张俊|博士后

       jzhang@gbu.edu.cn

             2013-2017，安徽建筑大学，应用化学，学士

     2017-2020，华东理工大学，化学工程，硕士                                            

             2020-2024，香港城市大学，机械工程，博士

科研领域

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      张俊，博士毕业于香港城市大学，获得计算材料学博士学位，现为大湾区大学（筹）智能计算中心博士后工作。主要研究方向：多相催化、高熵材料、机器学习、密度泛函理论、分子动力学、蒙特卡洛方法等。在Joule、Nature Communications、Acta Materialia、Nature Materials、Advanced Materials、Advanced Functional Materials、npj Computational Materials等期刊发表学术论文多篇，取得中国和美国专利各1项。

   

      个人简历：https://jzhang-github.github.io/

工作经历

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• 2024.08-至今，大湾区大学（筹），博士后

主要成果

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1. Jun, Z. Rational Design of Multi-Component Materials via Ab-Initio Calculations and Machine Learning, City University of Hong Kong, Hong Kong, 2024. https://scholars.cityu.edu.hk/en/theses/rational-design-of-multicomponent-materials-via-abinitio-calculations-and-machine-learning(ebd6821e-6935-4034-ace8-35a3f322b3fa).html.
2. Zhang, J.; He, L.; Xiong, Y.; Huang, S.; Xu, B.; Ma, S.; Xiang, X.; Fu, H.; Kai, J.; Wu, Z.; Zhao, S. Local-Distortion-Informed Exceptional Multicomponent Transition-Metal Carbides Uncovered by Machine Learning. npj Comput. Mater. 2024, 10 (1), 1–10. https://doi.org/10.1038/s41524-024-01351-1.
3. Zhang, J.; Xiang, X.; Xu, B.; Huang, S.; Xiong, Y.; Ma, S.; Fu, H.; Ma, Y.; Chen, H.; Wu, Z.; Zhao, S. Rational Design of High-Entropy Ceramics Based on Machine Learning – A Critical Review. Curr. Opin. Solid State Mater. Sci. 2023, 27 (2), 101057. https://doi.org/10.1016/j.cossms.2023.101057.
4. Zhang, J.; Wang, C.; Huang, S.; Xiang, X.; Xiong, Y.; Xu, B.; Ma, S.; Fu, H.; Kai, J.; Kang, X.; Zhao, S. Design High-Entropy Electrocatalyst via Interpretable Deep Graph Attention Learning. Joule 2023, 7, 1–20. https://doi.org/10.1016/j.joule.2023.06.003.
5. Zhang, J.; Xu, B.; Xiong, Y.; Ma, S.; Wang, Z.; Wu, Z.; Zhao, S. Design High-Entropy Carbide Ceramics from Machine Learning. npj Comput. Mater. 2022, 8 (1), 5. https://doi.org/10.1038/s41524-021-00678-3.
6. Zhang, J.; Zhou, R. J.; Chang, Q. Y.; Sui, Z. J.; Zhou, X. G.; Chen, D.; Zhu, Y. A. Tailoring Catalytic Properties of V2O3 to Propane Dehydrogenation through Single-Atom Doping: A DFT Study. Catal. Today 2020, 368, 46–57. https://doi.org/10.1016/j.cattod.2020.02.023.

开源项目

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1. AGAT: Atomic Graph ATtention networks: https://github.com/jzhang-github/AGAT
2. Elastic net:https://github.com/jzhang-github/elasticnet
3. HECC_phase_prediction:https://github.com/jzhang-github/HECC_phase_prediction
4. VoronoiAnalyse: https://github.com/jzhang-github/VoronoiAnalyse