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Description:

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.

Rights:

• Creative Commons BY Attribution 4.0 International
  

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)

MDR DOI:

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