I am Cheng Fan, a postdoctoral researcher in computational chemistry at Westlake University. My work spans path integral molecular dynamics, machine learning force fields, and efficient calculations for excited-state and nonadiabatic dynamics.
Journal of Chemical Theory and Computation, 21(15), 7279–7289 (2025)
Combining machine learning force fields with a modular simulation framework to study nuclear quantum effects in reactions and phase transitions at reduced computational cost.
ACS Central Science, 11(11), 2180–2187 (2025)
Investigating concerted hydrogen tunneling in catalytic hydrogenation at room temperature.
Physica B: Condensed Matter, 418749 (2026)
Path integral molecular dynamics with a machine learning force field to study muonium in diamond.
† Equal contribution; * Corresponding author