Machine learning assisted prediction of the Young’s modulus of compositionally complex alloys

We identify compositionally complex alloys (CCAs) that offer exceptional mechanical properties for elevated temperature applications by employing machine learning (ML) in conjunction with rapid synthesis and testing of alloys for validation to accelerate alloy design. The advantages of this approach...

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Detalles Bibliográficos
Autores principales: Khakurel, Hrishabh, Taufique, M. F. N., Roy, Ankit, Balasubramanian, Ganesh, Ouyang, Gaoyuan, Cui, Jun, Johnson, Duane D., Devanathan, Ram
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8387451/
https://www.ncbi.nlm.nih.gov/pubmed/34433841
http://dx.doi.org/10.1038/s41598-021-96507-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8387451/
https://www.ncbi.nlm.nih.gov/pubmed/34433841
http://dx.doi.org/10.1038/s41598-021-96507-0

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