“Blocking and rebalance”mechanism-guided design strategies of bimetallic doped 2D a-phosphorus carbide as efficient catalysts for N_(2) electroreduction  

作　　者：Cheng He Jianglong Ma Shen Xi Wenxue Zhang 

机构地区：[1]State Key Laboratory for Mechanical Behavior of Materials,School of Materials Science and Engineering,Xi'an Jiaotong University,Xian 710049,Shanxi,China [2]School of Materials Science and Engineering,Chang'an University,Xi'an 710064,Shaanxi,China

出　　处：《Journal of Energy Chemistry》2024年第10期68-78,I0003,共12页能源化学（英文版）

基　　金：supports by the National Natural Science Foundation of China (NSFC,Grant No.52271113);the Natural Science Foundation of Shaanxi Province,China (2020JM-218);the Fundamental Research Funds for the Central Universities (CHD300102311405);HPC platform,Xi’an Jiaotong University。

摘　　要：Compared to single atom catalysts(SACs),the introduction of dual atom catalysts(DACs)has a significantly positive effect on improving the efficiency in the electrocatalytic nitrogen reduction reaction(NRR)which provides an environmental alternative to the Haber-Bosch process.However,the research on the mechanism and strategy of designing bimetallic combinations for better performance is still in its early stages.Herein,based on"blocking and rebalance"mechanism,45 combinations of bimetallic pair dopedα-phosphorus carbide(TM_(A)TM_(B)@PC)are investigated as efficient NRR catalysts through density functional theory and machine learning method.After a multi-step screening,the combinations of TiV,TiFe,MnMo,and FeW exhibit highly efficient catalytic performance with significantly lower limiting potentials(-0.17,-0.18,-0.14,and-0.30 V,respectively).Excitingly,the limiting potential for CrMo and CrW combinations is 0 V,which are considered to be extremely suitable for the NRR process.The mechanism of"blocking and rebalance"is revealed by the exploration of charge transfer for phosphorus atoms in electron blocking areas.Moreover,the descriptorφis proposed with machine learning,which provides design strategies and accurate prediction for finding efficient DACs.This work not only offers promising catalysts TM_(A)TM_(B)@PC for NRR process but also provides design strategies by presenting the descriptorφ.

关 键 词：DACs Nitrogen reduction reaction 2D a-phosphorus carbide Inherent attributes Machine learning 

分 类 号：TQ113.2[化学工程—无机化工] O643.36[理学—物理化学]