Computational Materials Properties

We are a dynamic research group at the City University of Hong Kong. Our aim is to explore and understand materials properties using computational methods, especially at the electronic and atomic scales.

Our interest lies in structural materials, functional materials, and energy storage materials. To gain an overall understanding of their properties, we have developed different techniques to characterize their responses under different external conditions (see Research).

We are located at the Department of Mechanical Engineering, City University of Hong Kong.

We are looking for passionate new PhD students and Postdocs to join us (more info) !

We are grateful for funding from City University of Hong Kong, Research Grant Council of Hong Kong, and the National Natural Science Foundation of China.

News

2023.12.30

We have organized a special issue on Machine Learning for Advanced Design and Applications of High-Performance Ceramics in Jourmal of Materials Informatics. The submission deadline is 20 May 2024. Please consider submitting your manuscript on high-entropy ceramics!

2023.12.15

We have organized a special collection on Computational Progress of High Entropy Materials in the prestigious journal npj Computational Materials. The submission deadline is 07 July 2024. Please consider submitting your manuscript!

2023.09.01

We welcome new PhD students joining us in this new academic year, Miss LU Wenyu!

2023.07.03

We have developed an atomic graph attention network (AGAT) for high-precision machine learning. The model has been applied to predict high-performance high-entropy catalysts for oxygen reduction reaction (ORR). The prediction is successfully verified by experiments collaborated with Prof. Kang Xiongwu at the South China University of Technology. Please read the publication entitled Design high-entropy electrocatalyst via interpretable deep graph attention learning in the journal of JOULE .

2022.09.01

We welcome two new PhD students joining us in this new academic year, Mr FU Haijun and Miss XIANG Xuepeng!

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