FEG electron sources can achieve finely focused beams (<100 nm) with relatively high currents (up to 100 nA), reducing the effective ionization range to sub-micrometer scales and improving lateral resolution and surface sensitivity. For trace element analysis, detection limits of a few ppm are achievable through high-beam currents (up to 3 \u03bcA) and long acquisition times. Improved methods employ fractional counting times at multiple sample positions to mitigate beam damage, statistical data filtering, and improved background modeling. Analyses for trace elements at high resolution have been performed at 35 keV with 500 nA and total counting times of 15 minutes. However, at low voltages (5-6 keV), accuracy challenges arise with systematic deviations in transition element analysis, including Cr underestimation (-0.7 to -17%) and Fe/Ni overestimation (+14 to +42%), highlighting the need for careful standard selection and X-ray line choices at low overvoltages.",
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+                  "An FEG electron source yields a finely focused (<100 nm) electron beam with relatively high current (up to100 nA) even at low beam energies (<5 keV).",
+                  "At such energies, the effective ionization range of incident electrons drops from the conventional micrometer scale down to the sub-micrometer scale and leads to significant improvement in the lateral resolution and surface sensitivity of the technique",
+                  "These developments have made it possible to decrease the detection limits of the technique down to a few ppm by simply using high-beam currents (up to 3 \u03bcA) and long acquisition times.",
+                  "The latter authors developed a procedure to improve the detection limits as well as the precision and accuracy of trace analysis that includes fractional counting times at several sample positions (to mitigate sample damage), statistical data filtering, and improved background modeling.",
+                  "The analyses were performed at 35 keV, 500 nA, and total counting times of 15 min.",
+                  "The results showed an underestimation of the Cr contents, with relative deviations from the reference values ranging from \u22120.7 to \u221217%, and an overestimation of Fe and Ni, with relative deviations from the reference composition ranging from \u22124 to +30% and from +14 to +42%, respectively."
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+                  "Measurements of minerals containing minor and trace quantities (Cz < 10.0 % mass fraction) of REE are a challenge for both WDS and EDS.",
+                  "the ability of EDS to address simple measurements as well as more challenging measurements like major element interferences, light elements, trace elements, and low beam energy measurements has been demonstrated",
+                  "k = Cstd (Iunk/Istd) is the \ufb01rst approximation of the mass fraction of the associated element",
+                  "It is a good strategy to collect N spectra (with N \u22485 to 10) for a live-time t/N from the standard rather than one for a live-time t."
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+                  "useful accuracy can extend well into the trace (0.001 < C < 0.01) constituent range even when severe peak interference occurs",
+                  "EDS has developed into a fully quantitative analytical tool that can match wavelength dispersive spectrometry for accuracy in the determination of major (mass concentration C > 0.1) and minor (0.01 \u2264C \u22640.1) constituents",
+                  "2018 marked the 50th anniversary of the introduction of energy dispersive X-ray spectrometry (EDS) with semiconductor detectors to electron-excited X-ray microanalysis"
+                ],
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+                "context": "This paper demonstrates that SDD-EDS enables trace element detection with limits of detection below 0.001 mass fraction (1000 ppm) within practical measurement times of 500 seconds. The authors describe the k-ratio protocol for quantitative analysis, where characteristic X-ray intensities from unknowns are compared to standards under identical conditions (same beam energy, dose, and detector efficiency). This approach allows the detector efficiency to cancel out mathematically, improving accuracy and precision. The k-ratio/ZAF matrix correction method represents a standards-based quantification approach where measurements don't require standards that closely match the unknown composition, providing flexibility for analyzing complicated multi-element materials. The SDD advances provide accuracy and precision comparable to wavelength-dispersive spectrometry on electron probe microanalyzers, with high-count spectra enabling accurate peak fitting even for severe peak overlaps.",
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+                  "Measurement of trace constituents with limits of detection below 0.001 mass fraction (1000 ppm) is possible within a practical measurement time of 500 s.",
+                  "The recent advances in EDS performance with the silicon drift detector (SDD) enable accuracy and precision equivalent to that of the high spectral resolution wavelength-dispersive spectrometer employed on the electron probe microanalyzer platform.",
+                  "k \u00bc Iunknown=Istandard",
+                  "By measuring the same peak under identical conditions, the same efficiency value effectively appears in both the numerator and denominator of Eq. (1) as a multiplier of the intensity, and thus the efficiency quantitatively cancels in the k-ratio.",
+                  "the standards required do not have to closely match the composition of the unknown, which is an enormous advantage when dealing with complicated multi-element unknowns."
+                ],
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+                "id": "pqac-00000034",
+                "context": "The excerpt discusses EDS (Energy Dispersive Spectrometry) detection limits and analytical precision for trace element analysis. Trace elements are defined as those with mass concentration C < 0.01. Detection limits ranging from 0.0002\u20130.0005 mass fraction (200\u2013500 ppm) can be achieved with counting times below 500 seconds, depending on the element and matrix composition. The detection limit formula CDL = [3NB1/2/(NS \u2212NB)]CS is presented, where NB is background counts, NS is peak counts, and CS is the known concentration. The excerpt includes precision data showing relative standard deviations (\u03c3 relative) ranging from 0.008\u20131.8% and combined uncertainties from 0.0044\u20131.7% for various elements. The analysis addresses challenges including peak overlap from major/minor constituents and peak interference situations that can be resolved through peak fitting techniques.",
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+                "context": "This study explores EDS (Energy Dispersive Spectroscopy) capabilities for rare earth element analysis using silicon drift detectors (SDD). For major/minor elements above 1% mass fraction, SDD achieved relative deviations better than 10%. Between 0.1-1% mass fraction, detection was inconsistent with large uncertainties. Below 0.1% mass fraction, detection was unreliable. The analysis required extended acquisition times (10 minutes live-time per measurement). The authors note that WDS (Wavelength Dispersive Spectroscopy) maintains lower detection limits due to superior peak-to-background ratios. While most EDS measurements remain qualitative or standardless with large error bars, careful analysts using standards-based quantification can achieve accurate results comparable to WDS for major/minor elements. The study suggests combining SDD speed and accuracy for major elements with WDS sensitivity for trace elements.",
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+                  "At the major / minor levels (C > 1% mass fraction), the SDD was capable of measuring with RDEVs that were typically better than 10 %. Below these levels, there is no clear story.",
+                  "Below 0.1 % mass fraction, detection was hit-or-miss.",
+                  "Because the peak-to-background ratio is higher for WDS than SDD, WDS will always have the lower limits-of-detection.",
+                  "Accurate electron probe measurements have always been a challenge but careful analysts have been doing them for decades with WDS technology and, with similar care, accurate measurements can be performed with an SDD.",
+                  "The vast majority of EDS measurements remain qualitative or quantitative with large error bars (\"standardless analysis\").",
+                  "The acquisition times were fairly long (10 points at 10 minutes live-time per point)"
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+                    "authors": [
+                      "Dale E. Newbury",
+                      "Nicholas W.M. Ritchie"
+                    ],
+                    "publication_date": "2019-10-01T00:00:00Z",
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+                    "formatted_citation": "Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal."
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+                "snippets": [
+                  "the remote standards method is tied to measurements of real materials, it is inherently more accurate and is a good compromise between first-principles standardless analysis and locally collected standards-based analysis",
+                  "Standardless analysis requires only",
+                  "guessing how vendors implement their \"standard-less quantification\" because they have typically not provided the customer with adequate documentation on what is actually being done to derive numerical concentrations"
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000039",
+                "context": "This excerpt from Newbury & Ritchie (2019) discusses standardless quantification methods in EDS microanalysis. Standardless analysis requires only beam energy and spectrometer takeoff angle, but lacks electron dose information, necessitating normalization to 100 wt% for meaningful results. Early testing showed standardless analysis produced relative deviations (RDEV) spanning \u00b125% range for 95% of results. The authors note that approximately 95% or more of EDS quantitative compositional results are derived from standardless analysis. The excerpt includes analysis data from NIST reference materials (K523 glass and SRM 610 trace elements glass) measured at 20 keV, demonstrating detection capabilities for trace elements and providing measured concentrations with uncertainties. However, the excerpt does not explicitly address detection limits at 0.001 mass fraction, measurement time, dose-counting statistics relationships, or detailed comparisons of standardless versus standards-based approaches.",
+                "question": "Newbury Ritchie EDS detection limits trace analysis 0.001 mass fraction measurement time dose counting statistics precision accuracy standardless vs standards-based quantification",
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+                    "bibtex": "@article{newbury2019electronexcitedxraymicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W.M.\",\n    title = \"Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"1075-1105\",\n    month = \"Oct\",\n    doi = \"10.1017/s143192761901482x\",\n    url = \"https://doi.org/10.1017/s143192761901482x\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"05\",\n    issn = \"1431-9276\"\n}\n",
+                    "authors": [
+                      "Dale E. Newbury",
+                      "Nicholas W.M. Ritchie"
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+                    "publication_date": "2019-10-01T00:00:00Z",
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+                    "title": "Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping",
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+                  },
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+                  "Standardless analysis requires only that the analyst provides the beam energy and the X-ray spectrometer takeoff angle relative to the specimen surface. Knowledge of the electron dose is not needed.",
+                  "standardless analysis results, including oxygen if calculated by the method of assumed stoichiometry, must be normalized to unity mass fraction (100 wt%) to be placed on a sensible basis.",
+                  "Early testing of standardless analysis with known materials revealed a distribution of RDEVs such that 95% of the analytical results spanned an RDEV range of \u00b125% relative",
+                  "The vast majority of EDS quantitative compositional results are likely being derived from standardless analysis, perhaps 95% or more!"
+                ],
+                "used_images": false
+              },
+              {
+                "id": "pqac-00000037",
+                "context": "This paper discusses EDS (energy-dispersive X-ray spectrometry) capabilities for trace element analysis, specifically examining rare-earth element detection. The authors explain that EDS detection limits are primarily constrained by the background (continuum) level relative to signal (characteristic) level. They demonstrate that trace measurements in the 0.1-1.0% mass fraction range can be performed accurately with modern silicon drift detectors (SDDs). However, SDDs cannot match WDS (wavelength-dispersive X-ray spectrometry) at the lowest trace levels due to inferior peak-to-background ratios. The paper emphasizes recent improvements in EDS technology\u2014particularly SDDs\u2014that have dramatically enhanced throughput and resolution (approaching 120 eV at Mn-K\u03b1). The authors note that peak-to-background ratios in EDS depend on channel ranges used for continuum and peak estimation, with optimal results achieved by integrating peaks over the central full-width half-max. Recent advances allow EDS to match or exceed WDS accuracy and precision in many applications.",
+                "question": "Newbury Ritchie EDS detection limits trace analysis 0.001 mass fraction measurement time dose counting statistics precision accuracy standardless vs standards-based quantification",
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+                    "citation": "N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013.",
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+                    "bibtex": "@article{ritchie2018exploringthelimits,\n    author = \"Ritchie, N W M and Newbury, D E and Lowers, H and Mengason, M\",\n    title = \"Exploring the limits of EDS microanalysis: rare earth element analyses\",\n    year = \"2018\",\n    journal = \"IOP Conference Series: Materials Science and Engineering\",\n    volume = \"304\",\n    pages = \"012013\",\n    month = \"Aug\",\n    doi = \"10.1088/1757-899x/304/1/012013\",\n    url = \"https://doi.org/10.1088/1757-899x/304/1/012013\",\n    publisher = \"IOP Publishing\",\n    issn = \"1757-8981\"\n}\n",
+                    "authors": [
+                      "N W M Ritchie",
+                      "D E Newbury",
+                      "H Lowers",
+                      "M Mengason"
+                    ],
+                    "publication_date": "2018-08-01T00:00:00Z",
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+                    "title": "Exploring the limits of EDS microanalysis: rare earth element analyses",
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+                    "formatted_citation": "N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations."
+                  },
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+                  "Ultimately, limits of detection are constrained by the magnitude of the background (continuum) level relative to the signal (characteristic) level.",
+                  "Even higher level trace measurements (1.0 % mass fraction > Cz > 0.1 % mass fraction, where Cz is the mass fraction of element z) can be performed accurately with an SDD.",
+                  "Regardless, the SDD is unlikely to ever challenge the WDS at the lowest measurable trace levels [13] due to inferior peak-to-background ratios.",
+                  "The peak-to-background ratio on an EDS is determined by the ranges of channels used to estimate the continuum and peak intensity.",
+                  "the last decade has seen the accuracy and precision surge forward"
+                ],
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+              {
+                "id": "pqac-00000042",
+                "context": "# Summary\n\nThis excerpt demonstrates SDD-EDS quantitative analysis at E\u2080 = 10 keV using DTSA-II software on samples like SrWO\u2084 and WSi\u2082, achieving relative errors of 0.2\u20133.5% through iterative peak fitting with reference standards and stoichiometric calculations (Tables 9\u201310). The text emphasizes analytical protocol: qualitative analysis identifies major constituents first, then residual spectra reveal previously hidden minor/trace elements, enabling second-round quantification. For trace elements with severe interference\u2014exemplified by Ce at 0.0041 mass fraction under Ba interference (Ba/Ce = 53/1, peaks separated 12\u2013106 eV)\u2014the method achieves ~20% relative errors through careful peak-fitting. The excerpt notes that low-Z element analysis (C, N, O, F; energies <1 keV) presents \"great challenge\" due to chemical-shift effects and spectral-resolution limitations of EDS versus WDS, with interfering L-, M-, N-family X-rays complicating measurements. However, the excerpt provides **no derivation** of acquisition-parameter recommendations (overvoltage, dead time, process time, count targets, or statistical criteria), addressing only practical quantification outcomes.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt traces the development of quantitative EDS microanalysis from its inception in the 1960s using lithium-compensated silicon [Si(Li)-EDS] detectors. Early EDS implementations followed the established WDS k-ratio/matrix correction protocol, measuring both unknowns and standards under identical controlled conditions (polished surface, beam energy, beam current \u00d7 live time, take-off angle, detector solid angle). \n\nEarly Si(Li)-EDS achieved accuracy comparable to WDS for major constituents\u2014Table 1 demonstrates relative errors of \u22121.6 to +1.0% on NIST copper-gold standards, \"falling well within the WDS analysis error distribution\" of \u00b15% relative (2.5% standard deviation). The excerpt notes Si(Li)-EDS advantages: simultaneous multi-element detection, larger solid angle (>10\u00d7 WDS), and stable archived spectra enabling standard recall.\n\nHowever, the excerpt identifies a critical divergence: modern SEM/EDS practice has shifted toward \"standardless analysis which now dominates EDS quantitative analysis,\" accompanied by specimen-geometry effects and occasional elemental misidentification, creating an unintended \"semi-quantitative\" reputation despite demonstrated quantitative capability.\n\nThe excerpt does not address the specific physics derivations (overvoltage optimization, dead-time models, Currie statistics) or low-voltage/trace-element considerations requested in the question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                      "Dale E. Newbury",
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+                    "title": "Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive X-ray spectrometry (SEM/SDD-EDS)",
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+                "context": "# Summary\n\nThe excerpt provides empirical validation data for SEM-EDS analysis but does not derive the recommended acquisition parameters. It presents Tables 15-18 showing analysis results for standard materials (SRM 168 inclusion, binary fluorides, oxides, and nitrides) measured at E\u2080 = 10 keV and 5 keV, with reported relative standard deviations (RDEV) typically in the range of 0.3\u20134% and relative \u03c3 values of 0.05\u20132%.\n\nThe excerpt briefly discusses \"standardless\" analysis methods that avoid measuring standard k-ratios by calculating X-ray generation intensities, and addresses peak-fitting challenges when major/minor constituent interferences affect trace elements\u2014citing examples where Th M and U M peaks (separated by 19 eV) can be recovered with RDEVs of 2% at 100:1 intensity ratios but degrade to 26% at 1000:1 ratios.\n\n**However, the excerpt does not explain the underlying physics, derivations, or primary literature that originally fixed the specific recommended values (U\u2080 \u2248 2\u20133, 20\u201340% dead time, ~10\u2074 counts, 3-sigma criterion, or shaping-time trade-offs).**",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt provides practical guidance on low-voltage SEM-EDS analysis and trace-element quantification. \n\n**Low-voltage constraints:** At E\u2080 = 5 kV (the minimum practical beam energy), the analyst must exceed the critical excitation energy Ec \"ideally by a factor of at least 1.25.\" Below 5 kV, increasing numbers of elements become inaccessible due to lack of measurable characteristic X-ray peaks (Newbury & Ritchie, 2016a). The excerpt notes that \"the stratified nature of most materials\" and \"native oxides and other surface layers\" become significant contributors to the spectrum at low beam energy, and carbon contamination affects X-ray absorption near the C K-edge (0.284 keV).\n\n**Trace-element detection:** For trace elements (C < 0.01 mass concentration), the detection limit is calculated as CDL = [3NB^(1/2)/(NS \u2212 NB)]CS, where NB is background counts, NS is peak counts, and CS is known concentration. Newbury & Ritchie (2016b) report \"limits of detection in the range 0.0002\u20130.0005 mass concentration (200\u2013500 parts per million)...with counting times below 500 s.\" The excerpt demonstrates analysis of NIST SRM 610 (trace elements at ~500 ppm) using a 1.7 billion-count spectrum integral.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "## Summary\n\nThe excerpt does not contain the primary literature derivations requested in the question. Instead, it presents:\n\n**Empirical data tables** showing EDS analyses of binary nitrides (Table 19), carbides (Table 19), and borides (Table 20) at E\u2080 = 5\u201310 keV, with relative standard deviations (\u03c3_relative) typically 0.07\u20133.3% across multiple replicates, and relative deviation (RDEV) values mostly within \u00b16%.\n\n**Methodological discussion** mentioning that \"first-principles standardless analysis\" accuracy is \"limited by lack of accurate values for critical physical parameters such as ionization cross section,\" and that \"remote standards method\" offers a compromise between first-principles and standards-based approaches (Goldstein et al., 2018).\n\n**No derivations of recommended parameters**: The excerpt lacks theoretical justification for overvoltage ratios, dead-time percentages, shaping times, count statistics (10\u2074 counts, 3-sigma criterion), or low-voltage/trace-element modifications. It does not trace Bethe formulations, Green & Cosslett measurements, Kanaya-Okayama scaling, Castaing experiments, paralyzable dead-time models, or Currie's 1968 hypothesis-testing framework.\n\nThe excerpt demonstrates practical SEM-EDS accuracy but does not address the underlying physics or statistical foundations of canonical parameter recommendations.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                    "citation": "Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x.",
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+                    "bibtex": "@article{newbury2019electronexcitedxraymicroanalysis,\n    author = \"Newbury, Dale E. and Ritchie, Nicholas W.M.\",\n    title = \"Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping\",\n    year = \"2019\",\n    journal = \"Microscopy and Microanalysis\",\n    volume = \"25\",\n    pages = \"1075-1105\",\n    month = \"Oct\",\n    doi = \"10.1017/s143192761901482x\",\n    url = \"https://doi.org/10.1017/s143192761901482x\",\n    publisher = \"Oxford University Press (OUP)\",\n    issue = \"05\",\n    issn = \"1431-9276\"\n}\n",
+                    "authors": [
+                      "Dale E. Newbury",
+                      "Nicholas W.M. Ritchie"
+                    ],
+                    "publication_date": "2019-10-01T00:00:00Z",
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+                    "title": "Electron-Excited X-ray Microanalysis by Energy Dispersive Spectrometry at 50: Analytical Accuracy, Precision, Trace Sensitivity, and Quantitative Compositional Mapping",
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+                "context": "# Summary\n\nThe excerpt addresses dead-time correction in X-ray microanalysis, specifically for wavelength-dispersive spectroscopy (WDS). It describes the traditional linear dead-time expression: Icps = icps/(1 \u2212 icps\u00b7\u03c4), which assumes \"mathematically rectilinear\" pulse shapes and constant dead time and is limited to input count rates up to ~50 kcps. Above ~50 kcps, overlapping pulses and nonideal pulse shapes violate these assumptions. The excerpt presents nonlinear corrections\u2014a two-term expression (Willis et al. 1993) valid to ~100 kcps and a logarithmic formulation [Icps = icps/(1 + ln(1\u2212\u03c4\u00b7icps))] applicable to \"approximately 300 to 400 kcps\" depending on hardware dead-time constants. It introduces a \"constant k-ratio method\" for validating dead-time constants. However, the excerpt does not address the underlying derivations of the recommended 20-40% dead-time operating point, ionization cross-section physics, or Poisson statistics linking count numbers to precision\u2014the core topics requested.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                    "citation": "John J Donovan, Aur\u00e9lien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050.",
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+                    "authors": [
+                      "John J Donovan",
+                      "Aur\u00e9lien Moy",
+                      "Anette von der Handt",
+                      "Zack Gainsforth",
+                      "James L Maner",
+                      "William Nachlas",
+                      "John Fournelle"
+                    ],
+                    "publication_date": "2023-05-16T00:00:00Z",
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+                    "publisher": "Oxford University Press (OUP)",
+                    "url": "https://doi.org/10.1093/micmic/ozad050",
+                    "title": "A New Method for Dead Time Calibration and a New Expression for Correction of WDS Intensities for Microanalysis.",
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+                "context": "# Summary\n\nThe excerpt discusses dead-time in EDS systems\u2014the period when the detector cannot measure new X-ray photons while processing prior ones. Key points:\n\n**Dead-time fundamentals:** X-ray generation is random; the detector measures only one photon at a time. Output count rate (OCR) is always less than input count rate (ICR) due to photon loss. Dead-time percentage is calculated as: \"Deadtime (%) = (ICR \u2212 OCR) / ICR \u00d7 100%\" [equation 16.5].\n\n**Practical constraints:** For a single SDD chip, maximum output is ~130 kHz. A quad SDD with medium peaking time (470 ns) achieves maximum ~550 kHz at ICR ~1.5 MHz (Fig. 16.9). As dead-time increases with beam current, coincidence events become prominent, creating false peaks (Fig. 16.10, showing spectra at 7% and 20% dead-time). Dead-time correction circuits can maintain accuracy to \"80% or higher\" dead-time through live-time adjustment, though corrections should be periodically validated by systematically varying beam current.\n\nThe excerpt does not provide the derivations of the 20\u201340% dead-time recommendation or underlying physics models requested in the question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                    "citation": "Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16.",
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+                    "authors": [
+                      "Joseph I. Goldstein",
+                      "Dale E. Newbury",
+                      "Joseph R. Michael",
+                      "Nicholas W. M. Ritchie",
+                      "John Henry J. Scott",
+                      "David C. Joy"
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+                    "formatted_citation": "Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations."
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+                "context": "# Summary\n\nThe excerpt discusses dead-time correction mathematics in X-ray spectroscopy detectors, specifically comparing four dead-time models: traditional, Willis two-term, six-term expansion, and logarithmic expressions. \n\nKey findings: The simple exponential expression has fundamental mathematical limitations\u2014\"the product of the dead time and count rate cannot exceed 1/e,\" restricting application to \"245 kcps or less at 1.5 \u03bcs\" and \"123 kcps or less at dead times of 3 \u03bcs.\" The excerpt presents empirical comparisons (Figures 1\u20133, Table 2) showing that at \"\u223c1.5 \u03bcs dead times\" (typical JEOL instruments), the traditional expression performs similarly to Willis two-term up to ~200 kcps, but \"above that count rate\" the Willis and higher-order expressions diverge. The text notes instrument-dependent variation: \"Cameca instruments\" with \"\u223c3 \u03bcs dead time constants\" show even larger corrections. Additionally, gas-detector latencies cause \"paralyzing behavior\" where \"observed count rate drops to zero\" at extreme rates (500\u20131,000 kcps).\n\nThis provides empirical dead-time throughput data but does not explain the *derivation* of the 20\u201340% dead-time guidance or the original physics basis underlying parameter recommendations.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                    "citation": "John J Donovan, Aur\u00e9lien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050.",
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+                    "authors": [
+                      "John J Donovan",
+                      "Aur\u00e9lien Moy",
+                      "Anette von der Handt",
+                      "Zack Gainsforth",
+                      "James L Maner",
+                      "William Nachlas",
+                      "John Fournelle"
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+                    "publisher": "Oxford University Press (OUP)",
+                    "url": "https://doi.org/10.1093/micmic/ozad050",
+                    "title": "A New Method for Dead Time Calibration and a New Expression for Correction of WDS Intensities for Microanalysis.",
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+                "context": "# Summary\n\nThis excerpt addresses dead-time correction modeling in EDS, specifically how mathematical models predict true count rates from observed rates at high acquisition rates. The text describes an extended six-term Maclaurin expansion (Equation 3) used when count rates exceed 100\u2013200 kcps, with higher-order terms accounting for nonlinear pulse-processing effects. At extremely high rates (>300\u2013400 kcps), \"nonlinear effects come to dominate the pulse processing electronics, and the dead time correction becomes extremely sensitive to the exact value of the dead time constant utilized.\"\n\nTable 2 demonstrates how different dead-time correction expressions (traditional linear, Willis et al. 1993, six-term expansion, and logarithmic) converge at moderate rates but diverge significantly above ~100 kcps. The table shows observed/predicted count-rate ratios declining from 0.985 at 10 kcps to 0.643 at 220 kcps with a 1.5 \u03bcs dead-time constant, illustrating the throughput loss and sensitivity to correction model choice at high rates\u2014informing why the 20\u201340% dead-time operating window is practically maintained.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                    "authors": [
+                      "John J Donovan",
+                      "Aur\u00e9lien Moy",
+                      "Anette von der Handt",
+                      "Zack Gainsforth",
+                      "James L Maner",
+                      "William Nachlas",
+                      "John Fournelle"
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+                "context": "# Summary\n\nThis excerpt is a historical account of electron probe microanalysis (EPMA) development, not a technical derivation of SEM-EDS acquisition parameters. It describes the author's experience running Italy's first automated microprobe (1975) and meeting Raymond Castaing in 1983. \n\nThe passage mentions Castaing's foundational work demonstrating \"proportionality between the intensity of the emitted X-ray signal and the concentration of the emitting element\" and his formulation of matrix-effect approximations forming \"Castaing's Principle\u2014the fundamental law of EPMA.\" It references modern developments including the \u03a6-\u03c1-z (PAP) correction method, Monte Carlo simulations, and notes that trace-element analysis \"reaching well below the 0.1 wt% level and into the parts per million (ppm) range\" is now possible with present instruments.\n\nHowever, **the excerpt contains no information about the physics-based derivations, statistical foundations, or validation experiments** underlying specific parameter recommendations (overvoltage ratios, dead-time percentages, pulse-shaping times, count requirements, or Currie criteria).",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                    "authors": [
+                      "Romano Rinaldi",
+                      "Xavier Llovet"
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+                    "publication_date": "2015-05-12T00:00:00Z",
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+                    "formatted_citation": "Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal."
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+                "context": "# Summary\n\nThe excerpt discusses instrumental advances in EDS and EPMA that affect trace-element analysis and low-voltage operation, but does not systematically derive the recommended acquisition parameters from first principles.\n\n**Key points relevant to parameter derivation:**\n\n- Silicon drift detectors (SDDs) offer \"count rate performance...up to two orders of magnitude greater than that of a Si(Li) detector\" (Newbury & Ritchie, 2013) with energy resolution \"close to the theoretical value of 120 eV.\"\n\n- Low-voltage operation requires revisiting \"mass attenuation coefficients\" and accounting for \"secondary fluorescence (SF) at grain boundaries\" (Llovet et al., 2012; Wade & Wood, 2012).\n\n- Trace-element detection demands \"long counting times...divided into many short counting times and alternating peak and background measurements to minimize instrumental drift\" (Merlet & Bodinier, 1990), monitored via \u03c7\u00b2 and statistical filtering.\n\n- X-ray interaction volume extends \"one-to-two orders of magnitude larger\" than primary-electron range, affecting trace quantification near phase boundaries.\n\nThe excerpt emphasizes practical constraints and detector capabilities but does not explain the underlying physics models or statistical derivations that originally fixed the standard parameter values.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThe excerpt discusses the historical development and modern advances in electron probe microanalysis (EPMA), particularly regarding detection limits and instrumental improvements, but **does not directly address the derivation of SEM-EDS acquisition parameters** specified in the question.\n\n**Relevant content:**\n\nThe excerpt mentions Ziebold's (1967) classical expression for detection limit: \"CDL > 3.29\u03c3 = (ntP \u00d7 P/B)^1/2,\" linking detection capability to counting time, peak count rate (P), and peak-to-background ratio. It notes that \"more advanced statistical expressions have introduced confidence levels and standard deviations.\"\n\nFor low-voltage operation, the excerpt references that \"low voltage operation (5\u20137 kV)\" combined with field-emission guns produces \"very shallow penetration depth\" and \"greatly reduced interaction volume,\" but acknowledges that \"low voltage operation may require special care and a whole new approach for quantitative analysis\" (citing Merlet & Llovet 2012; Pinard & Richter 2014).\n\n**Gap:** The excerpt does not provide the underlying physics derivations, cross-section models (Bethe, Green & Cosslett), dead-time throughput models, pulse-shaping trade-offs, or Poisson statistics linking counts to precision that the question asks for.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt presents empirical SEM-EDS acquisition data rather than the theoretical derivation sought. The paper reports repeat analyses on glass standards (NMNH VG-2 basaltic and NMNH 72854 rhyolitic) across varying total count accumulations (1M to 20M counts). \n\nKey findings: analyses collecting \"10k and 20k counts\" yielded relative standard deviation (RSD%) >5% for major elements (>10 wt oxide%) and >10% for minor elements; above 100k counts, elements >1.5 wt oxide% achieved RSD% <5%; at >1M counts, major oxides showed RSD% <2%. The authors recommend \"a minimum of 1M counts\" for \"fully quantitative EDX analysis.\" The text notes that beam-induced elemental loss (Na, K, Cl) occurred only \"at high counts ($5M),\" and lower beam currents reduce this loss over extended acquisition periods.\n\n**This excerpt does not address the underlying physics models, cross-section measurements, counting-statistics derivations, or primary literature sources that originally justified the canonical parameter recommendations.**",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThe excerpt provides foundational context for EDX analysis but does not address the core question about how recommended acquisition parameters were originally derived from first-principles physics.\n\nThe document establishes that:\n- EDX peak intensity increases with element concentration, but two problems complicate quantification: (1) detector efficiency varies with X-ray energy, and (2) characteristic X-ray intensities are non-linear with concentration\n- An electron overvoltage of \"at least 1.8 is specified for quantitative analysis in ISO 22309:2011,\" with the rationale that \"X-ray peaks close to the primary electron energy may be hidden or very weak\"\n- Background subtraction and ZAF matrix corrections (accounting for electron backscattering, X-ray absorption, and secondary fluorescence) are necessary\n- Detector window material affects efficiency, especially below 1 keV\n\nHowever, the excerpt does **not** derive the 2\u20133 overvoltage rule from ionization cross-section physics (Bethe, Green & Cosslett), explain the 20\u201340% dead-time optimization, link pulse-shaping time to energy resolution trade-offs, connect the 10,000-count guidance to Poisson statistics, or cite Currie's 1968 derivation of the 3-sigma detection criterion. It provides no historical literature tracing these values to primary experimental validation.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                "context": "# Summary\n\nThis excerpt describes a practical SEM-EDX methodology study on silicate glasses but **does not address the fundamental question posed**. The text discusses:\n\n- **Sample preparation**: polishing to 1 micron, carbon coating (12 nm), and selection of reference glasses (NMNH, MPI-DING standards) spanning compositional ranges (SiO\u2082: 45.5\u201376.7 wt%).\n\n- **Instrument settings used**: 20 kV accelerating voltage, 4.5 nm beam, 300 pA current, \"process time of five\" in AZtec software (described as a dimensionless index 1\u20136 where lower values prioritize speed and higher values prioritize energy resolution).\n\n- **Data collection protocol**: standardization at 2M (2 million) counts per standard with ~15% dead time, yielding ~25 seconds per analysis at 100k counts/second acquisition rate.\n\n- **Analysis modes**: Raster (high magnification) versus Point & ID (reference image at lower magnification).\n\nThe excerpt provides **no derivation** of why the recommended parameters (U\u2080 ~ 2\u20133, dead time 20\u201340%, 10\u2074 net counts, 3-sigma criterion) were originally chosen, nor does it cite the underlying physics models, cross-section formulations, counting-statistics derivations, or validation experiments needed to answer the question.",
+                "question": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
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+                  "An improved absorption correction (Love et al., 1983) derived by MC fitting of \u03a6-\u03c1-z curves covering a wide range of experimental conditions.",
+                  "Castaing had the great merit to demonstrate the proportionality between the intensity of the emitted X-ray signal and the concentration of the emitting element, once account is taken (by empirical factors) of the nature of the sample (matrix effect)."
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+            "references": "1. (goldstein2018quantitativeanalysisthe pages 4-6): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n2. (goldstein2018quantitativeanalysisthe pages 9-11): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n3. (tong2026measurementuncertaintiesof pages 8-11): V. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.\n\n4. (newbury2019electronexcitedxraymicroanalysis pages 13-15): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n5. (goldstein2018energydispersivexray pages 9-10): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n6. (goldstein2018quantitativeanalysisthe pages 6-8): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n7. (donovan2023anewmethod pages 2-3): John J Donovan, Aur\u00e9lien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050. This article has 18 citations.\n\n8. (donovan2023anewmethod pages 3-4): John J Donovan, Aur\u00e9lien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050. This article has 18 citations.\n\n9. (goldstein2018energydispersivexray pages 14-15): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n10. (lechner2004novelhighresolutionsilicon pages 2-4): P. Lechner, A. Pahlke, and H. Soltau. Novel high-resolution silicon drift detectors. X-Ray Spectrometry, 33:256-261, Jul 2004. URL: https://doi.org/10.1002/xrs.717, doi:10.1002/xrs.717. This article has 111 citations and is from a peer-reviewed journal.\n\n11. (schlosser2010expandingthedetection pages 2-4): D.M. Schlosser, P. Lechner, G. Lutz, A. Niculae, H. Soltau, L. Str\u00fcder, R. Eckhardt, K. Hermenau, G. Schaller, F. Schopper, O. Jaritschin, A. Liebel, A. Simsek, C. Fiorini, and A. Longoni. Expanding the detection efficiency of silicon drift detectors. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 624:270-276, Dec 2010. URL: https://doi.org/10.1016/j.nima.2010.04.038, doi:10.1016/j.nima.2010.04.038. This article has 88 citations.\n\n12. (lechner2004novelhighresolutionsilicon pages 4-5): P. Lechner, A. Pahlke, and H. Soltau. Novel high-resolution silicon drift detectors. X-Ray Spectrometry, 33:256-261, Jul 2004. URL: https://doi.org/10.1002/xrs.717, doi:10.1002/xrs.717. This article has 111 citations and is from a peer-reviewed journal.\n\n13. (goldstein2018energydispersivexray pages 25-26): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n14. (newbury2011isscanningelectron pages 2-3): Dale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\n15. (goldstein2018quantitativeanalysisthe pages 8-9): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n16. (guyett2024optimizingsemedxfor pages 4-6): Paul C. Guyett, David Chew, Vitor Azevedo, Lucy C. Blennerhassett, Carolina Rosca, and Emma Tomlinson. Optimizing sem-edx for fast, high-quality and non-destructive elemental analysis of glass. Journal of Analytical Atomic Spectrometry, 39:2565-2579, Jan 2024. URL: https://doi.org/10.1039/d4ja00212a, doi:10.1039/d4ja00212a. This article has 50 citations and is from a peer-reviewed journal.\n\n17. (currie1999detectionandquantification pages 2-4): Lloyd A. Currie. Detection and quantification limits: origins and historical overview1adapted from the proceedings of the 1996 joint statistical meetings (american statistical association, 1997). original title: \u201cfoundations and future of detection and quantification limits\u201d. contribution of the national institute of standards and technology; not subject to copyright.1. May 1999. URL: https://doi.org/10.1016/s0003-2670(99)00105-1, doi:10.1016/s0003-2670(99)00105-1. This article has 701 citations and is from a domain leading peer-reviewed journal.\n\n18. (currie1999detectionandquantification pages 1-2): Lloyd A. Currie. Detection and quantification limits: origins and historical overview1adapted from the proceedings of the 1996 joint statistical meetings (american statistical association, 1997). original title: \u201cfoundations and future of detection and quantification limits\u201d. contribution of the national institute of standards and technology; not subject to copyright.1. May 1999. URL: https://doi.org/10.1016/s0003-2670(99)00105-1, doi:10.1016/s0003-2670(99)00105-1. This article has 701 citations and is from a domain leading peer-reviewed journal.\n\n19. (currie1999detectionandquantification pages 4-6): Lloyd A. Currie. Detection and quantification limits: origins and historical overview1adapted from the proceedings of the 1996 joint statistical meetings (american statistical association, 1997). original title: \u201cfoundations and future of detection and quantification limits\u201d. contribution of the national institute of standards and technology; not subject to copyright.1. May 1999. URL: https://doi.org/10.1016/s0003-2670(99)00105-1, doi:10.1016/s0003-2670(99)00105-1. This article has 701 citations and is from a domain leading peer-reviewed journal.\n\n20. (rinaldi2015electronprobemicroanalysis pages 4-5): Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.\n\n21. (rinaldi2015electronprobemicroanalysis pages 7-8): Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.\n\n22. (rinaldi2015electronprobemicroanalysis pages 2-4): Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.\n\n23. (newbury2019electronexcitedxraymicroanalysis pages 16-18): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n24. (wuhrer2016lowvoltageimaging pages 7-10): Richard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.\n\n25. (wuhrer2016lowvoltageimaging pages 10-12): Richard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.\n\n26. (donovan2023anewmethod pages 4-5): John J Donovan, Aur\u00e9lien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050. This article has 18 citations.\n\n27. (guyett2024optimizingsemedxfor pages 3-4): Paul C. Guyett, David Chew, Vitor Azevedo, Lucy C. Blennerhassett, Carolina Rosca, and Emma Tomlinson. Optimizing sem-edx for fast, high-quality and non-destructive elemental analysis of glass. Journal of Analytical Atomic Spectrometry, 39:2565-2579, Jan 2024. URL: https://doi.org/10.1039/d4ja00212a, doi:10.1039/d4ja00212a. This article has 50 citations and is from a peer-reviewed journal.\n\n28. (niculae2006optimizedreadoutmethods pages 2-3): A. Niculae, P. Lechner, H. Soltau, G. Lutz, L. Str\u00fcder, C. Fiorini, and A. Longoni. Optimized readout methods of silicon drift detectors for high-resolution x-ray spectroscopy. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 568:336-342, Nov 2006. URL: https://doi.org/10.1016/j.nima.2006.06.025, doi:10.1016/j.nima.2006.06.025. This article has 76 citations.\n\n29. (niculae2006optimizedreadoutmethods pages 3-6): A. Niculae, P. Lechner, H. Soltau, G. Lutz, L. Str\u00fcder, C. Fiorini, and A. Longoni. Optimized readout methods of silicon drift detectors for high-resolution x-ray spectroscopy. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 568:336-342, Nov 2006. URL: https://doi.org/10.1016/j.nima.2006.06.025, doi:10.1016/j.nima.2006.06.025. This article has 76 citations.\n\n30. (newbury2015performingelementalmicroanalysis pages 2-4): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 609 citations and is from a peer-reviewed journal.\n\n31. (ritchie2018exploringthelimits pages 9-11): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\n32. (ritchie2018exploringthelimits pages 4-5): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\n33. (gollaschindler2026edswithlowvoltage pages 3-6): Ute Golla-Schindler and Gerhard Schneider. Eds with low-voltage sem: possibilities and limitations of lithium detection and quantification. EPJ Web of Conferences, 349:01004, Jan 2026. URL: https://doi.org/10.1051/epjconf/202634901004, doi:10.1051/epjconf/202634901004. This article has 0 citations and is from a peer-reviewed journal.\n\n34. (newbury2019electronexcitedxraymicroanalysis pages 18-20): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.",
+            "formatted_answer": "Question: How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).\n\n## Derivation of Recommended Acquisition Parameters in SEM-EDS: From Physics Models to Standard Practice\n\n### 1. Overvoltage Ratio (U\u2080 \u2248 2\u20133)\n\nThe recommendation to set the accelerating voltage E\u2080 at roughly two to three times the critical excitation energy Ec of the highest-energy line of interest (i.e., overvoltage U\u2080 = E\u2080/Ec \u2248 2\u20133) derives from the interplay of three physics models.\n\n**Ionization cross-section.** The Bethe (1930) formulation of the inner-shell ionization cross-section Q predicts that Q rises steeply from the threshold (U = 1), passes through a broad maximum at overvoltages of a few (typically U \u2248 2\u20134 depending on the shell and the specific formulation), and then decreases slowly as ln(U)/U at high overvoltages. Green and Cosslett (1961, 1968) validated this behavior experimentally by measuring K-, L-, and M-shell X-ray production efficiencies from thick pure-element targets bombarded by electrons, confirming that characteristic X-ray yield per unit beam current rises rapidly above threshold but saturates at modest overvoltages. Powell, Llovet, and Salvat (2016) later evaluated the accuracy of the Bethe equation against distorted-wave Born-approximation calculations and experiment, finding that the Bethe formula provides a useful approximation in the overvoltage range relevant to microanalysis. These studies collectively established that the marginal gain in ionization efficiency diminishes above U \u2248 2\u20133.\n\n**Electron range and interaction volume.** Countering the benefit of higher overvoltage, the electron range R in a solid scales approximately as E\u2080^1.67/\u03c1 in the Kanaya\u2013Okayama (1972) formulation. This means that raising E\u2080 expands the interaction volume roughly as R\u00b3, degrading lateral and depth spatial resolution. As Goldstein et al. (2018) note, the beam energy of 20 keV provides sufficient overvoltage (E\u2080/Ec > 1.5) for K-shell excitation up to Br and L-shell excitation up to Bi, with photon energies up to ~12 keV (goldstein2018quantitativeanalysisthe pages 4-6). Reducing E\u2080 from 20 to 10 keV substantially reduces the absorption correction factor uncertainty, as demonstrated for the FeS system where the S absorption factor dropped from 1.118 to 1.04, improving the relative error from 1.0% to 0.59% (goldstein2018quantitativeanalysisthe pages 9-11).\n\n**Depth distribution \u03d5(\u03c1z).** Castaing's original tracer experiments (1951 onward) measured the distribution of X-ray production with depth by sandwiching a thin marker layer of known composition at varying depths within a substrate, establishing the \u03d5(\u03c1z) function that forms the basis of ZAF and \u03d5(\u03c1z) matrix corrections. The \u03d5(\u03c1z) function shows that at high overvoltage, X-ray production extends deeper into the specimen, increasing absorption losses and reducing the fraction of generated X-rays that escape to the detector. This provides the physics basis for the practical rule: the overvoltage of ~2\u20133 sits near the broad maximum of the ratio of useful (escaped) characteristic signal to interaction volume. ISO 22309:2011 codified this as a minimum overvoltage of 1.8 for quantitative analysis (tong2026measurementuncertaintiesof pages 8-11). Goldstein et al. recommend E\u2080/Ec > 1.5 as a minimum and note that a beam energy of 5 keV is the lowest at which at least one characteristic X-ray peak can be excited for all elements except H and He (newbury2019electronexcitedxraymicroanalysis pages 13-15).\n\n### 2. Dead-Time and Throughput Optimization (20\u201340% Historical; \u226410% for Modern SDD)\n\nThe dead-time recommendation comes directly from detector counting-rate theory. X-rays arrive randomly, but the EDS can process only one photon at a time. The dead-time percentage is defined as DT(%) = (ICR \u2212 OCR)/ICR \u00d7 100%, where ICR is the input count rate and OCR is the output count rate (goldstein2018energydispersivexray pages 9-10).\n\n**Paralyzable model.** For a truly paralyzable (extending) dead-time system, the output count rate is OCR = ICR \u00d7 exp(\u2212ICR \u00d7 \u03c4), where \u03c4 is the dead-time constant per event. This function has a maximum at ICR = 1/\u03c4, corresponding to a dead-time fraction of 1 \u2212 1/e \u2248 63.2%. Beyond this point, further increases in ICR actually decrease OCR\u2014the system paralyzes. In practice, the useful operating range is well below this mathematical maximum because (a) the dead-time correction accuracy degrades at high rates, and (b) coincidence (sum/pile-up) peaks grow rapidly.\n\n**Non-paralyzable model.** For a non-paralyzable system, OCR = ICR/(1 + ICR \u00d7 \u03c4). The OCR rises monotonically but with diminishing returns, and dead-time correction is mathematically straightforward. Real EDS systems exhibit behavior between these two limits, with modern SDD digital pulse processors closer to non-paralyzable at moderate rates.\n\n**Practical optimum.** The classic Si(Li)-EDS strategy was to operate at \u226430% dead-time on a strongly excited pure element standard (goldstein2018quantitativeanalysisthe pages 6-8). With modern SDD-EDS, Goldstein et al. recommend a more conservative approach: keeping dead-time below 10% on the most highly excited standard because coincidence peaks become significant above this threshold, particularly when trace constituents must be measured in spectral regions affected by sum peaks (goldstein2018quantitativeanalysisthe pages 6-8). At 3% dead-time, coincidence artifacts are minimal; at 29% dead-time on the same glass K412, extensive coincidence peaks (Al+Al, Si+O, Si+Mg, Si+Si, Si+Ca, Mg+Ca) become visible (goldstein2018quantitativeanalysisthe pages 6-8). Donovan et al. (2023) showed that the traditional linear dead-time correction expression Icps = icps/(1 \u2212 icps\u00b7\u03c4) becomes inaccurate above ~50 kcps, requiring higher-order correction expressions (Willis 2-term, 6-term expansion, or logarithmic models) for accurate quantification at higher count rates (donovan2023anewmethod pages 2-3, donovan2023anewmethod pages 3-4).\n\nThus the 20\u201340% guidance for Si(Li) detectors was a practical compromise maximizing stored counts while keeping dead-time correction errors tolerable; the shift to \u226410% for SDD-based quantitative work reflects the greater throughput capacity of SDDs and the more stringent demands of modern peak fitting for trace analysis.\n\n### 3. Pulse Process Time (Shaping Time): Electronic Noise Trade-off\n\nThe choice of process time (also called shaping time, time constant, or throughput setting) in EDS is governed by a fundamental noise trade-off in the front-end electronics (goldstein2018energydispersivexray pages 14-15).\n\n**Noise components.** Lechner et al. (2004) express the equivalent noise charge (ENC) of an SDD as:\n\nENC\u00b2 = (2k\u1d66T/g\u2098)\u00b7C\u00b2\u00b7A\u2081/\u03c4 + afC\u00b2\u00b7A\u2082 + q\u00b7Il\u00b7A\u2083\u00b7\u03c4\n\nwhere the three terms represent serial white noise (proportional to 1/\u03c4, dominated by detector capacitance C and FET transconductance g\u2098), 1/f noise (independent of \u03c4), and parallel noise (proportional to \u03c4, dominated by leakage current Il) (lechner2004novelhighresolutionsilicon pages 2-4). At short shaping times, the serial (voltage) noise dominates and energy resolution degrades hyperbolically; at long shaping times, the parallel (current) noise and pile-up probability increase. The optimal shaping time sits at the broad minimum of ENC versus \u03c4, typically around 0.5\u20133 \u03bcs for SDDs depending on detector area, temperature, and capacitance (schlosser2010expandingthedetection pages 2-4, lechner2004novelhighresolutionsilicon pages 4-5).\n\n**Practical implementation.** Goldstein et al. describe the trade-off as three-way: throughput, resolution, and coincidence rate. Longer process times achieve better resolution but poor throughput; shorter process times maximize throughput but increase coincidence events. The optimal setting for quantitative analysis is a moderate process time that degrades resolution by only a few percent (e.g., from 122\u2013128 eV to 130\u2013135 eV FWHM at Mn K\u03b1) while substantially increasing throughput (goldstein2018energydispersivexray pages 14-15, goldstein2018energydispersivexray pages 25-26). Modern SDDs with 500 ns time constants can achieve resolution below 130 eV at Mn K\u03b1 while maintaining maximum OCR of ~130 kHz per detector chip (newbury2011isscanningelectron pages 2-3). The precision of quantitative analysis is more determined by the number of measured X-rays than by spectral resolution alone (goldstein2018energydispersivexray pages 14-15). Critically, for standards-based analysis, the same process time must be used for all standards and unknowns; adaptive process times that change resolution with throughput make spectrum fitting challenging and less accurate (goldstein2018energydispersivexray pages 14-15).\n\n### 4. Counting Statistics: Why ~10\u2074 Counts Gives ~1% RSD\n\nThe count-time recommendation derives directly from Poisson counting statistics. For a measured number of counts N drawn from a Poisson process, the standard deviation is \u03c3 = \u221aN, so the relative standard deviation (RSD) is \u03c3/N = 1/\u221aN. Thus:\n\n- N = 10\u2074 \u2192 RSD = 1%\n- N = 10\u2076 \u2192 RSD = 0.1%\n- N = 10\u00b2 \u2192 RSD = 10%\n\nThis is a mathematical identity, not an empirical convention. Newbury and Ritchie (2019) tabulate the separate contributions of counting error, absorption-factor error, and atomic-number-factor error to the combined uncertainty budget for standards-based SDD-EDS analysis. For example, in the analysis of FeS at 20 keV with 7 \u00d7 10\u2076 integrated spectrum counts, the counting error for the standard contributes \u00b10.0002 mass fraction and for the unknown \u00b10.0007, while the absorption factor error dominates at \u00b10.0017 (goldstein2018quantitativeanalysisthe pages 8-9). This demonstrates that at sufficiently high counts, counting statistics become a minor contributor and systematic errors (matrix corrections) dominate.\n\nGuyett et al. (2024) empirically validated the counting precision relationship for glass analyses: with only 10k\u201320k total counts (<1 s acquisition), RSD exceeded 5% even for major element oxides above 10 wt%; above 100k counts, all elements above 1.5 wt% exhibited RSD < 5%; and above 1M counts, major element oxide RSD was consistently below 2% (guyett2024optimizingsemedxfor pages 4-6). They recommended a minimum of 1M total spectrum counts for fully quantitative major-element SEM-EDX analysis, achievable in approximately 15 seconds with modern multi-detector SDD systems.\n\n### 5. Currie's Detection-Limit Framework (the \"3-sigma\" Criterion)\n\nThe widely used \"3-sigma\" detection criterion traces to Currie's seminal 1968 paper in Analytical Chemistry, which rigorously separated three quantities using hypothesis-testing theory (currie1999detectionandquantification pages 2-4, currie1999detectionandquantification pages 1-2):\n\n1. **Critical value (decision threshold) Lc = z\u2081\u208b\u03b1\u00b7\u03c3\u2080 = 1.645\u03c3\u2080** (for \u03b1 = 0.05): the threshold above which the analyst decides \"detected.\" This controls only the false-positive rate.\n\n2. **Detection limit Ld = Lc + z\u2081\u208b\u03b2\u00b7\u03c3d \u2248 2\u00d7Lc = 3.29\u03c3\u2080** (for \u03b1 = \u03b2 = 0.05, homoscedastic Gaussian): the true signal level at which the probability of a false negative is also limited to \u03b2 = 0.05. The factor 3.29 (not 3) arises from the sum of two one-sided z-quantiles: 1.645 + 1.645 = 3.29.\n\n3. **Quantification limit Lq = kq\u00b7\u03c3\u2080 = 10\u03c3\u2080** (for 10% RSD at the quantification limit).\n\nThe casual shorthand \"3-sigma detection limit\" conflates the decision threshold (1.645\u03c3) with the detection limit (3.29\u03c3) and slightly misquotes the coefficient. Currie (1999) reviewed this confusion, noting that prior approaches ignoring false negatives effectively set \u03b2 = 0.50, yielding detection capability estimates that differed by up to three orders of magnitude from the hypothesis-testing result (currie1999detectionandquantification pages 1-2, currie1999detectionandquantification pages 4-6).\n\nIn the EDS microanalysis context, Newbury and Ritchie (2019) express the concentration detection limit as CDL = [3\u221aNB/(NS \u2212 NB)]\u00b7CS, where NB is the background counts under the peak, NS is the total peak integral counts, and CS is the known concentration (newbury2019electronexcitedxraymicroanalysis pages 13-15). This functional form traces directly to Ziebold's (1967) sensitivity expression CDL > 3.29a/(ntP \u00d7 P/B)^(1/2), where a relates composition to intensity, n is the number of observations, tP is counting time, and P/B is the peak-to-background ratio (rinaldi2015electronprobemicroanalysis pages 4-5). Both formulations encode the same Poisson-statistics\u2013based detection theory.\n\n### 6. Standards vs. Genuine Optima vs. Committee Convention\n\nThe table below synthesizes how each parameter was derived and whether it represents a true optimum or a codified convention:\n\n| Parameter | Common recommended value | How the number was derived | Key primary literature / anchor reference | True optimum or convention? | Shift at low-kV / trace analysis |\n|---|---|---|---|---|---|\n| Overvoltage ratio U0 = E0/Ec | Typically ~2\u20133; ISO floor for quant often stated as \u22651.8 | From the inner-shell ionization cross-section rising steeply just above threshold and then flattening or declining in benefit per added kV, as described by Bethe-type formulations and later evaluated by Powell, Llovet, and Salvat; thick-target X-ray production efficiency measurements by Green and Cosslett showed characteristic yield peaking broadly near modest overvoltage, not at the highest beam energy. The competing penalty is that electron range and interaction volume grow strongly with E0, approximately by Kanaya\u2013Okayama scaling, while phi(rho-z) depth distributions show X-ray generation moving deeper, increasing absorption and reducing spatial resolution. Thus the rule came from maximizing useful characteristic production per unit interaction volume, not from committee preference alone. (goldstein2018quantitativeanalysisthe pages 4-6, goldstein2018quantitativeanalysisthe pages 9-11, rinaldi2015electronprobemicroanalysis pages 7-8, newbury2019electronexcitedxraymicroanalysis pages 13-15, rinaldi2015electronprobemicroanalysis pages 2-4, tong2026measurementuncertaintiesof pages 8-11) | Bethe theory; Green and Cosslett 1961, 1968 measurements; Kanaya and Okayama 1972; Castaing-origin phi(rho-z) framework as summarized in later reviews | Mostly a genuine physics optimum, but broad rather than sharp; committees codified a robust operating zone | At \u22645 keV the optimum is often driven by line accessibility and spatial resolution rather than by the classic 2\u20133 rule alone; one may accept lower overvoltage (~1.25\u20131.8) to keep the interaction volume small or to reach only available L or M lines, with increased sensitivity to absorption, surface films, and matrix-correction error. For Mg K-alpha at 5 keV, U0 \u2248 5/1.254 \u2248 4.0: excitation is ample, but the practical limit becomes background, absorption, and overlap handling rather than insufficient ionization. (newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2019electronexcitedxraymicroanalysis pages 16-18, rinaldi2015electronprobemicroanalysis pages 7-8, wuhrer2016lowvoltageimaging pages 7-10, wuhrer2016lowvoltageimaging pages 10-12) |\n| Detector dead time / throughput | Historically ~20\u201340% for Si(Li); modern standards-based SDD quant often kept much lower, commonly <10\u201315% on the most intense peak if coincidence artifacts matter | Derived from counting-system dead-time theory. For a paralyzable model, stored rate behaves approximately as OCR = ICR \u00d7 exp(-ICR \u00d7 tau), which peaks at ICR \u00d7 tau = 1, i.e. 36.8% dead time; for a non-paralyzable model OCR = ICR/(1 + ICR \u00d7 tau), throughput keeps rising but with diminishing returns. Real EDS electronics also have anti-coincidence rejection and pile-up artifacts, so the practical maximum useful throughput occurs before the mathematical maximum if sum peaks will compromise quantification. Goldstein shows OCR\u2013ICR curves and coincidence-peak growth; Donovan shows why simple linear dead-time correction breaks down at higher rates. (goldstein2018quantitativeanalysisthe pages 6-8, goldstein2018energydispersivexray pages 9-10, donovan2023anewmethod pages 3-4, donovan2023anewmethod pages 2-3, donovan2023anewmethod pages 4-5) | Classic dead-time theory; modern microanalysis implementation in Goldstein and Donovan | A real throughput optimum exists mathematically, but the widely taught 20\u201340% band is partly a practical convention balancing throughput against pile-up; with SDD quantitative work the optimum for accuracy often shifts lower | For low-kV and trace work, keep dead time lower because weak trace peaks can be hidden by coincidence peaks and by calibration or resolution drift at high rates. Modern SDDs can run at high OCR, but if looking for 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, a conservative dead time (~10\u201320%, or even lower if sum peaks intrude) is usually preferable to maximize spectral cleanliness. (goldstein2018quantitativeanalysisthe pages 6-8, goldstein2018energydispersivexray pages 9-10, guyett2024optimizingsemedxfor pages 4-6, guyett2024optimizingsemedxfor pages 3-4) |\n| Pulse processor shaping / process time | Choose a moderate setting: a few eV worse than best resolution, but far better throughput; avoid adaptive shaping for standards-based quant | Derived from the equivalent-noise-charge minimum. Lechner gives ENC^2 = serial white term proportional to 1/tau + a 1/f term + a parallel-noise term proportional to tau: short shaping times increase series white noise and ballistic-deficit sensitivity; long shaping times increase parallel-noise contribution and pile-up probability. Therefore the optimum is at the broad minimum of ENC versus shaping time, then adjusted upward or downward depending on count-rate needs. Goldstein describes the three-way trade-off among resolution, throughput, and coincidence rate; Schlosser and Niculae show measured FWHM versus shaping time for SDDs. (goldstein2018energydispersivexray pages 25-26, goldstein2018energydispersivexray pages 14-15, newbury2011isscanningelectron pages 2-3, niculae2006optimizedreadoutmethods pages 2-3, niculae2006optimizedreadoutmethods pages 3-6, schlosser2010expandingthedetection pages 2-4, lechner2004novelhighresolutionsilicon pages 2-4, lechner2004novelhighresolutionsilicon pages 4-5) | Semiconductor-detector noise theory; Lechner 2004; Niculae 2006; Schlosser 2010; later digital-pulse work such as Blaj 2017 | Genuine electronics optimum, but broad; the exact chosen setting is instrument-specific and thus partly conventional in practice | At low-kV, low-energy peaks are narrow and often crowded, so somewhat longer shaping than for fast mapping may be justified if resolving Mg, Al, Si low-energy structure matters. For trace analysis, prioritize stability and peak shape over absolute OCR; sacrificing a small amount of throughput for cleaner low-energy deconvolution is often worthwhile. (goldstein2018energydispersivexray pages 14-15, newbury2011isscanningelectron pages 2-3, schlosser2010expandingthedetection pages 2-4, wuhrer2016lowvoltageimaging pages 10-12) |\n| Live time / counts for precision | Rule of thumb: ~10,000 net counts in a peak of interest gives ~1% counting RSD; major-element whole-spectrum quant often uses 10^6 total counts or more | Pure Poisson statistics: for net peak counts N, sigma/N \u2248 1/sqrt(N). Thus N = 10^4 gives 1% relative standard deviation from counting alone. Real net-peak precision is worse when background subtraction is needed, so standards and unknowns both require sufficient dose. Newbury and Goldstein tables separate counting error from matrix-correction error; Guyett empirically found >10^5 counts gives <5% RSD for >1.5 wt% oxides and recommends ~10^6 counts for robust quantitative SEM-EDX of majors. (goldstein2018quantitativeanalysisthe pages 8-9, goldstein2018quantitativeanalysisthe pages 9-11, newbury2019electronexcitedxraymicroanalysis pages 13-15, newbury2015performingelementalmicroanalysis pages 2-4, guyett2024optimizingsemedxfor pages 4-6) | Poisson counting law; Ziebold 1967 sensitivity framework; Currie 1968 and 1999 for limits; Newbury and Ritchie applications | This is a true statistical relationship, not convention; the exact count targets are practical translations of desired precision | Low-kV reduces continuum volume but often lowers usable peak-to-background and can worsen matrix sensitivity for low-energy lines, so more counts may be needed than the simple 10^4 rule suggests. For 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, several 10^5 to ~10^6 total counts, or repeated acquisitions summed after drift or damage checks, is more realistic if one wants robust sub-wt% precision. (newbury2019electronexcitedxraymicroanalysis pages 13-15, ritchie2018exploringthelimits pages 9-11, ritchie2018exploringthelimits pages 4-5, guyett2024optimizingsemedxfor pages 4-6) |\n| Detection criterion | Currie 3-sigma family: LC = 1.645 sigma0, LD = 3.29 sigma0 for alpha = beta = 0.05; often simplified in practice to 3 sigma detection | Currie\u2019s 1968 hypothesis-testing framework separated the decision threshold LC from the true minimum detectable amount LD. Under Gaussian, homoscedastic approximation and equal Type-I and Type-II risks of 0.05, LC = 1.645 sigma0, and LD = LC + 1.645 sigmaD \u2248 3.29 sigma0. For counting data, sigma is usually controlled by blank or background counts, which is why detection capability depends on the background under the peak. Newbury expresses the same idea in concentration form as CDL = [3 \u00d7 sqrt(NB)/(NS \u2212 NB)] \u00d7 CS. (currie1999detectionandquantification pages 4-6, currie1999detectionandquantification pages 2-4, currie1999detectionandquantification pages 1-2, newbury2019electronexcitedxraymicroanalysis pages 13-15, rinaldi2015electronprobemicroanalysis pages 4-5) | Currie 1968; Currie 1999 retrospective; Ziebold 1967 concentration sensitivity expression | A genuine statistical derivation; the casual phrase 3-sigma is a simplified convention for Currie\u2019s more exact 3.29-sigma detection limit | At low-kV the blank and low-energy artifacts become more dominant, so sigma is often set by background modeling, contamination, and deconvolution residuals rather than by raw peak counts alone. For Mg K-alpha at 0.5\u20131 wt% in AlSi10Mg at 5 keV, formal detectability is usually not the bottleneck; reliable quantification is limited more by standards and matrix-correction quality, low-energy peak fitting, and reproducibility than by passing the Currie decision threshold. (wuhrer2016lowvoltageimaging pages 10-12, newbury2019electronexcitedxraymicroanalysis pages 13-15, tong2026measurementuncertaintiesof pages 8-11) |\n\n\n*Table: This table summarizes how the standard SEM-EDS acquisition parameters were justified from physics, electronics, and counting statistics rather than merely adopted by standards committees. It also shows which values are true optima, which are practical conventions, and how they shift for low-voltage and trace-level analysis.*\n\nSeveral observations emerge regarding the nature of these recommendations:\n\n- The **overvoltage ratio** of ~2\u20133 reflects a genuine but broad physics optimum: the Bethe cross-section maximum is broad, and the exact best value depends on whether one prioritizes intensity, spatial resolution, or matrix-correction accuracy. ISO 22309:2011 codified a floor of 1.8, which is a conservative standardization of the physics (tong2026measurementuncertaintiesof pages 8-11).\n\n- The **dead-time** guidance evolved from 20\u201340% (Si(Li) era, optimizing stored-count rate) to <10% (SDD era, minimizing coincidence peaks for trace analysis) as detector technology changed. No published round-robin explicitly validated the 20\u201340% range; it was derived from dead-time throughput curves and practical experience (goldstein2018quantitativeanalysisthe pages 6-8).\n\n- The **process time** setting has a genuine electronics optimum (the ENC minimum), but the commercially available settings and naming conventions differ between vendors, making the specific recommendation partly instrument-dependent (goldstein2018energydispersivexray pages 14-15, lechner2004novelhighresolutionsilicon pages 2-4).\n\n- The **10,000-count rule** is a direct mathematical consequence of Poisson statistics and is not convention. The translation into specific live-times depends entirely on count rates, which depend on all other parameters.\n\n- **Currie's 3.29\u03c3 detection limit** is a rigorous derivation from Neyman-Pearson hypothesis testing at specified error rates, not an empirical guess. The common simplification to \"3\u03c3\" is a minor approximation that has become conventional shorthand (currie1999detectionandquantification pages 2-4).\n\nRegarding interlaboratory validation, Newbury and Ritchie (2015) demonstrated that the k-ratio/matrix correction protocol with SDD-EDS achieves accuracy matching the WDS distribution established in 1975 (approximately 2.5% relative standard deviation for major constituents, with ~95% of analyses falling within \u00b15% relative error) (newbury2015performingelementalmicroanalysis pages 2-4). However, no published round-robin study was identified that systematically varied EDS acquisition parameters (overvoltage, dead-time, process time) across laboratories to validate the specific recommended ranges. The standards appear to have been written by codifying well-understood physics relationships and experienced practitioners' consensus within ISO TC 202 and ASTM E04 committees.\n\n### 7. Shifts for Low-Voltage Microanalysis and Trace Quantification\n\n**Low beam energy (\u22645 keV).** At low voltage, the conventional parameter optima shift significantly. A beam energy of 5 keV represents the lowest value at which at least one characteristic X-ray peak can be excited for all elements of the periodic table except H and He (newbury2019electronexcitedxraymicroanalysis pages 13-15). At lower voltages, an increasing number of elements becomes inaccessible. The analyst is forced to use unfamiliar X-ray families (e.g., Ba M-family instead of Ba L-family) which may suffer severe mutual interferences, as demonstrated for YBa\u2082Cu\u2083O\u2087 analyzed at 5 keV where O K, Cu L, and Ba M families overlap (newbury2019electronexcitedxraymicroanalysis pages 16-18). Rinaldi and Llovet (2015) documented systematic deviations in transition-element analysis at low voltages (5\u20136 keV), including Cr underestimation (\u22120.7% to \u221217%) and Fe/Ni overestimation (+14% to +42%), attributed to problems with mass absorption coefficients and low fluorescence yields for L-lines (rinaldi2015electronprobemicroanalysis pages 7-8). The interaction volume reduction (approximately 100-fold decrease from 20 keV to 1 keV) improves spatial resolution to the sub-micrometer scale but reduces absolute X-ray yield per electron, requiring higher beam currents or longer counting times (gollaschindler2026edswithlowvoltage pages 3-6). Surface contamination layers and native oxides, which are negligible at 20 keV, become significant contributors to the measured spectrum at low voltage (newbury2019electronexcitedxraymicroanalysis pages 13-15).\n\n**Trace-element quantification near 0.5\u20131 wt%.** For Mg K\u03b1 (1.254 keV) at 0.5\u20131 wt% in AlSi10Mg measured at 5 keV with an SDD, the overvoltage is generous (U\u2080 \u2248 4.0), so excitation efficiency is not limiting. The challenges are instead: (a) the Mg K peak sits in a crowded low-energy region where Al K (1.486 keV) is a dominant neighboring peak; (b) peak-to-background ratios for the Mg peak depend on the continuum modeling and the detector response at low energies; (c) the absorption correction for low-energy photons becomes large and uncertain; and (d) surface contamination carbon deposition can increase absorption of X-rays near the carbon K-edge (0.284 keV) and affect quantification of light elements. Newbury and Ritchie showed that detection limits of 200\u2013500 ppm (0.02\u20130.05 wt%) are achievable at conventional voltages within 500 s counting time (newbury2019electronexcitedxraymicroanalysis pages 13-15), but at low voltage the effective detection limit for a given counting time may be worse due to increased background relative to peak and poorer matrix-correction accuracy (wuhrer2016lowvoltageimaging pages 10-12). For reliable quantification of 0.5\u20131 wt% Mg, standards-based analysis with well-characterized standards and careful peak fitting is essential; standardless methods showed ~95% of results within \u00b125% relative deviation in early testing, an unacceptable error for trace-level work (newbury2019electronexcitedxraymicroanalysis pages 18-20). The practical recommendation is to collect substantially more counts than the simple 10\u2074-count rule would suggest (several 10\u2075 to 10\u2076 total spectrum counts), use a moderate process time prioritizing spectral stability over maximum throughput, keep dead time conservatively low to avoid pile-up artifacts in the energy region of interest, and employ multiple replicate measurements with statistical quality-control tests to monitor drift and damage (ritchie2018exploringthelimits pages 4-5, guyett2024optimizingsemedxfor pages 4-6).\n\nReferences\n\n1. (goldstein2018quantitativeanalysisthe pages 4-6): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n2. (goldstein2018quantitativeanalysisthe pages 9-11): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n3. (tong2026measurementuncertaintiesof pages 8-11): V. Tong and K. Mingard. Measurement uncertainties of energy dispersive x-ray spectroscopy in the scanning electron microscope (sem-edx/eds). Unknown journal, Mar 2026. URL: https://doi.org/10.47120/npl.mat135, doi:10.47120/npl.mat135.\n\n4. (newbury2019electronexcitedxraymicroanalysis pages 13-15): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n5. (goldstein2018energydispersivexray pages 9-10): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n6. (goldstein2018quantitativeanalysisthe pages 6-8): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n7. (donovan2023anewmethod pages 2-3): John J Donovan, Aur\u00e9lien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050. This article has 18 citations.\n\n8. (donovan2023anewmethod pages 3-4): John J Donovan, Aur\u00e9lien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050. This article has 18 citations.\n\n9. (goldstein2018energydispersivexray pages 14-15): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n10. (lechner2004novelhighresolutionsilicon pages 2-4): P. Lechner, A. Pahlke, and H. Soltau. Novel high-resolution silicon drift detectors. X-Ray Spectrometry, 33:256-261, Jul 2004. URL: https://doi.org/10.1002/xrs.717, doi:10.1002/xrs.717. This article has 111 citations and is from a peer-reviewed journal.\n\n11. (schlosser2010expandingthedetection pages 2-4): D.M. Schlosser, P. Lechner, G. Lutz, A. Niculae, H. Soltau, L. Str\u00fcder, R. Eckhardt, K. Hermenau, G. Schaller, F. Schopper, O. Jaritschin, A. Liebel, A. Simsek, C. Fiorini, and A. Longoni. Expanding the detection efficiency of silicon drift detectors. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 624:270-276, Dec 2010. URL: https://doi.org/10.1016/j.nima.2010.04.038, doi:10.1016/j.nima.2010.04.038. This article has 88 citations.\n\n12. (lechner2004novelhighresolutionsilicon pages 4-5): P. Lechner, A. Pahlke, and H. Soltau. Novel high-resolution silicon drift detectors. X-Ray Spectrometry, 33:256-261, Jul 2004. URL: https://doi.org/10.1002/xrs.717, doi:10.1002/xrs.717. This article has 111 citations and is from a peer-reviewed journal.\n\n13. (goldstein2018energydispersivexray pages 25-26): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Energy dispersive x-ray spectrometry: physical principles and user-selected parameters. ArXiv, pages 209-234, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_16, doi:10.1007/978-1-4939-6676-9\\_16. This article has 33 citations.\n\n14. (newbury2011isscanningelectron pages 2-3): Dale E. Newbury and Nicholas W. M. Ritchie. Is scanning electron microscopy/energy dispersive x-ray spectroscopy (sem/eds) quantitative? effect of specimen shape. SPIE Proceedings, 8036:803602, May 2011. URL: https://doi.org/10.1117/12.881040, doi:10.1117/12.881040. This article has 3 citations.\n\n15. (goldstein2018quantitativeanalysisthe pages 8-9): Joseph I. Goldstein, Dale E. Newbury, Joseph R. Michael, Nicholas W. M. Ritchie, John Henry J. Scott, and David C. Joy. Quantitative analysis: the sem/eds elemental microanalysis k-ratio procedure for bulk specimens, step-by-step. ArXiv, pages 309-339, Nov 2018. URL: https://doi.org/10.1007/978-1-4939-6676-9\\_20, doi:10.1007/978-1-4939-6676-9\\_20. This article has 9 citations.\n\n16. (guyett2024optimizingsemedxfor pages 4-6): Paul C. Guyett, David Chew, Vitor Azevedo, Lucy C. Blennerhassett, Carolina Rosca, and Emma Tomlinson. Optimizing sem-edx for fast, high-quality and non-destructive elemental analysis of glass. Journal of Analytical Atomic Spectrometry, 39:2565-2579, Jan 2024. URL: https://doi.org/10.1039/d4ja00212a, doi:10.1039/d4ja00212a. This article has 50 citations and is from a peer-reviewed journal.\n\n17. (currie1999detectionandquantification pages 2-4): Lloyd A. Currie. Detection and quantification limits: origins and historical overview1adapted from the proceedings of the 1996 joint statistical meetings (american statistical association, 1997). original title: \u201cfoundations and future of detection and quantification limits\u201d. contribution of the national institute of standards and technology; not subject to copyright.1. May 1999. URL: https://doi.org/10.1016/s0003-2670(99)00105-1, doi:10.1016/s0003-2670(99)00105-1. This article has 701 citations and is from a domain leading peer-reviewed journal.\n\n18. (currie1999detectionandquantification pages 1-2): Lloyd A. Currie. Detection and quantification limits: origins and historical overview1adapted from the proceedings of the 1996 joint statistical meetings (american statistical association, 1997). original title: \u201cfoundations and future of detection and quantification limits\u201d. contribution of the national institute of standards and technology; not subject to copyright.1. May 1999. URL: https://doi.org/10.1016/s0003-2670(99)00105-1, doi:10.1016/s0003-2670(99)00105-1. This article has 701 citations and is from a domain leading peer-reviewed journal.\n\n19. (currie1999detectionandquantification pages 4-6): Lloyd A. Currie. Detection and quantification limits: origins and historical overview1adapted from the proceedings of the 1996 joint statistical meetings (american statistical association, 1997). original title: \u201cfoundations and future of detection and quantification limits\u201d. contribution of the national institute of standards and technology; not subject to copyright.1. May 1999. URL: https://doi.org/10.1016/s0003-2670(99)00105-1, doi:10.1016/s0003-2670(99)00105-1. This article has 701 citations and is from a domain leading peer-reviewed journal.\n\n20. (rinaldi2015electronprobemicroanalysis pages 4-5): Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.\n\n21. (rinaldi2015electronprobemicroanalysis pages 7-8): Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.\n\n22. (rinaldi2015electronprobemicroanalysis pages 2-4): Romano Rinaldi and Xavier Llovet. Electron probe microanalysis: a review of the past, present, and future. Microscopy and Microanalysis, 21:1053-1069, May 2015. URL: https://doi.org/10.1017/s1431927615000409, doi:10.1017/s1431927615000409. This article has 98 citations and is from a peer-reviewed journal.\n\n23. (newbury2019electronexcitedxraymicroanalysis pages 16-18): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.\n\n24. (wuhrer2016lowvoltageimaging pages 7-10): Richard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.\n\n25. (wuhrer2016lowvoltageimaging pages 10-12): Richard Wuhrer and K. Moran. Low voltage imaging and x-ray microanalysis in the sem: challenges and opportunities. IOP Conference Series: Materials Science and Engineering, 109:012019, Feb 2016. URL: https://doi.org/10.1088/1757-899x/109/1/012019, doi:10.1088/1757-899x/109/1/012019. This article has 67 citations.\n\n26. (donovan2023anewmethod pages 4-5): John J Donovan, Aur\u00e9lien Moy, Anette von der Handt, Zack Gainsforth, James L Maner, William Nachlas, and John Fournelle. A new method for dead time calibration and a new expression for correction of wds intensities for microanalysis. Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada, 29 3:1096-1110, May 2023. URL: https://doi.org/10.1093/micmic/ozad050, doi:10.1093/micmic/ozad050. This article has 18 citations.\n\n27. (guyett2024optimizingsemedxfor pages 3-4): Paul C. Guyett, David Chew, Vitor Azevedo, Lucy C. Blennerhassett, Carolina Rosca, and Emma Tomlinson. Optimizing sem-edx for fast, high-quality and non-destructive elemental analysis of glass. Journal of Analytical Atomic Spectrometry, 39:2565-2579, Jan 2024. URL: https://doi.org/10.1039/d4ja00212a, doi:10.1039/d4ja00212a. This article has 50 citations and is from a peer-reviewed journal.\n\n28. (niculae2006optimizedreadoutmethods pages 2-3): A. Niculae, P. Lechner, H. Soltau, G. Lutz, L. Str\u00fcder, C. Fiorini, and A. Longoni. Optimized readout methods of silicon drift detectors for high-resolution x-ray spectroscopy. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 568:336-342, Nov 2006. URL: https://doi.org/10.1016/j.nima.2006.06.025, doi:10.1016/j.nima.2006.06.025. This article has 76 citations.\n\n29. (niculae2006optimizedreadoutmethods pages 3-6): A. Niculae, P. Lechner, H. Soltau, G. Lutz, L. Str\u00fcder, C. Fiorini, and A. Longoni. Optimized readout methods of silicon drift detectors for high-resolution x-ray spectroscopy. Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment, 568:336-342, Nov 2006. URL: https://doi.org/10.1016/j.nima.2006.06.025, doi:10.1016/j.nima.2006.06.025. This article has 76 citations.\n\n30. (newbury2015performingelementalmicroanalysis pages 2-4): Dale E. Newbury and Nicholas W. M. Ritchie. Performing elemental microanalysis with high accuracy and high precision by scanning electron microscopy/silicon drift detector energy-dispersive x-ray spectrometry (sem/sdd-eds). Journal of Materials Science, 50:493-518, Nov 2015. URL: https://doi.org/10.1007/s10853-014-8685-2, doi:10.1007/s10853-014-8685-2. This article has 609 citations and is from a peer-reviewed journal.\n\n31. (ritchie2018exploringthelimits pages 9-11): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\n32. (ritchie2018exploringthelimits pages 4-5): N W M Ritchie, D E Newbury, H Lowers, and M Mengason. Exploring the limits of eds microanalysis: rare earth element analyses. IOP Conference Series: Materials Science and Engineering, 304:012013, Aug 2018. URL: https://doi.org/10.1088/1757-899x/304/1/012013, doi:10.1088/1757-899x/304/1/012013. This article has 15 citations.\n\n33. (gollaschindler2026edswithlowvoltage pages 3-6): Ute Golla-Schindler and Gerhard Schneider. Eds with low-voltage sem: possibilities and limitations of lithium detection and quantification. EPJ Web of Conferences, 349:01004, Jan 2026. URL: https://doi.org/10.1051/epjconf/202634901004, doi:10.1051/epjconf/202634901004. This article has 0 citations and is from a peer-reviewed journal.\n\n34. (newbury2019electronexcitedxraymicroanalysis pages 18-20): Dale E. Newbury and Nicholas W.M. Ritchie. Electron-excited x-ray microanalysis by energy dispersive spectrometry at 50: analytical accuracy, precision, trace sensitivity, and quantitative compositional mapping. Microscopy and Microanalysis, 25:1075-1105, Oct 2019. URL: https://doi.org/10.1017/s143192761901482x, doi:10.1017/s143192761901482x. This article has 69 citations and is from a peer-reviewed journal.",
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+              "artifact-00": "| Parameter | Common recommended value | How the number was derived | Key primary literature / anchor reference | True optimum or convention? | Shift at low-kV / trace analysis |\n|---|---|---|---|---|---|\n| Overvoltage ratio U0 = E0/Ec | Typically ~2\u20133; ISO floor for quant often stated as \u22651.8 | From the inner-shell ionization cross-section rising steeply just above threshold and then flattening or declining in benefit per added kV, as described by Bethe-type formulations and later evaluated by Powell, Llovet, and Salvat; thick-target X-ray production efficiency measurements by Green and Cosslett showed characteristic yield peaking broadly near modest overvoltage, not at the highest beam energy. The competing penalty is that electron range and interaction volume grow strongly with E0, approximately by Kanaya\u2013Okayama scaling, while phi(rho-z) depth distributions show X-ray generation moving deeper, increasing absorption and reducing spatial resolution. Thus the rule came from maximizing useful characteristic production per unit interaction volume, not from committee preference alone. (pqac-00000007, pqac-00000008, pqac-00000028, pqac-00000043, pqac-00000050, pqac-00000053) | Bethe theory; Green and Cosslett 1961, 1968 measurements; Kanaya and Okayama 1972; Castaing-origin phi(rho-z) framework as summarized in later reviews | Mostly a genuine physics optimum, but broad rather than sharp; committees codified a robust operating zone | At \u22645 keV the optimum is often driven by line accessibility and spatial resolution rather than by the classic 2\u20133 rule alone; one may accept lower overvoltage (~1.25\u20131.8) to keep the interaction volume small or to reach only available L or M lines, with increased sensitivity to absorption, surface films, and matrix-correction error. For Mg K-alpha at 5 keV, U0 \u2248 5/1.254 \u2248 4.0: excitation is ample, but the practical limit becomes background, absorption, and overlap handling rather than insufficient ionization. (pqac-00000043, pqac-00000045, pqac-00000028, pqac-00000029, pqac-00000030) |\n| Detector dead time / throughput | Historically ~20\u201340% for Si(Li); modern standards-based SDD quant often kept much lower, commonly <10\u201315% on the most intense peak if coincidence artifacts matter | Derived from counting-system dead-time theory. For a paralyzable model, stored rate behaves approximately as OCR = ICR \u00d7 exp(-ICR \u00d7 tau), which peaks at ICR \u00d7 tau = 1, i.e. 36.8% dead time; for a non-paralyzable model OCR = ICR/(1 + ICR \u00d7 tau), throughput keeps rising but with diminishing returns. Real EDS electronics also have anti-coincidence rejection and pile-up artifacts, so the practical maximum useful throughput occurs before the mathematical maximum if sum peaks will compromise quantification. Goldstein shows OCR\u2013ICR curves and coincidence-peak growth; Donovan shows why simple linear dead-time correction breaks down at higher rates. (pqac-00000009, pqac-00000011, pqac-00000046, pqac-00000047, pqac-00000048, pqac-00000049) | Classic dead-time theory; modern microanalysis implementation in Goldstein and Donovan | A real throughput optimum exists mathematically, but the widely taught 20\u201340% band is partly a practical convention balancing throughput against pile-up; with SDD quantitative work the optimum for accuracy often shifts lower | For low-kV and trace work, keep dead time lower because weak trace peaks can be hidden by coincidence peaks and by calibration or resolution drift at high rates. Modern SDDs can run at high OCR, but if looking for 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, a conservative dead time (~10\u201320%, or even lower if sum peaks intrude) is usually preferable to maximize spectral cleanliness. (pqac-00000009, pqac-00000046, pqac-00000054, pqac-00000055) |\n| Pulse processor shaping / process time | Choose a moderate setting: a few eV worse than best resolution, but far better throughput; avoid adaptive shaping for standards-based quant | Derived from the equivalent-noise-charge minimum. Lechner gives ENC^2 = serial white term proportional to 1/tau + a 1/f term + a parallel-noise term proportional to tau: short shaping times increase series white noise and ballistic-deficit sensitivity; long shaping times increase parallel-noise contribution and pile-up probability. Therefore the optimum is at the broad minimum of ENC versus shaping time, then adjusted upward or downward depending on count-rate needs. Goldstein describes the three-way trade-off among resolution, throughput, and coincidence rate; Schlosser and Niculae show measured FWHM versus shaping time for SDDs. (pqac-00000014, pqac-00000015, pqac-00000016, pqac-00000023, pqac-00000024, pqac-00000025, pqac-00000026, pqac-00000027) | Semiconductor-detector noise theory; Lechner 2004; Niculae 2006; Schlosser 2010; later digital-pulse work such as Blaj 2017 | Genuine electronics optimum, but broad; the exact chosen setting is instrument-specific and thus partly conventional in practice | At low-kV, low-energy peaks are narrow and often crowded, so somewhat longer shaping than for fast mapping may be justified if resolving Mg, Al, Si low-energy structure matters. For trace analysis, prioritize stability and peak shape over absolute OCR; sacrificing a small amount of throughput for cleaner low-energy deconvolution is often worthwhile. (pqac-00000015, pqac-00000016, pqac-00000025, pqac-00000030) |\n| Live time / counts for precision | Rule of thumb: ~10,000 net counts in a peak of interest gives ~1% counting RSD; major-element whole-spectrum quant often uses 10^6 total counts or more | Pure Poisson statistics: for net peak counts N, sigma/N \u2248 1/sqrt(N). Thus N = 10^4 gives 1% relative standard deviation from counting alone. Real net-peak precision is worse when background subtraction is needed, so standards and unknowns both require sufficient dose. Newbury and Goldstein tables separate counting error from matrix-correction error; Guyett empirically found >10^5 counts gives <5% RSD for >1.5 wt% oxides and recommends ~10^6 counts for robust quantitative SEM-EDX of majors. (pqac-00000006, pqac-00000008, pqac-00000034, pqac-00000041, pqac-00000043, pqac-00000054) | Poisson counting law; Ziebold 1967 sensitivity framework; Currie 1968 and 1999 for limits; Newbury and Ritchie applications | This is a true statistical relationship, not convention; the exact count targets are practical translations of desired precision | Low-kV reduces continuum volume but often lowers usable peak-to-background and can worsen matrix sensitivity for low-energy lines, so more counts may be needed than the simple 10^4 rule suggests. For 0.5\u20131 wt% Mg in AlSi10Mg at 5 keV, several 10^5 to ~10^6 total counts, or repeated acquisitions summed after drift or damage checks, is more realistic if one wants robust sub-wt% precision. (pqac-00000034, pqac-00000036, pqac-00000038, pqac-00000054) |\n| Detection criterion | Currie 3-sigma family: LC = 1.645 sigma0, LD = 3.29 sigma0 for alpha = beta = 0.05; often simplified in practice to 3 sigma detection | Currie\u2019s 1968 hypothesis-testing framework separated the decision threshold LC from the true minimum detectable amount LD. Under Gaussian, homoscedastic approximation and equal Type-I and Type-II risks of 0.05, LC = 1.645 sigma0, and LD = LC + 1.645 sigmaD \u2248 3.29 sigma0. For counting data, sigma is usually controlled by blank or background counts, which is why detection capability depends on the background under the peak. Newbury expresses the same idea in concentration form as CDL = [3 \u00d7 sqrt(NB)/(NS \u2212 NB)] \u00d7 CS. (pqac-00000018, pqac-00000021, pqac-00000022, pqac-00000034, pqac-00000051) | Currie 1968; Currie 1999 retrospective; Ziebold 1967 concentration sensitivity expression | A genuine statistical derivation; the casual phrase 3-sigma is a simplified convention for Currie\u2019s more exact 3.29-sigma detection limit | At low-kV the blank and low-energy artifacts become more dominant, so sigma is often set by background modeling, contamination, and deconvolution residuals rather than by raw peak counts alone. For Mg K-alpha at 0.5\u20131 wt% in AlSi10Mg at 5 keV, formal detectability is usually not the bottleneck; reliable quantification is limited more by standards and matrix-correction quality, low-energy peak fitting, and reproducibility than by passing the Currie decision threshold. (pqac-00000030, pqac-00000034, pqac-00000043, pqac-00000053) |\n\n\n*Table: This table summarizes how the standard SEM-EDS acquisition parameters were justified from physics, electronics, and counting statistics rather than merely adopted by standards committees. It also shows which values are true optima, which are practical conventions, and how they shift for low-voltage and trace-level analysis.*"
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+        "query": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy)."
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+  "task": "How are the recommended acquisition-parameter values in SEM energy-dispersive X-ray spectroscopy (SEM-EDS) standards and textbooks actually derived? Standards and canonical references (ISO 22309, ASTM E1508, Goldstein et al. \"Scanning Electron Microscopy and X-ray Microanalysis\") recommend specific values: overvoltage ratio U0 of roughly 2-3 (accelerating voltage about twice the highest critical excitation energy of interest); detector dead time held around 20-40%; pulse-processor process/shaping time chosen to trade energy resolution against throughput; live time long enough for on the order of 10,000 net counts in a peak of interest (or several hundred thousand total spectrum counts); and the Currie 3-sigma criterion for deciding whether an element is detected.\n\nDo NOT simply restate these recommendations or say \"consult the standards.\" For each parameter, trace HOW the recommended value was originally chosen: the underlying physics models, counting-statistics derivations, and validation experiments in the primary literature that fixed the number. Cover at least: (1) ionization cross-section as a function of overvoltage (Bethe formulation; Green & Cosslett measurements) and why its maximum near U ~ 2-3 sets the kV rule, against the competing electron-range/interaction-volume growth (Kanaya-Okayama scaling) and depth distribution of X-ray production phi(rho-z) (Castaing tracer experiments onward); (2) the paralyzable/non-paralyzable dead-time throughput model (output rate = input rate x exp(-input x tau)) and why stored-count rate peaks at a particular dead-time fraction, giving the 20-40% guidance; (3) pulse shaping/process time in Si(Li) and silicon drift detector processors - the electronic-noise vs series-noise ballistic-deficit trade-off that links shaping time to energy resolution and maximum count rate; (4) Poisson counting statistics linking net peak counts to relative precision (why ~10^4 counts gives ~1% relative standard deviation) and Currie's 1968 derivation of decision/detection/determination limits from hypothesis-testing error rates (alpha = beta = 0.05) that yields the 3.29-sigma (commonly '3-sigma') criterion; (5) where the standard values are genuine optima of a quantified trade-off versus mere empirical convention adopted by committees (ISO TC 202, ASTM E04), including any published round-robin/interlaboratory studies used to justify them.\n\nFinally, explain how these optima shift for low-voltage microanalysis (beam energy <= 5 keV) and for trace-element quantification near 0.5-1 wt% - the concrete case being Mg K-alpha (1.254 keV) at 0.5-1 wt% in AlSi10Mg measured at 5 kV with an SDD - citing the low-kV and trace-analysis literature (e.g., Newbury & Ritchie on low-voltage SEM/EDS and on standardless quantification accuracy).",
+  "started_at": "2026-08-20T19:40:43.004888Z",
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diff --git a/scripts/eds_kfactor_quant.png b/scripts/eds_kfactor_quant.png
new file mode 100644
index 0000000..fde1074
Binary files /dev/null and b/scripts/eds_kfactor_quant.png differ
diff --git a/scripts/eds_kfactor_quant.py b/scripts/eds_kfactor_quant.py
new file mode 100644
index 0000000..311a667
--- /dev/null
+++ b/scripts/eds_kfactor_quant.py
@@ -0,0 +1,100 @@
+# Calibrated k-factor quantification of a real AlSi10Mg SEM-EDS sum spectrum
+# (Apreo SEM, EDAX Octane Plus, 5 kV, live time 327.7 s, takeoff 35.1 deg).
+#
+# k-factors are sensitivity factors valid ONLY for the exact acquisition
+# conditions (kV, detector, geometry), the exact fitting procedure that
+# produced the calibration intensities, AND compositions near the calibrant:
+# on a bulk sample they embed its matrix (ZAF) effects, which change with
+# composition, and eXSpy has no bulk matrix correction (quantification() is
+# TEM-only; no ZAF/phi-rho-z). Calibrate them once against a spectrum of
+# KNOWN composition, then reuse on other spectra measured the same way.
+# Replace KNOWN_WT with certified-standard values for standards-based numbers;
+# the vendor eZAF result is used here only as a placeholder reference.
+import numpy as np
+import matplotlib.pyplot as plt
+import hyperspy.api as hs
+
+CSV = "scripts/AlSi10Mg_EDS_Map_1.csv"
+BEAM_KV, LIVE_TIME, TAKEOFF, RES_MNKA = 5.0, 327.7, 35.1, 127.9
+ELEMENTS = ["Al", "C", "Mg", "O", "Si"]
+# calibration composition for the SAME spectrum (EDAX eZAF, Report.pdf p.5)
+KNOWN_WT = {"Al_Ka": 84.24, "C_Ka": 1.99, "Mg_Ka": 0.94, "O_Ka": 1.68, "Si_Ka": 11.15}
+
+data = np.loadtxt(CSV, delimiter=",")
+s = hs.signals.Signal1D(data[:, 1])
+s.set_signal_type("EDS_SEM")
+ax = s.axes_manager.signal_axes[0]
+ax.name, ax.units, ax.scale, ax.offset = "Energy", "keV", data[1, 0] - data[0, 0], data[0, 0]
+s.set_microscope_parameters(
+    beam_energy=BEAM_KV, live_time=LIVE_TIME, elevation_angle=TAKEOFF,
+    energy_resolution_MnKa=RES_MNKA,
+)
+s.add_elements(ELEMENTS)
+s.add_lines()
+
+# fit only the physical range: above the noise cutoff, below the Duane-Hunt limit (= beam kV)
+s = s.isig[0.045:BEAM_KV]
+s.estimate_poissonian_noise_variance()
+variance = s.metadata.Signal.Noise_properties.variance
+variance.data = np.clip(variance.data, 1, None)  # zero-count channels get infinite weight otherwise
+
+m = s.create_model()
+m.fit_background()
+for c in m:
+    if hasattr(c, "A"):
+        c.A.bmin = 0.0  # forbid negative peak areas
+m.fit(bounded=True)
+
+fitted = m.get_lines_intensity()
+counts = {f.metadata.Sample.xray_lines[0]: float(f.data.sum()) for f in fitted}
+
+# component curves evaluated through the model's own path (component.function()
+# evaluates against a different internal axis normalisation and gives wrong values)
+for c in m:
+    c.active = "background" in c.name
+background = m.as_signal().data
+for c in m:
+    c.active = "background" in c.name or c.name == "Mg_Ka"
+mg_curve = m.as_signal().data
+for c in m:
+    c.active = True
+
+# Currie detection check: net counts vs 3*sqrt(2B) with B taken +/- 1.2 FWHM around the line
+energy = s.axes_manager.signal_axes[0].axis
+for ln in counts:
+    comp = m[ln]
+    window = np.abs(energy - comp.centre.value) < 1.2 * comp.fwhm
+    B = float(background[window].sum())
+    print(f"{ln}: net={counts[ln]:9.0f}  bg_under_peak={B:8.0f}  "
+          f"significance={counts[ln] / np.sqrt(2 * B):7.1f} sigma  "
+          f"(detected: {counts[ln] > 3 * np.sqrt(2 * B)})")
+
+# calibrate k-factors (relative to Al) from the known composition, then apply.
+# On the calibration spectrum this reproduces KNOWN_WT by construction; the value
+# is reusing these k-factors on OTHER spectra taken under identical conditions.
+used = [ln for ln in counts if counts[ln] > 0]
+k = {ln: KNOWN_WT[ln] / counts[ln] for ln in used}
+k = {ln: v / k["Al_Ka"] for ln, v in k.items()}
+print("\ncalibrated k-factors (Al=1):", {ln: round(v, 3) for ln, v in k.items()})
+
+total = sum(k[ln] * counts[ln] for ln in used)
+wt = {ln: 100 * k[ln] * counts[ln] / total for ln in used}
+print("wt% =", {ln: round(v, 2) for ln, v in wt.items()})
+
+fig, axp = plt.subplots(figsize=(9, 5))
+axp.plot(energy, s.data, color="#6b6b6b", lw=1, drawstyle="steps-mid", label="measured")
+axp.plot(energy, m.as_signal().data, color="#0072B2", lw=2, label="model fit")
+axp.plot(energy, background, color="#009E73", lw=2, ls="--", label="background")
+axp.fill_between(energy, background, mg_curve, color="#D55E00", alpha=0.6, label="Mg K$\\alpha$")
+for ln in counts:
+    comp = m[ln]
+    peak_top = s.data[np.abs(energy - comp.centre.value).argmin()]
+    axp.annotate(ln.replace("_Ka", ""), (comp.centre.value, peak_top * 1.35),
+                 ha="center", fontsize=9, color="#404040")
+axp.set(xlim=(0.1, 2.5), yscale="log", ylim=(50, 1e5),
+        xlabel="Energy (keV)", ylabel="Counts per 5 eV channel",
+        title="AlSi10Mg sum spectrum, 5 kV — eXSpy model fit")
+axp.legend(frameon=False, loc="upper right")
+axp.grid(alpha=0.25)
+fig.tight_layout()
+fig.savefig("scripts/eds_kfactor_quant.png", dpi=150)