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Machine learning superalloy microchemistry and creep strength from physical descriptors

Published version
Peer-reviewed

Repository URI

https://www.repository.cam.ac.uk/handle/1810/350299

Repository DOI

Files

Published version (2.12 MB)

Type

Article

Change log

Authors

Conduit, G 

Description

Keywords

40 Engineering, 4016 Materials Engineering, Machine Learning and Artificial Intelligence

Journal Title

Computational Materials Science

Conference Name

Journal ISSN

0927-0256

Volume Title

227

Publisher

Elsevier BV

Publisher DOI

https://doi.org/10.1016/j.commatsci.2023.112265

Rights

Attribution 4.0 International Repository logo
Sponsorship
Engineering and Physical Sciences Research Council (2485285)
Relationships
Is supplemented by:
https://doi.org/10.17863/CAM.92063

Collections

University of Cambridge Research Outputs (Articles and Conferences)