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Automated information compression of XPS spectrum using information criteria

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We developed and implemented a fully automated method to perform X-ray photoelectron spectroscopy (XPS) spectral analysis based on the active Shirley method and information criteria. Our method searches a large number of initial fitting models by changing the degree of smoothing, and then optimizes the peak parameters and background parameters to obtain a large number of fitting results. The goodness of those optimized models is ranked using information criteria. As a result of applying this algorithm to measured XPS spectra, we found that, using the Bayesian information criterion (BIC), a simple model with reasonably good agreement and a moderate number of peaks was selected. The model selected by the BIC was close to the result of peak fitting performed by XPS analysis experts.

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Creator
  • Name
    Shinotsuka, Hiroshi
    ORCID
    https://orcid.org/0000-0001-5147-1396
    Organization
    National Institute for Materials Science
    Sub organization
    Materials Data Analysis Group, Materials Data Platform Center, Research and Services Division of Materials Data and Integrated System
    Role
    author
    Name
    Yoshikawa, Hideki
    ORCID
    https://orcid.org/0000-0002-7389-8865
    Organization
    National Institute for Materials Science
    Sub organization
    Materials Data Analysis Group, Materials Data Platform Center, Research and Services Division of Materials Data and Integrated System
    Role
    author
    Name
    Murakami, Ryo
    Organization
    National Institute of Technology, Yonago College
    Sub organization
    Department of Electrical and Computer Engineering
    Role
    author
    Name
    Nakamura, Kazuki
    Organization
    National Institute of Technology, Yonago College
    Sub organization
    Department of Electrical and Computer Engineering
    Role
    author
    Name
    Tanaka, Hiromi
    Organization
    National Institute of Technology, Yonago College
    Sub organization
    Department of Electrical and Computer Engineering
    Role
    author
    Name
    Yoshihara, Kazuhiro
    Organization
    Scienta Omicron Inc.
    Role
    author
Keyword
Resource type
Publisher
Date published
  • 03/12/2019
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Manuscript type
  • Accepted manuscript
Language
Last modified
  • 17/06/2022
Other Date
  • Accepted
    30/10/2019
    Submitted
    17/06/2019

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