The geometric-electronic coupled design of diatomic catalyst towards oxygen reduction reaction
Yan Liu, Yan Yang, Xuanni Lin, Yutao Lin, Zhiwen Zhuo, Dong Liu, Junjie Mao, Jun Jiang
Abstract
Diatomic catalysts are promising candidates for heterogeneous catalysis, whereas the rational design meets the challenges of numerous optional elements and the correlated alternation of parameters that affect the performance. Herein, we demonstrate a geometric-electronic coupled design of diatomic catalysts towards oxygen reduction reaction through machine learning derived catalytic “hot spot map”. The hot spot map is constructed with two descriptors as axes, including the geometric distance of the diatom and electronic magnetic moment. The narrow hot region in the map indicates the necessary collaborative regulation of the geometric and electronic effects for catalyst design. As a predicted ideal catalyst for oxygen reduction reaction, the N-bridged Co, Mn diatomic catalyst (Co-N-Mn/NC) is experimentally synthesized with a half-wave potential of 0.90 V, together with the embodied zinc air battery displaying high peak power density of 271 mW cm−2 and specific capacity of 806 mAh g − 1Zn. This work presents an advanced prototype for the comprehensive design of catalysts. The rational design of diatomic catalysts faces challenges due to the numerous tunable parameters. Here, the authors report a geometric-electronic coupled design using machine learning-derived catalytic “hot spot maps” for screening diatomic catalysts towards oxygen reduction reaction.