# Construction of Machine Learning Potentials toward the Exploration of Alloy Cluster Catalysts

https://mdr.nims.go.jp/datasets/6195c927-0e0a-43b1-a18f-f505626a81be

## File

- [Miyamoto_2025.pdf](https://mdr.nims.go.jp/filesets/5903f162-c536-4622-b3ed-4c3a73328cf7/download) ([Detail](https://mdr.nims.go.jp/filesets/5903f162-c536-4622-b3ed-4c3a73328cf7.md))

## Id

6195c927-0e0a-43b1-a18f-f505626a81be

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2026-04-16T03:44:13.191462Z

## Updated at

2026-05-18T06:04:41.265171Z

## Published at

2026-05-18T07:23:12.764003Z

## Doi



## First published url

https://doi.org/10.1380/ejssnt.2025-028

## Date published

2025-05-17

## Recorded date published

2025

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: Construction of Machine Learning Potentials toward the Exploration of Alloy
    Cluster Catalysts
  title_type: original
  lang: en

## Description

- description: High entropy alloys (HEAs) are expected to show excellent performance
    in various fields, such as catalysts and high-temperature structural materials,
    but the huge number of configurations makes it difficult to find the optimal compositions
    for HEAs. In this study, machine learning potentials were developed to accurately
    predict the total and H/CO adsorption energies of multi-element slab models and
    cluster models of various sizes and shapes, based on density functional theory
    calculations.
  description_type: abstract
  lang: und

## Creator

- name: Kentaro Miyamoto
  role: author
- name: Koji Shimizu
  role: author
- name: Anh Khoa Augustin Lu
  role: author
  orcid: https://orcid.org/0000-0003-4702-0933
  organization: National Institute for Materials Science
- name: Satoshi Watanabe
  role: author

## Contact agent



## Publisher

organization: Surface Science Society Japan

## Managing organization



## Keyword

- subject: High entropy alloys
  schema: not_defined
- subject: " Machine learning"
  schema: not_defined
- subject: Density functional theory
  schema: not_defined
- subject: Catalysts
  schema: not_defined
- subject: CO2 reduction reaction
  schema: not_defined

## Rights

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

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## Journal

- title: e-Journal of Surface Science and Nanotechnology
  issn: '13480391'
  volume: '23'
  issue: '2'
  start_page: 188
  end_page: 192
  article_number: 2025-028

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## Related item



## Funding

- identifier: " JPMJSC21E2"
  funder_name: " Japan Science and Technology Agency (JST)"
  description: 触媒・電池応用に向けたハイエントロピー合金材料の理論的設計

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## Specimen



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## Fileset

- id: 5903f162-c536-4622-b3ed-4c3a73328cf7
  filename: Miyamoto_2025.pdf
  content_type: application/pdf
  size: 1966490
  md5: 1a1421eb5d2295aaf7a4863a71825600

## Thumbnail

fileset_id: 5903f162-c536-4622-b3ed-4c3a73328cf7
filename: Miyamoto_2025.pdf