运用多尺度模拟与人工智能技术，并结合高通量计算和数据库系统，通过构建“物理仿真+数据驱动”的混合模型，实现材料成分和结构的精准预测以及工艺参数优化，提高材料性能和制备效率，催动传统材料研发从“经验驱动”向“智能驱动”转型。
本研究方向“十四五”期间代表性成果有：
1、C. J. Peng, X. G. Yao, X. Y. Miao, S. W. Chen, Q. F. Lu, X. J. Han*, D. Shi,Y. L. Shao, Y. Z. Wu and X. P. Hao*. Optimization of the process parameters for the AlN crystal growth in the PVT method through an improved numerical simulation considering partial pressure of gas phases. CrystEngComm, 2024.
2、Xiaoyu Miao1, Shunwei Chen1, Cunjin Peng, Qiulin Bi, Jialiang Liu, Xiujun Han*. Enyan Guo, Mingzhi Wei, Conghui Si, Qifang Lu*, Self-supported Ni–Co–Fe ternary metal phosphide for highly efficient oxygen evolution reaction: DFT and experimental insights. International Journal of Hydrogen Energy, 2024.
3、Shunwei Chen*, Huajing Zhang, Yi Li, Tingfeng Chen, Hao Liu and Xiujun Han*. Revealing and Tuning the Photophysics of C=N Containing Photothermal Molecules: Excited State Dynamics Simulations. International Journal of Molecular Sciences, 2022.
4、Kaiming Cheng*, Yan Zheng, Jiaxing Sun, Yafei Zhao, Jin Wang, Huan Yu,Dongqing Zhao, Hang Li, Jixue Zhou*, Zhenyu Ma, Junmin Wang, Cuiping Guo,Xitao Wang, Lijun Zhang, Yong Du. Investigation on the temperature-dependent diffusion growth of intermetallic compounds in the Mg-Al-Zn system: Experiment and modeling. Journal of Magnesium and Alloys, 2024.
5、Kaiming Cheng, Huixia Xu, Lijun Zhang, Jixue Zhou*, Xitao Wang, Yong Du,Ming Chen. Computational engineering of the oxygen electrode-electrolyte interface in solid oxide fuel cells. npj Computational Materials, 2021.
6、Qiulin Bi, Jialiang Liu, Junting Li, Hanmei Chen, Shunwei Chen*, Xiujun Han*. Predicting the magnetic properties of Fe-based bulk metallic glasses by ensemble machine learning and interpretable information. Journal of Alloys and Compounds, 2025.
