Dr. Chen Qian

Dr. Chen Qian is a postdoctoral research fellow whose work bridges computational chemistry and machine learning to understand light-matter interactions at molecular-metal interfaces.

Research Focus

Chen’s research centers on the dynamics of excited hot electrons through the interface between molecules and metal surfaces under solar radiation. His approach employs advanced computational methods including:

• Nonadiabatic molecular dynamics (NAMD) and surface hopping methods
• Machine-learning-enhanced density functional theory calculations
• Equivariant and invariant graph neural networks
• Generative models for molecular systems

This work is crucial for understanding photocatalysis, solar energy conversion, and other light-driven processes at surfaces.

Machine Learning and Electronic Structure

Chen is developing novel machine-learning techniques to enhance the accuracy and efficiency of density functional theory calculations. By going beyond traditional Born-Oppenheimer approximations, his methods can capture the complex electron dynamics that occur when molecules interact with light while adsorbed on metal surfaces.

Background

Chen earned his PhD in Mechanical Engineering from Zhejiang University, where he developed expertise in computational methods for molecular systems. After completing his doctorate, he worked as a postdoctoral researcher at City University of Hong Kong before joining the Maurer group at Warwick.

Publications

For a complete list of publications, visit his Google Scholar profile or ORCID.