cardiGAN: A generative adversarial network model for design and discovery of multi principal element alloys
Version 2 2024-06-02, 23:42
Version 1 2023-10-06, 02:58
journal contribution
posted on 2024-06-02, 23:42 authored by Z Li, WT Nash, SP O'Brien, Y Qiu, RK Gupta, Nick BirbilisNick BirbiliscardiGAN: A generative adversarial network model for design and discovery of multi principal element alloys
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Journal
Journal of Materials Science and TechnologyVolume
125Pagination
81-96Location
Amsterdam, The NetherlandsPublisher DOI
ISSN
1005-0302eISSN
1941-1162Language
engPublication classification
C1.1 Refereed article in a scholarly journalPublisher
ElsevierPublication URL
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Keywords
Alloy designDUCTILITYGenerative adversarial networkHigh entropy alloysHIGH ENTROPY ALLOYSMachine learningMaterials ScienceMaterials Science, MultidisciplinaryMetallurgy & Metallurgical EngineeringMulti-principal element alloyNeural networkPREDICTIONScience & TechnologySOLID-SOLUTION PHASESTABILITYSTRENGTHTechnology
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