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A step toward calculating the uncertainties in combined GIXRF‐XRR

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Název: A step toward calculating the uncertainties in combined GIXRF‐XRR
Autoři: Stephanie Melhem, Yves Ménesguen, Emmanuel Nolot, Marie‐Christine Lépy
Přispěvatelé: CEA, Contributeur MAP
Zdroj: X-Ray Spectrometry. 52:412-422
Informace o vydavateli: Wiley, 2023.
Rok vydání: 2023
Témata: thin film, grazing incidence X-ray fluorescence, X-ray reflectivity, modelling, chalcogenide, Bootstrap statistical method, particle transport, multilayered material, signal processing, Monte Carlo, material characterisation, roughness, dynamic range, density, detector, uncertaintiy assessment, carbon caping layer, simulation, thickness, measuring procedures, metrology, elemental composition, [PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], associated uncertainties, ionizing radiation, [PHYS.COND] Physics [physics]/Condensed Matter [cond-mat], data analysis procedures
Popis: The combination of X‐ray reflectivity (XRR) and grazing incidence X‐ray fluorescence (GIXRF) is a surface sensitive analytical method, which can be used for the characterization of thin films and multilayered materials. Both of these techniques are implemented on the same experimental setup and make use of similar mechanical processes and the same fundamental physical concept required for a combined data analysis. The combination of these techniques removes ambiguous results for the characterization of nanometer layers, as well as nanometer depth profiles, resulting in more accurate characterization of thickness, roughness, density, and elemental composition. Due to the vast number of fitting parameters, the estimation of the thin film sample structure is a challenging task. In this paper, we propose a recursive method for estimating the uncertainties of data from GIXRF‐XRR analysis, based on a Bootstrap statistical method. This approach relies on re‐sampling a dataset to estimate statistics on a population by applying random weights. We applied this method on an as‐deposited chalcogenide germanium, antimony, and tellurium (GST) thin film with a carbon‐capping layer. We found good agreement between the experimental and the theoretical XRR‐GIXRF values for a sample structure model, of which the parameters were determined within a confidence interval using the bootstrap method. We also propose an approach for calculating the uncertainty on the solid angle of detection based on Monte Carlo simulations.
Druh dokumentu: Article
Popis souboru: application/pdf
Jazyk: English
ISSN: 1097-4539
0049-8246
DOI: 10.1002/xrs.3377
Přístupová URL adresa: https://cea.hal.science/cea-04563756v1/document
https://cea.hal.science/cea-04563756v1
https://doi.org/10.1002/xrs.3377
Rights: CC BY NC ND
Přístupové číslo: edsair.doi.dedup.....69a7ab0a0a432d4d5f0adff145eadc5b
Databáze: OpenAIRE
Popis
Abstrakt:The combination of X‐ray reflectivity (XRR) and grazing incidence X‐ray fluorescence (GIXRF) is a surface sensitive analytical method, which can be used for the characterization of thin films and multilayered materials. Both of these techniques are implemented on the same experimental setup and make use of similar mechanical processes and the same fundamental physical concept required for a combined data analysis. The combination of these techniques removes ambiguous results for the characterization of nanometer layers, as well as nanometer depth profiles, resulting in more accurate characterization of thickness, roughness, density, and elemental composition. Due to the vast number of fitting parameters, the estimation of the thin film sample structure is a challenging task. In this paper, we propose a recursive method for estimating the uncertainties of data from GIXRF‐XRR analysis, based on a Bootstrap statistical method. This approach relies on re‐sampling a dataset to estimate statistics on a population by applying random weights. We applied this method on an as‐deposited chalcogenide germanium, antimony, and tellurium (GST) thin film with a carbon‐capping layer. We found good agreement between the experimental and the theoretical XRR‐GIXRF values for a sample structure model, of which the parameters were determined within a confidence interval using the bootstrap method. We also propose an approach for calculating the uncertainty on the solid angle of detection based on Monte Carlo simulations.
ISSN:10974539
00498246
DOI:10.1002/xrs.3377