Deep learning-based phase prediction of high-entropy alloys: Optimization, generation, and explanation

Deep learning-based phase prediction of high-entropy alloys: Optimization, generation, and explanation

Identifying phase information of high-entropy alloys (HEAs) can be helpful as it provides useful information such as anticipated mechanical properties. Recently, machine learning methods are attracting interest to predict phases of HEAs, which could reduce the effort for designing new HEAs. As resea...

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Bibliographic Details
Main Authors: Soo Young Lee, Seokyeong Byeon, Hyoung Seop Kim, Hyungyu Jin, Seungchul Lee
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Materials & Design
Subjects:
High-entropy alloys
Phase prediction
Deep learning
Deep neural networks
Bayesian optimization
Conditional generative adversarial networks
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127520307954

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http://www.sciencedirect.com/science/article/pii/S0264127520307954

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