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説明:

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.

権利情報:

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

キーワード: Bayesian estimation, X-ray photoelectron spectroscopy, Statistical analysis, Silicon surface oxidation

刊行年月日: 2024-12-03

出版者: Elsevier BV

掲載誌:

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

研究助成金:

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

原稿種別: 出版者版 (Version of record)

MDR DOI:

公開URL: https://doi.org/10.1016/j.apsusc.2024.162001

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更新時刻: 2025-01-21 12:30:34 +0900

MDRでの公開時刻: 2025-01-21 12:30:34 +0900