Ammonia (NH3) is widely used in agriculture, fertilizer production and chemical industry. The process of commercial NH3 production relies on the Haber-Bosch process that is energy-intensive and highly dependent on fossil fuels, and has with significant greenhouse gas emissions.
In this regard, the electrocatalytic N2 reduction reaction (NRR) for NH3 production is a promising approach to address these issues in a carbon-neutral and energy-saving way. The major challenges for electrochemical NRR are: low catalytic activity and poor selectivity.
The strong N bond of N2 inhibits the reaction due to sluggish NRR kinetics. The poor selectivity is due to the strong competition with the hydrogen reduction reaction (HER), which results in low Faradaic efficiency (FE) in aqueous solution. In this regard, designing efficient catalysts to boost the electrocatalytic NRR efficiency and minimize HER is extremely important.
Rational design of catalysts by computational methods makes it possible to find new materials, followed up by density functional theory (DFT) calculations to investigate the reaction pathways and mechanisms of promising materials. This is the key advance and importance of current proposal to utilize the high performance computing (HPC).