(For a full list of publications see below or go to Google Scholar, ResearcherID)
We develop machine learning techniques to predict the single-phase formation ability of high-entropy carbide ceramics materials. The predictions are validated by experiments.
Jun Zhang, Biao Xu, Yaoxu Xiong, Shihua Ma, Zhe Wang, Zhenggang Wu, Shijun Zhao
npj Computational Materials, 8, 1 (2022)
This is a Mini Review paper in the Risinig Stars in JNM special issue. In this publication, we review the applications of machine learning techniqiues in the field of radiation damage specifically for high-entropy materials.
Shijun Zhao
Journal of Nuclear Materials 559, 153462 (2022)
Shijun Zhao, Yanwen Zhang, William J Weber
High Entropy Alloys: Irradiation
Reference Module in Materials Science and Materials Engineering
Elsevier 2020
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