Tri-modal machine learning powers efficient catalyst discovery for high-performance energy storage
Zhiwen Min(University of Macau), Yuanmiao Sun(Nanyang Technological University), Guodong Fu(Xiamen University), Hui-Ming Cheng(Shenzhen Institutes of Advanced Technology), Kwun Nam Hui(Xiamen University), Xinyu Ye(Shenzhen Institutes of Advanced Technology), Ting Wang(Shenzhen Institutes of Advanced Technology), Yaxin Cheng(Xiamen University), Yiwei You(University of Macau), Tianyu Chen(University of Macau)
Cited by 0
Related Papers
Anodic Oxidation Enabled Cation Leaching for Promoting Surface Reconstruction in Water Oxidation
|Angewandte Chemie International Edition|2020|248
Hierarchically porous Cu/Zn bimetallic catalysts for highly selective CO2 electroreduction to liquid C2 products
|Applied Catalysis B: Environmental|2020|184
Coordination Effect-Promoted Durable Ni(OH)2 for Energy-Saving Hydrogen Evolution from Water/Methanol Co-Electrocatalysis
|Nano-Micro Letters|2022|109
Capturing critical gem-diol intermediates and hydride transfer for anodic hydrogen production from 5-hydroxymethylfurfural
|Nature Communications|2023|86
Essential role of lattice oxygen in methanol electrochemical refinery toward formate
|Science Advances|2023|55