Machine learning assisted design of high entropy alloys with desired property

We formulate a materials design strategy combining a machine learning (ML) surrogate model with experimental design algorithms to search for high entropy alloys (HEAs) with large hardness in a model Al-Co-Cr-Cu-Fe-Ni system. We fabricated several alloys with hardness 10% higher than the best value i...

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Bibliographic Details

Published in:	Acta materialia Vol. 170; no. C; pp. 109 - 117
Main Authors:	Wen, Cheng, Zhang, Yan, Wang, Changxin, Xue, Dezhen, Bai, Yang, Antonov, Stoichko, Dai, Lanhong, Lookman, Turab, Su, Yanjing
Format:	Journal Article
Language:	English
Published:	United States Elsevier Ltd 15.05.2019 Elsevier
Subjects:	Active learning Machine learning Materials genome initiative Multi-principal element alloys Materials genome initiative Multi-principal element alloys Active learning Machine learning
ISSN:	1359-6454, 1873-2453
Online Access:	Get full text
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