Article Bayesian inference method utilizing SESSA in quantitative layer structure estimation from XPS data

Atsushi Machida ; Kenji Nagata SAMURAI ORCID (National Institute for Materials Science) ; Ryo Murakami SAMURAI ORCID (National Institute for Materials Science) ; Hiroshi Shinotsuka SAMURAI ORCID (National Institute for Materials Science) ; Hayaru Shouno ; Hideki Yoshikawa SAMURAI ORCID (National Institute for Materials Science) ; Masato Okada

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Atsushi Machida, Kenji Nagata, Ryo Murakami, Hiroshi Shinotsuka, Hayaru Shouno, Hideki Yoshikawa, Masato Okada. Bayesian inference method utilizing SESSA in quantitative layer structure estimation from XPS data. Journal of Electron Spectroscopy and Related Phenomena. 2024, 273 (), 147449. https://doi.org/10.1016/j.elspec.2024.147449

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(abstract)

We propose a method that combines Bayesian inference with simulation of electron spectra for surface analysis (SESSA) to infer layer structures from XPS data. SESSA simulates XPS spectra for specified compositions and microstructures, producing highly reproducible results. Our method estimates the layer structure based on posterior probability distributions, applicable to both wide-scan and narrow-scan data without angle resolution. This approach allows for quantitative analysis of layer structure information in XPS measurements.

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Keyword: X-ray photoelectron spectroscopy, Bayesian estimation, Exchange Monte Carlo method, SESSA

Date published: 2024-05-29

Publisher: Elsevier BV

Journal:

  • Journal of Electron Spectroscopy and Related Phenomena (ISSN: 03682048) vol. 273 147449

Funding:

  • Core Research for Evolutional Science and Technology JPMJCR1761
  • Japan Science and Technology Agency
  • Japan Society for the Promotion of Science JP23KJ0471
  • Japan Society for the Promotion of Science JP23H00486

Manuscript type: Publisher's version (Version of record)

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First published URL: https://doi.org/10.1016/j.elspec.2024.147449

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Updated at: 2025-11-10 12:30:27 +0900

Published on MDR: 2025-11-10 12:24:32 +0900

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