# Rapid, comprehensive search of crystalline phases from X-ray diffraction in seconds via GPU-accelerated Bayesian variational inference

https://mdr.nims.go.jp/datasets/64573b9f-708f-425c-a31d-a9891444c16c

## File

- [Rapid  comprehensive search of crystalline phases from X-ray diffraction in seconds via GPU-accelerated Bayesian variational inference.pdf](https://mdr.nims.go.jp/filesets/2f4ec8ae-bdeb-4b05-a386-6d8047d95c16/download) ([Detail](https://mdr.nims.go.jp/filesets/2f4ec8ae-bdeb-4b05-a386-6d8047d95c16.md))

## Id

64573b9f-708f-425c-a31d-a9891444c16c

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2025-07-25T06:33:20.521584Z

## Updated at

2025-07-25T23:30:18.679215Z

## Published at

2025-07-25T23:16:42.978219Z

## Doi



## First published url

https://doi.org/10.1080/27660400.2025.2485016

## Date published

2025-12-31

## Recorded date published

2025-12-31

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Rapid, comprehensive search of crystalline phases from X-ray diffraction
    in seconds via GPU-accelerated Bayesian variational inference
  title_type: original
  lang: en

## Description

- description: In analysis of X-ray diffraction data, identifying the crystalline
    phase is important for interpreting the material. The typical method is identifying
    the crystalline phase from the coincidence of the main diffraction peaks. This
    method identifies crystalline phases by matching them as individual crystalline
    phases rather than as combinations of crystalline phases, in the same way as the
    greedy method. If multiple candidates are obtained, the researcher must subjectively
    select the crystalline phases. Thus, the identification results depend on the
    researcher's experience and knowledge of materials science. To solve this problem,
    we have developed a Bayesian estimation method to identify the combination of
    crystalline phases, taking the entire profile into account. This method estimates
    the Bayesian posterior probability of crystalline phase combinations by performing
    an approximate exhaustive search of all possible combinations. It is a method
    for identifying crystalline phases that takes into account all peak shapes and
    phase combinations. However, it takes a few hours to obtain the analysis results.
    The aim of this study is to develop a Bayesian method for crystalline phase identification
    that can provide results in seconds, which is a practical calculation time. We
    introduce variational sparse estimation and GPU computing. Our method is able
    to provide results within 10 seconds even when analysing 250 candidate crystalline
    phase combinations. Furthermore, the crystalline phases identified by our method
    are consistent with the results of previous studies that used a high-precision
    algorithm.
  description_type: abstract
  lang: und

## Creator

- name: Ryo Murakami
  role: author
  orcid: https://orcid.org/0000-0001-8585-9268
  organization: National Institute for Materials Science
- name: Kenji Nagata
  role: author
  orcid: https://orcid.org/0000-0001-9894-4461
  organization: National Institute for Materials Science
- name: Yoshitaka Matsushita
  role: author
  orcid: https://orcid.org/0000-0002-4968-8905
  organization: National Institute for Materials Science
- name: Masahiko Demura
  role: author
  orcid: https://orcid.org/0000-0002-7308-3041
  organization: National Institute for Materials Science

## Contact agent



## Publisher

organization: Informa UK Limited

## Managing organization



## Keyword

- subject: X-ray diffraction
  schema: not_defined
- subject: GPU computing
  schema: not_defined
- subject: sparse modeling
  schema: not_defined
- subject: bayesian inference
  schema: not_defined
- subject: model selection
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS-METHODS
  issn: '27660400'
  volume: '5'
  issue: '1'
  article_number: '2485016'

## Conference



## Related item



## Funding

- identifier: JPMJGX23S6
  funder_name: JST
  description: GteX Program Japan

## Instrument



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## Measurement method



## Specimen



## Chemical composition



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## Specific property for specimen



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## Fileset

- id: 2f4ec8ae-bdeb-4b05-a386-6d8047d95c16
  filename: Rapid  comprehensive search of crystalline phases from X-ray diffraction
    in seconds via GPU-accelerated Bayesian variational inference.pdf
  content_type: application/pdf
  size: 3806359
  md5: e43d027d80540fe2790c27c95ab29eb2

## Thumbnail

fileset_id: 2f4ec8ae-bdeb-4b05-a386-6d8047d95c16
filename: Rapid  comprehensive search of crystalline phases from X-ray diffraction
  in seconds via GPU-accelerated Bayesian variational inference.pdf