Machine learning-enabled prediction and optimization of hardness for Nb-Ti-V-Zr refractory high entropy alloy-Reference-Cited by-同舟云学术

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Machine learning-enabled prediction and optimization of hardness for Nb-Ti-V-Zr refractory high entropy alloy

Published:2024-08 Issue: Volume:40 Page:109607
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Hosseini Seyedmehrab^ORCID,Vaghefi Ehsan,Lee Chanho,Prorok Bart^ORCID,Mirkoohi Elham

Publisher

Elsevier BV

Reference65 articles.

1. A review on fundamental of high entropy alloys with promising high–temperature properties;Chen;J. Alloys Compd.,2018

2. High-entropy alloys in hexagonal close-packed structure;Gao;Metall. Mater. Trans. A,2016

3. Metastable high-entropy dual-phase alloys overcome the strength–ductility trade-off;Li;Nature,2016

4. Exceptional damage-tolerance of a medium-entropy alloy CrCoNi at cryogenic temperatures;Gludovatz;Nat. Commun.,2016

5. Nanoscale serration and creep characteristics of Al0. 5CoCrCuFeNi high-entropy alloys;Chen;J. Alloys Compd.,2018

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