# Automated system for high-throughput process-structure-property dataset generation of structural materials: A γ/γ′ superalloy case study

https://mdr.nims.go.jp/datasets/2d7edfe5-ea98-4e31-b05e-20596178a0d8

## File

- [1-s2.0-S0264127525006999-main.pdf](https://mdr.nims.go.jp/filesets/b37cceee-6771-4e3c-a7fa-5ae27836bc6f/download) ([Detail](https://mdr.nims.go.jp/filesets/b37cceee-6771-4e3c-a7fa-5ae27836bc6f.md))

## Id

2d7edfe5-ea98-4e31-b05e-20596178a0d8

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2025-06-30T07:49:38.338122Z

## Updated at

2025-07-01T03:30:19.633893Z

## Published at

2025-07-01T03:26:49.246669Z

## Doi



## First published url

https://doi.org/10.1016/j.matdes.2025.114279

## Date published

2025-06-20

## Recorded date published

2025-8

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: 'Automated system for high-throughput process-structure-property dataset
    generation of structural materials: A γ/γ′ superalloy case study'
  title_type: original
  lang: en

## Description

- description: We present an automated high-throughput method capable of gathering
    2400 data points relating processing conditions, microstructure geometry and yield
    strength in just 13 days. An estimated 200 times faster than conventional methods
    using tensile testing specimens, a complete Process-Structure-Property (P-S-P)
    dataset is created from a single sample. The method is demonstrated by example
    of the aging heat treatment process of a γ/γ′ superalloy. By aging the sample
    in a temperature gradient, a wide range of aging process temperatures is mapped
    over the sample length. Structure analysis consists of fully automated, nanometer-resolution
    FE-SEM scanning, with precipitate fraction, size and shape distributions determined
    by automatic image analysis using the Python programming language. Mechanical
    properties are evaluated by nanoindentation inverse analysis, an approach combining
    instrumented indentation data with pile-up analysis to calculate stress/strain
    curves. While the neces sary topographic data is typically acquired using atomic
    force microscopy, a significant speedup was achieved by automatic indent detection
    and scanning using Angular selective Backscatter FE-SEM analysis. As a method
    to rapidly assemble comprehensive and consistent P-S-P datasets, we expect it
    to facilitate efficient alloy design, given a vast majority of modeling approaches
    still heavily rely on empirical data.
  description_type: abstract
  lang: und

## Creator

- name: Thomas Hoefler
  role: author
  orcid: https://orcid.org/0000-0003-0650-179X
- name: Ayako Ikeda
  role: author
  orcid: https://orcid.org/0000-0002-1705-9004
- name: Toshio Osada
  role: author
  orcid: https://orcid.org/0000-0003-1539-9264
- name: Toru Hara
  role: author
  orcid: https://orcid.org/0000-0002-9715-6444
- name: Kyoko Kawagishi
  role: author
  orcid: https://orcid.org/0000-0001-7652-9232
- name: Takahito Ohmura
  role: author
  orcid: https://orcid.org/0000-0001-7528-566X

## Contact agent



## Publisher

organization: Elsevier BV

## Managing organization



## Keyword

- subject: high-throughput method
  schema: not_defined
- subject: Nanoindentation
  schema: not_defined
- subject: Image analysis
  schema: not_defined
- subject: γ/γ' superalloy
  schema: not_defined
- subject: Aging heat treatment
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin



## Embargo



## Journal

- title: Materials & Design
  issn: '02641275'
  volume: '256'
  article_number: '114279'

## Conference



## Related item



## Funding



## 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

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  filename: 1-s2.0-S0264127525006999-main.pdf
  content_type: application/pdf
  size: 10259923
  md5: fb3e5742efc600f800665ba77ff03ccd

## Thumbnail

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filename: 1-s2.0-S0264127525006999-main.pdf