Improved oxygen electrocatalysis at Fe N_(4)and Co N_(4)sites via construction of axial coordination  

作　　者：Ze Zhang Lei Yang Jin-Ru Liu Hao Hu Jian-Li Mi Chao Su Bei-Bei Xiao Zhi-Min Ao 

机构地区：[1]School of Energy and Power Engineering,Jiangsu University of Science and Technology,Zhenjiang 212003,China [2]Institute for Computation in Molecular and Materials Science,School of Chemistry and Chemical Engineering,Nanjing University of Science and Technology,Nanjing 210094,China [3]Institute for Advanced Materials,School of Materials Science and Engineering,Jiangsu University,Zhenjiang 212013,China [4]Advanced Interdisciplinary Institute of Environment and Ecology,Beijing Normal University,Zhuhai 519087,China

出　　处：《Chinese Chemical Letters》2025年第2期454-459,共6页中国化学快报(英文版)

基　　金：financial support from the National Natural Science Foundation of China(Nos.21503097,52130101,51701152,21806023,and 51702345);Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX23_3905)。

摘　　要：The quest for efficient and durable catalysts using abundant resources has garnered significant interest in the field of bifunctional oxygen electrocatalysis.In this contribution,we have designed a FeN_(4)or CoN_(4)embedded graphene-based bilayer as active layer and TMC_(3)or TMN_(3)doped graphene as supporting layer,named as FeN_(4)/TMC_(3)or FeN_(4)/TMN_(3)and CoN_(4)/TMC_(3)or CoN_(4)/TMN_(3),wherein TM strands for transition metal.Based on density functional theory calculations,our results demonstrate that the interaction formed between dual metal atoms in the bilayer interspace leads to the coordination environment altered from flat four-coordination to spatial five-coordination,further stabilizing the bilayer structure and impairing its affinity toward the O-containing intermediates.According to thermodynamic analysis,the bilayers of CoN_(4)/CoN_(3),FeN_(4)/FeC_(3),FeN_(4)/CoC_(3),FeN_(4)/NiC_(3),FeN_(4)/ZnC_(3),FeN_(4)/FeN_(3),FeN_(4)/CrN_(3)and FeN_(4)/ZnN_(3)are attractively promising for bifunctional oxygen electrocatalysis due to the small overpotential differenceΔηbetween oxygen reduction and oxygen evolution that are less than 1 V.Density functional theory calculations combined with machine learning analysis directly identify the key role played by the interbinding formed between bilayers,that boosts catalytic activity,which establishes a predictable framework for a fast screen for graphene-based bilayer vertical heterojunction.This work opens up a new path for designing the efficient electrocatalysts via modification of coordination environment.

关 键 词：Oxygen electrocatalysis Thermodynamic analysis Density functional theory Machine learning 

分 类 号：TM911.41[电气工程—电力电子与电力传动] O643.36[理学—物理化学]