3 papers
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…
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…