# Sample structure prediction from measured XPS data using Bayesian estimation and SESSA simulator

https://mdr.nims.go.jp/datasets/3eb80d14-f125-4e6e-8be6-bce4da3da307

## File

- [Shinotsuka2023_JES267_147370.pdf](https://mdr.nims.go.jp/filesets/869c4146-c409-4242-8eaa-aed5dadc697c/download) ([Detail](https://mdr.nims.go.jp/filesets/869c4146-c409-4242-8eaa-aed5dadc697c.md))

## Id

3eb80d14-f125-4e6e-8be6-bce4da3da307

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2023-08-23T04:34:14.401158Z

## Updated at

2024-01-05T13:11:57.062771Z

## Published at

2023-08-25T04:30:16.423383Z

## Doi



## First published url

https://doi.org/10.1016/j.elspec.2023.147370

## Date published

2023-07-06

## Recorded date published

2023-8

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Sample structure prediction from measured XPS data using Bayesian estimation
    and SESSA simulator
  title_type: original
  lang: en

## Description

- description: We have developed a framework for solving the inverse problem of X-ray
    photoelectron spectroscopy (XPS) by incorporating an XPS simulator, Simulation
    of Electron Spectra for Surface Analysis (SESSA), into Bayesian estimation to
    obtain an overall picture of the distribution of plausible sample structures from
    the measured XPS data. The Bayesian estimation framework automated the very tedious
    task of adjusting the sample structure parameters manually in the simulator. As
    an example, we performed virtual experiments of angle-resolved XPS on a four-layered
    sample, and we estimated the sample structures based on the XPS intensity data
    obtained from experiments. We succeeded in not only obtaining an optimal solution,
    but also visualizing the distribution of the solution through the Bayesian posterior
    probability distribution.
  description_type: abstract
  lang: eng

## Creator

- name: Hiroshi Shinotsuka
  role: author
  orcid: https://orcid.org/0000-0001-5147-1396
  organization: National Institute for Materials Science
  department: Research and Services Division of Materials Data and Integrated System
  ror: https://ror.org/026v1ze26
- name: Kenji Nagata
  role: author
  orcid: https://orcid.org/0000-0001-9894-4461
  organization: National Institute for Materials Science
  department: Research and Services Division of Materials Data and Integrated System
  ror: https://ror.org/026v1ze26
- name: Malinda Siriwardana
  role: author
  organization: National Institute for Materials Science
  department: Research and Services Division of Materials Data and Integrated System
  ror: https://ror.org/026v1ze26
- name: Hideki Yoshikawa
  role: author
  orcid: https://orcid.org/0000-0002-7389-8865
  organization: National Institute for Materials Science
  department: Research and Services Division of Materials Data and Integrated System
  ror: https://ror.org/026v1ze26
- name: Hayaru Shouno
  role: author
  orcid: https://orcid.org/0000-0002-2412-0184
  organization: The University of Electro-Communications
  department: Graduate School of Informatics and Engineering
- name: Masato Okada
  role: author
  orcid: https://orcid.org/0000-0002-9040-8784
  organization: The University of Tokyo
  department: Graduate School of Frontier Science

## Contact agent



## Publisher

organization: Elsevier BV

## Managing organization



## Keyword

- subject: X-ray photoelectron spectroscopy
  schema: not_defined
- subject: Bayesian estimation
  schema: not_defined
- subject: Exchange Monte Carlo method
  schema: not_defined
- subject: SESSA
  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: JOURNAL OF ELECTRON SPECTROSCOPY AND RELATED PHENOMENA
  issn: '03682048'
  volume: '267'
  article_number: '147370'

## Conference



## Related item



## Funding

- identifier: JPMJCR1761
  funder_name: JST CREST
- identifier: 19K12154
  funder_name: JSPS KAKENHI

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



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## Process for specimen treatment



## Computational method



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## Fileset

- id: 869c4146-c409-4242-8eaa-aed5dadc697c
  filename: Shinotsuka2023_JES267_147370.pdf
  content_type: application/pdf
  size: 1952556
  md5: 64b0e388fff59b939a3fc8e3319310e8

## Thumbnail

fileset_id: 869c4146-c409-4242-8eaa-aed5dadc697c
filename: Shinotsuka2023_JES267_147370.pdf