Recent advances in developing multiscale descriptor approach for the design of oxygen redox electrocatalysts
Dantong Zhang,
Qi Zhang,
Chao Peng,
Zhi Long,
Guilin Zhuang,
Denis Kramer,
Sridhar Komarneni,
Chunyi Zhi,
Dongfeng Xue
Affiliations
Dantong Zhang
Multiscale Crystal Materials Research Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Qi Zhang
Multiscale Crystal Materials Research Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Chao Peng
Multiscale Crystal Materials Research Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Corresponding author
Zhi Long
Multiscale Crystal Materials Research Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Guilin Zhuang
College of Chemical Engineering, Zhejiang University of Technology, 18, Chaowang Road, Hangzhou, Zhejiang Province 310032, China
Denis Kramer
Helmut-Schmidt-University, University of the Armed Forces, Hamburg 22043, Germany
Sridhar Komarneni
Materials Research Institute, Materials Research Laboratory, The Pennsylvania State University, University Park, PA 16802, USA
Chunyi Zhi
Department of Materials Science and Engineering, City University of Hong Kong, Kowloon, Hong Kong 999077, China; Corresponding author
Dongfeng Xue
Multiscale Crystal Materials Research Center, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China; Corresponding author
Summary: Oxygen redox electrocatalysis is the crucial electrode reaction among new-era energy sources. The prerequisite to rationally design an ideal electrocatalyst is accurately identifying the structure-activity relationship based on the so-called descriptors which link the catalytic performance with structural properties. However, the quick discovery of those descriptors remains challenging. In recent, the high-throughput computing and machine learning methods were identified to present great prospects for accelerating the screening of descriptors. That new research paradigm improves cognition in the way of oxygen evolution reaction/oxygen reduction reaction activity descriptor and reinforces the understanding of intrinsic physical and chemical features in the electrocatalytic process from a multiscale perspective. This review summarizes those new research paradigms for screening multiscale descriptors, especially from atomic scale to cluster mesoscale and bulk macroscale. The development of descriptors from traditional intermediate to eigen feature parameters has been addressed which provides guidance for the intelligent design of new energy materials.
