Phase formation prediction of high-entropy alloys: a deep learning study

Phase formation prediction of high-entropy alloys: a deep learning study

High-entropy alloys (HEAs) represent prospective applications considering their outstanding mechanical properties. The properties in HEAs can be affected by the phase structure. Artificial neural network (ANN) is a promising machine learning approach for predicting the phases of HEAs. In this work,...

Full description

Bibliographic Details
Main Authors: Wenhan Zhu, Wenyi Huo, Shiqi Wang, Xu Wang, Kai Ren, Shuyong Tan, Feng Fang, Zonghan Xie, Jianqing Jiang
Format: Article
Language:English
Published: Elsevier 2022-05-01
Series:Journal of Materials Research and Technology
Subjects:
High-entropy alloys
Phase formation
Deep neural network
Residual network
Online Access:http://www.sciencedirect.com/science/article/pii/S2238785422002514

Similar Items

Similar Items