Deep Learning-Based Hardness Prediction of Novel Refractory High-Entropy Alloys with Experimental Validation

Deep Learning-Based Hardness Prediction of Novel Refractory High-Entropy Alloys with Experimental Validation

Hardness is an essential property in the design of refractory high entropy alloys (RHEAs). This study shows how a neural network (NN) model can be used to predict the hardness of a RHEA, for the first time. We predicted the hardness of several alloys, including the novel C<sub>0.1</sub>C...

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Bibliographic Details
Main Authors: Uttam Bhandari, Congyan Zhang, Congyuan Zeng, Shengmin Guo, Aashish Adhikari, Shizhong Yang
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Crystals
Subjects:
high entropy alloys
neural networks
hardness-prediction
microstructure
Online Access:https://www.mdpi.com/2073-4352/11/1/46

Internet

https://www.mdpi.com/2073-4352/11/1/46

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