# High-throughput evaluation of hardness dependence on composition and temperature in Ni–Co binary alloy systems

https://mdr.nims.go.jp/datasets/35c6ef91-dd9f-4bb4-93d8-17a6239c0a8b

## File

- [1-s2.0-S0925838825054295-main.pdf](https://mdr.nims.go.jp/filesets/dd7ad3fa-cb5c-4a80-9bc6-47b98fef7196/download) ([Detail](https://mdr.nims.go.jp/filesets/dd7ad3fa-cb5c-4a80-9bc6-47b98fef7196.md))

## Id

35c6ef91-dd9f-4bb4-93d8-17a6239c0a8b

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2025-10-06T00:54:29.743176Z

## Updated at

2025-10-06T07:30:29.825570Z

## Published at

2025-10-06T07:21:49.751674Z

## Doi



## First published url

https://doi.org/10.1016/j.jallcom.2025.183868

## Date published

2025-09-18

## Recorded date published

2025-10

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: High-throughput evaluation of hardness dependence on composition and temperature
    in Ni–Co binary alloy systems
  title_type: original
  lang: en

## Description

- description: To accelerate the design of multicomponent alloys, it is of key importance
    predicting required properties and identifying specific compositions from numerous
    element combinations. Prediction techniques, including theoretical strengthening
    models, numerical simulations, and machine learning approaches, offer promising
    avenues for accelerating alloy development. However, achieving high-precision
    predictions requires large experimental composition–process–structure–property
    (CPSP) datasets, which demand significant time and effort to acquire. This study
    introduces a high-throughput evaluation approach for generating composition–process–structure–high-temperature
    property datasets by combining diffusion couples with high-temperature nanoindentation.
    Applied to a Ni–Co binary alloy system containing face-centered cubic (fcc) and
    hexagonal close-packed (hcp) phases, this approach efficiently obtains 1144 data
    points, capturing the hardness across temperatures from 300 to 773 K and Co concentrations
    from 2 to 98 at%. These datasets facilitate data-driven analyses of empirical
    formulas for solid-solution strengthening.
  description_type: abstract
  lang: und

## Creator

- name: Mayu Asano
  role: author
- name: Toshio Osada
  role: author
  orcid: https://orcid.org/0000-0003-1539-9264
- name: Ayako Ikeda
  role: author
  orcid: https://orcid.org/0000-0002-1705-9004
- name: Taichi Abe
  role: author
  orcid: https://orcid.org/0000-0002-5065-0939
- name: Thomas Hoefler
  role: author
  orcid: https://orcid.org/0000-0003-0650-179X
- name: Eri Nakagawa
  role: author
  orcid: https://orcid.org/0000-0002-8784-0138
- name: Takahito Ohmura
  role: author
  orcid: https://orcid.org/0000-0001-7528-566X

## Contact agent



## Publisher

organization: Elsevier BV

## Managing organization



## Keyword

- subject: Hardness
  schema: not_defined
- subject: Nanoindentation
  schema: not_defined
- subject: Diffusion couple
  schema: not_defined
- subject: NI-Co alloy
  schema: not_defined
- subject: High-throughput investigation
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: Journal of Alloys and Compounds
  issn: '09258388'
  volume: '1042'
  article_number: '183868'

## Conference



## Related item



## Funding

- identifier: JPJ004596
  funder_name: 防衛装備庁
  description: 安全保障技術推進制度

## 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: dd7ad3fa-cb5c-4a80-9bc6-47b98fef7196
  filename: 1-s2.0-S0925838825054295-main.pdf
  content_type: application/pdf
  size: 4599579
  md5: cac11105b7a76b292026eef7052d3b03

## Thumbnail

fileset_id: dd7ad3fa-cb5c-4a80-9bc6-47b98fef7196
filename: 1-s2.0-S0925838825054295-main.pdf