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Description:

X-ray Photoelectron Spectroscopy (XPS) is a powerful technique that reveals surface chemical states, and least-squares curve-fitting is commonly used for spectrum analysis. However, a major issue with these analyses is that the number of spectral components and other analytical conditions often include qualitative or arbitrary settings. In this work, we applied Bayesian estimation to the spectral data of the oxidized state of silicon (Si) surfaces. Bayesian estimation discussed in this paper is based on stochastic modelling without incorporating physical properties such as Si oxidation. By applying our method to the time-dependent oxidation spectra of Si surfaces, we have succeeded to detect the shift of peak position in the initial oxidation of Si surface, which could not be traced by the conventional method.

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• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International
  

Keyword: Bayesian estimation, X-ray photoelectron spectroscopy, Statistical analysis, Silicon surface oxidation

Date published: 2024-12-03

Publisher: Elsevier BV

Journal:

• Applied Surface Science (ISSN: 01694332) vol. 685 162001

Funding:

• Japan Society for the Promotion of Science JP20K05338
• Japan Society for the Promotion of Science JP26420289
• Japan Society for the Promotion of Science JP23K04578

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

MDR DOI:

First published URL: https://doi.org/10.1016/j.apsusc.2024.162001

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Updated at: 2025-01-21 12:30:34 +0900

Published on MDR: 2025-01-21 12:30:34 +0900