Advances in two dimensional electrochemical catalysts for ammonia synthesis

Abstract

Synthesizing ammonia at ambient environment is of great significance to maintain the sustainable development of human society. During the past few decades, the design and development of electrocatalysts with high nitrogen reduction efficiency have been widely studied. Although exciting advances have been made in the nitrogen reduction reaction (NRR) field, the development of electrochemical nitrogen-to-ammonia conversion is still challenging because of the low ammonia formation activity and unsatisfactory selectivity. Noble metals like Ru-based catalysts can convert N2 into ammonia at low potential, however, the high price, poor selectivity and ambiguous active centers hindered their applications as efficient electrocatalytic nitrogen reduction catalysts. An idea electrocatalyst with low-cost, high activity and selectivity toward NH3 was urgently sought by researchers. The rise of two-dimensional materials represented by graphene has brought new opportunities for the development of high-efficiency catalysts. Compared with traditional materials, two-dimensional materials process ultra-high specific surface area and surface atomic ratio, which is very beneficial for applications in the field of electro-chemical catalysis. More importantly, the chemical properties of two-dimensional materials can be controlled and modulated through element doping, surface modification, and manufacturing defects, which is very critical for the construction of high-performance electrocatalysts. The application of two-dimensional materials in electrochemical NRR has received extensive attention and researches. Many two-dimensional materials exhibit higher catalytic activity and selectivity than noble metal catalysts, which brings new opportunities for the development of electrochemical NRR. With the development of theoretical methods and the continuous improvement of computer performance, theoretical simulation has become an important tool for interpreting experimental phenomena, revealing catalytic mechanisms, and designing new catalysts in the field of catalysis. In the development process of two-dimensional NRR electrocatalysts, theoretical calculations have also made great contributions in determining the active center, guiding the experimental synthesis and therefore promoting the catalysis performance. In this paper, we introduced the reaction mechanism of NRR on these two-dimensional NRR electrocatalysts, and then briefly summarized the application of a series of two-dimensional materials in the field of N2 reduction electrocatalysis including graphene, graphite phase carbonitrides, boron nitride, transition metal dichalcogenides, transition metal carbon/nitrogen compounds, and metal borides. Various surface engineering strategies like doping heteroatoms, cave defects, changing coordinate environment aiming at increasing the exposed active sites, altering the electronic structure and improving the intrinsic activity were also systematically introduced in each chapter to improve the intrinsic activity and limiting the competing hydrogen evolution reaction. In the last chapter, we discussed the challenges and opportunities of using two-dimensional nanomaterials as high-efficiency electrocatalysts in N2 reduction. To better understand the geometry-activity relationships, machine learning was also adopted in the catalysis design process. With the help of machine learning algorithm, we can establish a correlation between physicochemical properties of catalysts and NRR performance, find out the most relevant physical-chemical descriptors and obtain a general equation for fast screening idea electrocatalysts. The combination of high throughput calculations and machine learning provides guidance for designing heterogeneous NRR electrocatalysts with high activity, good selectivity, and high stability. We believe this new research paradigm will improve calculation accuracy and accelerate the discovery process of idea NRR catalysts at the same time.