# Bayesian estimation analysis of X-ray photoelectron spectra: Application to Si 2p spectrum analysis of oxidized silicon surfaces

https://mdr.nims.go.jp/datasets/e499c38b-8d63-40b0-ad81-b7f412a87073

## File

- [Shinotsuka2024_ApplSurfSci685_162001.pdf](https://mdr.nims.go.jp/filesets/863ebfc0-aa6d-4604-9f19-79d681467cf5/download) ([Detail](https://mdr.nims.go.jp/filesets/863ebfc0-aa6d-4604-9f19-79d681467cf5.md))

## Id

e499c38b-8d63-40b0-ad81-b7f412a87073

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-12-25T05:58:50.495246Z

## Updated at

2025-01-21T03:30:34.263019Z

## Published at

2025-01-21T03:30:34.347868Z

## Doi



## First published url

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

## Date published

2024-12-03

## Recorded date published

2025-3

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: 'Bayesian estimation analysis of X-ray photoelectron spectra: Application
    to Si 2p spectrum analysis of oxidized silicon surfaces'
  title_type: original
  lang: en

## Description

- 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.
  description_type: abstract
  lang: und

## Creator

- name: Hiroshi Shinotsuka
  role: author
  orcid: https://orcid.org/0000-0001-5147-1396
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Kenji Nagata
  role: author
  orcid: https://orcid.org/0000-0001-9894-4461
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Hideki Yoshikawa
  role: author
  orcid: https://orcid.org/0000-0002-7389-8865
  organization: National Institute for Materials Science
  ror: https://ror.org/026v1ze26
- name: Shuichi Ogawa
  role: author
- name: Akitaka Yoshigoe
  role: author

## Contact agent



## Publisher

organization: Elsevier BV

## Managing organization



## Keyword

- subject: Bayesian estimation
  schema: not_defined
- subject: X-ray photoelectron spectroscopy
  schema: not_defined
- subject: Statistical analysis
  schema: not_defined
- subject: Silicon surface oxidation
  schema: not_defined

## Rights

- identifier: https://creativecommons.org/licenses/by-nc-nd/4.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Applied Surface Science
  issn: '01694332'
  volume: '685'
  article_number: '162001'

## Conference



## Related item



## Funding

- identifier: JP20K05338
  funder_name: Japan Society for the Promotion of Science
- identifier: JP26420289
  funder_name: Japan Society for the Promotion of Science
- identifier: JP23K04578
  funder_name: Japan Society for the Promotion of Science

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



## Specific property for specimen



## Process for specimen treatment



## Computational method



## Energy level/transition state



## Software



## Custom property



## Fileset

- id: 863ebfc0-aa6d-4604-9f19-79d681467cf5
  filename: Shinotsuka2024_ApplSurfSci685_162001.pdf
  content_type: application/pdf
  size: 3522529
  md5: 7da4592fede5cd48edf8b3334fe6c341

## Thumbnail

fileset_id: 863ebfc0-aa6d-4604-9f19-79d681467cf5
filename: Shinotsuka2024_ApplSurfSci685_162001.pdf