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Building up a general selection strategy and catalytic performance prediction expressions of heteronuclear double-atom catalysts for N_(2)reduction

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摘要 The severe environmental problems and the demand for energy urgently require electrocatalysis to replace Haber-Bosch for the nitrogen reduction reaction(NRR).The descriptors and important properties of single-atom and homonuclear double-atom catalysts have been preliminarily explored,but the relationship between the inherent properties and catalytic activity of heteronuclear double-atom catalysts with better performance remains unclear.Therefore,it is very significant to explore the prediction expressions of catalytic activity of heteronuclear double-atom catalysts based on their inherent properties and find the rule for selecting catalytic centers.Herein,by summarizing the free energy for the key steps of NRR on 55 catalysts calculated through the first-principle,the expressions of predicting the free energy and the corresponding descriptors are deduced by the machine learning,and the strategy for selecting the appropriate catalytic center is proposed.The selection strategy for the central atom of heteronuclear double-atom catalysts is that the atomic number of central B atom should be between group VB and VIIIB,and the electron difference between central A atom and B atom should be large enough,and the selectivity of NRR or hydrogen evolution reaction(HER)could be calculated through the prediction formula.Moreover,five catalysts are screened to have low limiting potential and excellent selectivity,and are further analyzed by electron transfer.This work explores the relationship between the inherent properties of heteronuclear double-atom catalysts and the catalytic activity,and puts forward the rules for selecting the heteronuclear double-atom catalytic center,which has guiding significance for the experiment.
出处 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2023年第7期375-386,I0009,共13页 能源化学(英文版)
基金 supports by the National Natural Science Foundation of China(NSFC,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。
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