collaborators

5 papers

physics.chem-ph2026

A Unified Generative Framework for Scalable Chemical Reaction Network Exploration

Zechang Sun, Chenxi Hu, Kailai Lin +6

Chemical reaction networks (CRNs) are crucial for understanding reaction mechanisms and guiding chemical synthesis, yet the computational exploration remains limited by the combina…

physics.chem-ph2026

Quantum Many-Body Simulations of Catalytic Metal Surfaces

Changsu Cao, Hung Q. Pham, Zhen Guo +5

Quantum simulations of metal surfaces are critical for catalytic innovation. Yet existing methods face a cost-accuracy dilemma: density functional theory is efficient but system-de…

cs.LG2026

Hessian-informed machine learning interatomic potential towards bridging theory and experiments

Bangchen Yin, Jian Ouyang, Zhen Fan +7

Local curvature of potential energy surfaces is critical for predicting certain experimental observables of molecules and materials from first principles, yet it remains far beyond…

physics.chem-ph2025

ByteQC: GPU-Accelerated Quantum Chemistry Package for Large-Scale Systems

Zhen Guo, Zigeng Huang, Qiaorui Chen +7

Applying quantum chemistry algorithms to large-scale systems requires substantial computational resources scaled with the system size and the desired accuracy. To address this, Byt…

cond-mat.mtrl-sci2025

Advancing Surface Chemistry with Large-Scale Ab-Initio Quantum Many-Body Simulations

Zigeng Huang, Zhen Guo, Changsu Cao +5

Predictive simulation of surface chemistry is of paramount importance for progress in fields from catalysis to electrochemistry and clean energy generation. Ab-initio quantum many-…