汤富杰

发布日期:2026-07-23     浏览次数:次   

职称:教授
研究生指导资格:硕士生导师,博士生导师
办公室:思明校区曾呈奎楼B308室
E-mail:tangfujie@xmu.edu.cn
课题组网站:https://fujiepku.github.io/

个人简历:

教育经历:

2009.09-2013.07  学士     北京大学物理学院

2013.09-2018.07  博士     北京大学量子材料科学中心


博士后与访问经历:

2016.01–2016.09  访问学生   德国马克斯·普朗克学会高分子研究所

2018.10–2019.09  博士后    美国天普大学物理系

2019.06–2019.07  访问学者   美国加州大学伯克利分校物理系

2019.10–2023.09  联合博士后  美国普林斯顿大学–天普大学联合计算化学中心


任职经历:

2024.01–2025.12  副研究员   嘉庚创新实验室人工智能电化学联合实验室

2024.01–2025.12  副教授    厦门大学萨本栋微米纳米科学技术研究院

2025.12–2026.07  教授     厦门大学萨本栋微米纳米科学技术研究院

2025.12–至今    研究员    嘉庚创新实验室人工智能电化学联合实验室

2026.07–至今    教授     厦门大学化学化工学院/人工智能研究院


 

获得荣誉:

2025   国家高层次人才计划青年项目

2025   厦门大学“南强青年拔尖人才支持计划A类”

2025   厦门市高层次留学人员

2024   福建省第九批引才“百人计划”

2024   厦门大学“南强青年拔尖人才支持计划B类”

2018   Springer杰出博士论文奖

2018   北京大学优秀博士论文奖

2018   北京大学优秀毕业生

 

研究兴趣:

1. 面向复杂化学体系的理论与计算光谱学方法发展
发展振动光谱、激发态光谱、X射线散射谱和核磁共振谱等谱学计算方法,建立复杂化学体系“微观结构–动力学–谱学响应”的定量联系,实现实验谱学信号的机理解析与可预测模拟。

2. 面向复杂化学体系的第一性原理与机器学习原子模拟方法发展
发展电子结构、第一性原理分子动力学、路径积分分子动力学及机器学习原子间势方法,研究液相、界面与能源材料中的结构、动力学和核量子效应。

3. 复杂界面、能源化学与水科学研究
研究固–液与电化学界面、低维限域体系以及极端条件下水和冰中的氢键网络、电荷转移、激子效应与相变行为。

4. 人工智能赋能的谱学预测与反演研究
发展物理约束的谱学预测、跨模态谱–构学习与谱学反演方法,服务复杂界面和能源化学体系的结构识别与机理发现。


承担课题:

1.国家自然科学基金优秀青年科学基金项目(海外),2026.01-2028.12,项目负责人

2.国家自然科学基金面上项目,2026.01-2029.12,项目负责人

3.国家重点研发计划“催化科学”重点专项,2025.12-2030.11,子课题负责人

4.国家重点研发计划“纳米前沿”重点专项,2024.12-2029.11,子课题负责人

5.厦门市自然科学基金青年项目,2024.07-2027.06,项目负责人

 

近期主要代表论著:

  1. 1. Suyang Zhong#, Yuhao Zhao#, Boying Huang, Fanjie Xu, Pengwei Xu, Haoyi Tao, Xi Fang*, Jun Cheng*, Fujie Tang*. Uni-XAS: Alignment-Driven Bidirectional Multimodal Learning for X-ray Absorption Spectroscopy. 34th ACM International Conference on Multimedia (ACM MM), 2026. Accepted. (CCF-A) (corresponding author)

  2. 2. Mingyang Xia#, Xianglong Du#, Canbin Wang#, Jinguo Liu, Zhihua Zhou, Ying-Ru Qiu, Yao-Hui Wang, Fujie Tang*, Sheng Hu*. Ion-Disrupted Hydrogen-Bond Networks Enable Fast Water Transport under Two-Dimensional Confinement. Nat. Commun., 2026, DOI: 10.1038/s41467-026-75604-6. (corresponding author)

  3. 3. Xianglong Du, Jun Cheng*, Fujie Tang*. Machine-Learning Accelerated Computational Spectroscopy Reveals Vibrational Signature of the Oxidation Level of Graphene in Contact with Water. J. Phys. Chem. Lett., 2026, 17, 1471–1478. (corresponding author)

  4. 4. Kang Wang, Yingchen Peng, Boying Huang, Chun Zhou, Qianlu Sun, Fujie Tang*, Weigao Xu, Kezhao Du, Xingzhi Wang, Ye Yang*. Correlation between Exciton Dynamics and Spin Structure in the van der Waals Antiferromagnet NiPS3. Phys. Rev. B 2025, 112, L220413. (corresponding author)

  5. 5. Yongkang Wang#, Fujie Tang#, Xiaoqing Yu, Kuo-Yang Chiang, Chun-Chieh Yu, Tatsuhiko Ohto, Yunfei Chen, Yuki Nagata, Mischa Bonn. Interfaces Govern the Structure of Angstrom-scale Confined Water Solutions. Nat. Commun., 2025, 16, 7288. (#equal contribution)

  6. 6. Xianglong Du, Qi You, Jiezhen Xia, Fujie Tang*, Jun Cheng, Zhongqun Tian. Progress in Machine Learning-Accelerated Computational Spectroscopy. Sci. Sin. Chim., 2025, 55, 1715–1733. (corresponding author) (Invited Review) (In Chinese)

  7. 7. Qi You, Yan Sun, Feng Wang, Jun Cheng, Fujie Tang. Decoding the Competing Effects of Dynamic Solvation Structures on Nuclear Magnetic Resonance Chemical Shifts of Battery Electrolytes via Machine Learning. J. Am. Chem. Soc., 2025, 147, 14667–14676. (corresponding author)

  8. 8. Fanjie Xu, Wentao Guo, Feng Wang, Lin Yao, Hongshuai Wang, Fujie Tang, Zhifeng Gao, Linfeng Zhang, Weinan E, Zhong-Qun Tian, Jun Cheng. Toward a Unified Benchmark and Framework for Deep Learning-Based Prediction of Nuclear Magnetic Resonance Chemical Shifts. Nat. Comput. Sci., 2025, 5, 292–300. (corresponding author)

  9. 9. Fujie Tang, Diana Y. Qiu and Xifan Wu. Optical Absorption Spectroscopy Probes Water Wire and Its Ordering in a Hydrogen-Bond Network. Phys. Rev. X 2025, 15, 011048.

  10. Featured in an APS Physics Viewpoint: D. Donadio and G. Galli, ‘Shedding Light on Water Wires,’ Physics 2025, 18, 54.

  11. 10. Xianglong Du, Weizhi Shao, Chenglong Bao, Linfeng Zhang, Jun Cheng, Fujie Tang. Revealing the Molecular Structures of α-Al2O3(0001)-water Interface by Machine Learning Based Computational Vibrational Spectroscopy. J. Chem. Phys., 2024, 161, 124702. (∗corresponding author) (JCP Editor’s Pick)

  12. 11. Yongkang Wang#, Fujie Tang#, Xiaoqing Yu, Tatsuhiko Ohto, Yuki Nagata, Mischa Bonn. Heterodyne-Detected Sum-Frequency Generation Vibrational Spectroscopy Reveals Aqueous Molecular Structure at the Suspended Graphene/Water Interface. Angew. Chem. Int. Ed., 2024, 63, e202319503. (#equal contribution)

  13. 12. Fujie Tang, Kefeng Shi and Xifan Wu. Exploring the Impact of Ions on Oxygen K-Edge X-ray Absorption Spectroscopy in NaCl Solution using the GW-Bethe-Salpeter-Equation Approach. J. Chem. Phys., 2023, 159, 174501. (corresponding author)

  14. 13. Fujie Tang, Zhenglu Li, Chunyi Zhang, Steven G. Louie, Roberto Car, Diana Y. Qiu and Xifan Wu. Many-Body Effects in the X-ray Absorption Spectra of Liquid Water. Proc. Natl. Acad. Sci. U.S.A., 2022, 119, e2201258119.

  15. 14. Fujie Tang, Jianhang Xu, Diana Y. Qiu and Xifan Wu. Nuclear Quantum Effects on the Quasiparticle Properties of the Chloride Anion Aqueous Solution within the GW Approximation. Phys. Rev. B, 2021, 104, 035117.

  16. 15. Fujie Tang, Tatsuhiko Ohto, Shumei Sun, Jeremy R. Rouxel, Sho Imoto, Ellen H. G. Backus, Shaul Mukamel, Mischa Bonn, and Yuki Nagata. Molecular Structure and Modeling of Water-Air and Ice-Air Interfaces Monitored by Sum-Frequency Generation. Chem. Rev., 2020, 120, 3633-3667.


 


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