精准智能化学全国重点实验室

主要研究方向与成果：

从事理论与智能化学研究，致力于推动人工智能、计算化学与材料创制的深度融合，发展面向材料“结构–谱学–性能”关联的智能建模方法，构建数据驱动的材料逆向设计与高效筛选体系。2025年入选国家海外优青项目，获2024年美国西北大学国际纳米技术研究所“杰出研究员奖”。已在 Science、JACS、EES 等国际顶尖期刊发表论文100余篇。30余项研究成果被ScienceDaily等国际主流科技媒体专题报道，并获《Science》编辑专文推荐。

代表性论文：

1. E. Xie, X. Wang*, J. I. Siepmann, H. Chen, R. Q. Snurr*, “Generative AI for Design of Nanoporous Materials: Review and Future Prospects”, Digit. Discov., 2025, 4, 2336-2363.
2. S. Wei, X. Hu, R. Yang, B. Liu, Q. Kang*, X. Wang*, Y. Hu*, “Catalytic Nano-Reactor Engineering of Metal Single-Atom Site and Metal-Free Chemical Group for Accelerating Sulfur Redox Electrocatalysis”, Angew. Chem. Int. Ed., 2025, e202517190.
3. X. Wang, K. Shi, A. Peng, R. Q. Snurr, “Computational Chemistry and Machine Learning-assisted Screening of Supported Amorphous Metal Oxide Nanoclusters for Methane Activation”, ACS Catal., 2024, 14, 18708-18721.
4. X. Wang, S. Jiang, W. Hu, S. Ye, T. Wang, F. Wu, L. Yang, X. Li, G. Zhang, X. Chen, J. Jiang, Y. Luo, “Quantitatively Determining Surface-Adsorbate Properties from Vibrational Spectroscopy with Interpretable Machine Learning”, J. Am. Chem. Soc., 2022, 144, 16069–16076.
5. X. Wang, Y.Gao, E. Krzystowczyk, S. Iftikhar, J. Dou, R. Cai, H. Wang, C. Ruan, S. Ye, F. Li, “High-Throughput Oxygen Chemical Potential Engineering of Perovskite Oxides for Chemical Looping Applications”, Energy Environ. Sci., 2022, 15, 1512-1528.