# Alloys innovation through machine learning: a statistical literature review

https://mdr.nims.go.jp/datasets/cd0fe17f-7315-40dc-a996-cbed715e961a

## File

- [STAMMethods4(2024)2326305.pdf](https://mdr.nims.go.jp/filesets/4078f9e8-aae5-41d2-badb-80b989035bd0/download) ([Detail](https://mdr.nims.go.jp/filesets/4078f9e8-aae5-41d2-badb-80b989035bd0.md))

## Id

cd0fe17f-7315-40dc-a996-cbed715e961a

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-06-24T10:31:20.665569Z

## Updated at

2024-06-25T03:30:16.907701Z

## Published at

2024-06-25T03:30:16.979428Z

## Doi



## First published url

https://doi.org/10.1080/27660400.2024.2326305

## Date published

2024-12-31

## Recorded date published

2024-12-31

## Resource type

journal_article

## Manuscript type

vor

## Collection



## Title

- title: 'Alloys innovation through machine learning: a statistical literature review'
  title_type: original
  lang: en

## Description

- description: "This review systematically analyzes over 200 publications to explore
    the growing role of data-driven methods and their potential benefits in accelerating
    alloy development. The review presents a comprehensive overview of different aspects
    of alloy innovation by machine learning and other computational approaches used
    in recent years. \r\nThese methods harness the power of advanced simulation techniques
    and data analytics to expedite materials’ discovery, predict properties, and optimize
    performance. \r\nThrough analysis, significant trends and disparities within the
    data discerned, while highlighting previously overlooked research gaps, thus underscoring
    areas that require further exploration. \r\n"
  description_type: abstract
  lang: und

## Creator

- name: Alireza Valizadeh
  role: author
- name: Ryoji Sahara
  role: author
  orcid: https://orcid.org/0000-0003-0788-2985
  organization: National Institute for Materials Science
- name: Maaouia Souissi
  role: author

## Contact agent



## Publisher

organization: Informa UK Limited

## Managing organization



## Keyword

- subject: Alloy development
  schema: not_defined
- subject: machine learning
  schema: not_defined
- subject: data-driven research
  schema: not_defined
- subject: materials informatics
  schema: not_defined
- subject: Materials Genome Initiative
  schema: not_defined
- subject: Materials databases
  schema: not_defined

## Rights

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

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo



## Journal

- title: 'Science and Technology of Advanced Materials: Methods'
  issn: '27660400'
  volume: '4'
  issue: '1'
  article_number: '2326305'

## Conference



## Related item



## Funding

- identifier: D3090

## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



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## Fileset

- id: 4078f9e8-aae5-41d2-badb-80b989035bd0
  filename: STAMMethods4(2024)2326305.pdf
  content_type: application/pdf
  size: 20583182
  md5: 703f44caec92b315b561969e11fec16a

## Thumbnail

fileset_id: 4078f9e8-aae5-41d2-badb-80b989035bd0
filename: STAMMethods4(2024)2326305.pdf