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.