Machine learning-driven insights into phase prediction for high entropy alloys

Machine learning-driven insights into phase prediction for high entropy alloys

The unique properties of high-entropy alloys (HEAs) have attracted considerable attention, largely due to their dependence on the choice among three distinct phases: solid solution (SS), intermetallic compound (IM), or a blend of both (SS + IM). For this reason, precise phase prediction is key to id...

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Bibliographic Details
Main Authors: Reliance Jain, Sandeep Jain, Sheetal Kumar Dewangan, Lokesh Kumar Boriwal, Sumanta Samal
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Journal of Alloys and Metallurgical Systems
Subjects:
High entropy alloys
Phase prediction
Machine learning. Model validation
New alloy design
Online Access:http://www.sciencedirect.com/science/article/pii/S2949917824000579
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