EN
Peilin Kang
Physical Chemistry
Assistant Professor
Room A3069, Chemistry Building, Department of Chemistry, Fudan University 2005 Songhu Road, Yangpu District, Shanghai 200438, China
Research Interests
Artificial intelligence guided rational design of novel materials and catalysts
Development and application of neural network potentials
Development of enhanced sampling methods
Biography
2013.9-2017.6BSc, Department of Chemistry, Fudan University, China
2017.9-2022.6PhD, Department of Chemistry, Fudan University, China
2022.10-2026.2Postdoc, Italian Institute of Technology, Italy
2026.3-Assistant Professor, Department of Chemistry, Fudan University, China
Key Publications
Peilin Kang#; Jintu Zhang#; Enrico Trizio; Tinjun Hou*; Michele Parrinello*. Committors without Descriptors. J. Chem. Theory Comput., 2026. 22, 4, 1613–1620 //doi.org/10.1021/acs.jctc.5c01848
Enrico Trizio#; Peilin Kang#*; Michele Parrinello*. Everything everywhere all at once: a probability-based enhanced sampling approach to rare events. Nat. Comput. Sci., 2025. 5, 582-591 //doi.org/10.1038/s43588-025-00799-5
Peilin Kang; Enrico Trizio; Michele Parrinello*. Computing the committor with the committor to study the transition state ensemble. Nat. Comput. Sci., 2024. 4, 451-460 //doi.org/10.1038/s43588-024-00645-0
Pei-Lin Kang; Zheng-Xin Yang; Cheng Shang*; Zhi-Pan Liu*. Global Neural Network Potential with Explicit Many-body Functions for Improved Descriptions of Complex Potential Energy Surface, J. Chem. Theory Comput., 2023, 21, 7972 //doi.org/10.1021/acs.jctc.3c00873
Pei-Lin Kang; Yun-fei Shi; Cheng Shang*; Zhi-Pan Liu*. Artificial intelligence pathway search to resolve catalytic glycerol hydrogenolysis selectivity. Chem. Sci,2022, 13, 8148. //doi.org/10.1039/D2SC02107B
Pei-Lin Kang; Zhi-Pan Liu*. Reaction Prediction via Atomistic Simulation: From Quantum Mechanics to Machine Learning. iScience 2021, 24 (1), 102013. //doi.org/10.1016/j.isci.2020.102013.
Pei-Lin Kang; Cheng Shang*; Zhi-Pan Liu*. Recent Implementations in LASP 3.0: Global Neural Network Potential with Multiple Elements and Better Long-Range Description. Chin. J. Chem. Phys.2021, 34 (5), 583–590. //doi.org/10.1063/1674-0068/cjcp2108145.
Pei-Lin Kang; Cheng Shang*; Zhi-Pan Liu*. Large-Scale Atomic Simulation via Machine Learning Potentials Constructed by Global Potential Energy Surface Exploration. Acc. Chem. Res.2020, 53 (10), 2119–2129. //doi.org/10.1021/acs.accounts.0c00472.
Pei-Lin Kang; Cheng Shang*; Zhi-Pan Liu*. Glucose to 5-Hydroxymethylfurfural: Origin of Site-Selectivity Resolved by Machine Learning Based Reaction Sampling. J. Am. Chem. Soc. 2019, 141 (51), 20525–20536. //doi.org/10.1021/jacs.9b11535.
