Supervised machine learning for multi-principal element alloy structural design

Berry, J. orcid.org/0000-0001-7291-2306 and Christofidou, K.A. orcid.org/0000-0002-8064-5874 (2024) Supervised machine learning for multi-principal element alloy structural design. Materials Science and Technology. ISSN 0267-0836

Abstract

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Item Type: Article
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© 2024 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords: multi-principal element alloys; highen tropy alloys; complex concentrated alloys; compositionally complex alloys; machine learning; experimental data; alloy design
Dates:
  • Published: 16 August 2024
  • Published (online): 16 August 2024
  • Accepted: 2 July 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > School of Chemical, Materials and Biological Engineering
The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Materials Science and Engineering (Sheffield)
Funding Information:
Funder
Grant number
Engineering and Physical Sciences Research Council
EP/S022635/1
Depositing User: Symplectic Sheffield
Date Deposited: 11 Oct 2024 10:30
Last Modified: 11 Oct 2024 10:30
Published Version: http://dx.doi.org/10.1177/02670836241272086
Status: Published online
Publisher: SAGE Publications
Refereed: Yes
Identification Number: 10.1177/02670836241272086
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