collaborators

5 papers

physics.chem-ph2026

Quantum Vibronic Dynamics Shape Catalytically Relevant Au-Ligand Interfaces in Atomically Precise Gold Nanoclusters

Mengyuan Cui, Tianrui Chen, Junhua Zhou +6

Atomically precise gold nanoclusters are versatile for photocatalysis and energy conversion because their electronic structure stems from strong metal-ligand interactions. However,…

cond-mat.mtrl-sci2026

Decoupling Intrinsic Molecular Efficacy from Platform Effects: An Interpretable Machine Learning Framework for Unbiased Perovskite Passivator Discovery

Jing Zhang, Ziyuan Li, Shan Gao +3

Rational design of interface passivators for perovskite solar cells is hindered by the entanglement of intrinsic molecular efficacy with extrinsic platform-dependent performance -…

physics.chem-ph2025

Identifying the Catalytic Descriptor of Single-Atom Catalysts in Nitrate Reduction Reaction: An Interpretable Machine-Learning Method

Zhen Zhu, Shan Gao, Jing Zhang +3

Elucidating the catalytic descriptor that accurately characterizes the structure-activity relationships of typical catalysts for various important heterogeneous catalytic reactions…

quant-ph2025

Toward Heisenberg Scaling in Non-Hermitian Metrology at the Quantum Regime

Xinglei Yu, Xinzhi Zhao, Liangsheng Li +4

Non-Hermitian quantum metrology, an emerging field at the intersection of quantum estimation and non-Hermitian physics, holds promise for revolutionizing precision measurement. Her…

physics.chem-ph2025

Prediction of CO2 reduction reaction intermediates and products on transition metal-doped r-GeSe monolayers:A combined DFT and machine learning approach

Xuxin Kang, Wenjing Zhou, Ziyuan Li +5

The electrocatalytic CO2 reduction reaction (CO2RR) is a complex multi-proton-electron transfer process that generates a vast network of reaction intermediates. Accurate prediction…