Catalytic reactivity descriptors of metal-nitrogen-doped carbon catalysts for electrocatalysis

Abstract

Metal-nitrogen-doped carbon material have sparked enormous attentions as they show excellent electrocatalytic performance and provide a prototype for mechanistic understandings of electrocatalytic reactions. Researchers spare no effort to find catalytic reactivity “descriptor”, which is correlated with catalytical properties and could be utilized for guiding the rational design of high-performance catalysts. In recent years, benefited from the development of computational technology, theoretical calculation came into being as a powerful tool to understand catalytic mechanisms from an atomic level as well as to accelerate the process of finding a catalytic reactivity descriptor and promoting the development of effective catalysts. In the present review, we provide the latest theoretical research toward energetic and electronic descriptors for metal-nitrogen-doped carbon (M-N-C) materials, which have shown excellent electrocatalytic performance and provide a prototype for the mechanistic understanding of electrocatalytic reactions. This review uses density functional theory calculation and the most advanced machine learning method to describe the exploration of four kinds of electrocatalytic reaction descriptors, namely oxygen reduction reaction, carbon dioxide reduction reaction, hydrogen evolution reaction, and nitrogen reduction reaction. The aim of this review is to inspire the future design of high-efficiency M-N-C catalysts by providing in-depth insights into the electrocatalytic activity of these materials.