Bayesian estimation for XPS spectral analysis at multiple core levels-Reference-Cited by-同舟云学术

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Bayesian estimation for XPS spectral analysis at multiple core levels

Published:2021-01-01 Issue:1 Volume:1 Page:123-133
ISSN:2766-0400
Container-title:Science and Technology of Advanced Materials: Methods
language:en
Short-container-title:Science and Technology of Advanced Materials: Methods

Author:

Machida Atsushi¹,Nagata Kenji²,Murakami Ryo³,Shinotsuka Hiroshi²,Shouno Hayaru³,Yoshikawa Hideki²,Okada Masato²⁴^ORCID

Affiliation:

1. Graduate School of Science, The University of Tokyo, Bunkyo, Japan

2. Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, Tsukuba, Japan

3. Department of Informatics, The University of Electro-Communications, Chofu, Japan

4. Graduate School of Frontier Science, The University of Tokyo, Kashiwa, Japan

Funder

Japan Science and Technology Agency

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/27660400.2021.1943172

Reference27 articles.

1. Development of multiple core-level XPS spectra decomposition method based on the Bayesian information criterion

2. Bayesian spectral deconvolution with the exchange Monte Carlo method

3. Product or sum: comparative tests of Voigt, and product or sum of Gaussian and Lorentzian functions in the fitting of synthetic Voigt-based X-ray photoelectron spectra

4. Practical methods for background subtraction in photoemission spectra

5. Reproducibility of XPS analysis for film thickness of SiO2/Si by active Shirley method

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2. Noise-robust analysis of X-Ray absorption near-edge structure based on poisson distribution;Science and Technology of Advanced Materials: Methods;2024-08-29

3. Bayesian inference method utilizing SESSA in quantitative layer structure estimation from XPS data;Journal of Electron Spectroscopy and Related Phenomena;2024-06

4. Correlation analysis with measurement conditions and peak structures in XPS spectral round-robin tests on MnO powder sample;Journal of Electron Spectroscopy and Related Phenomena;2023-04

5. High-throughput XPS spectrum modeling with autonomous background subtraction for 3 d _5/2 peak mapping of SnS;Science and Technology of Advanced Materials: Methods;2023-01-24

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