Prediction of Three-Metal Cluster Catalysts on Two-Dimensional W2N3 Support with Integrated Descriptors for Electrocatalytic Nitrogen Reduction

In the electrocatalytic nitrogen reduction reaction (NRR), nitrogen (N2) is chemically inert, it is difficult to break the triple bond, and the subsequent protonation step is very challenging. Suitable catalysts with high selectivity and high activity are needed to promote the electrocatalytic NRR. We screen a large number of clusters composed of three metal atoms embedded into a two-dimensional metal nitride, W2N3, with a N vacancy, and calculate the reaction energetics. The VNiCu cluster has the best catalytic activity among all the catalysts proposed so far. The Fe3 and Fe2Co clusters are excellent catalysts as well. In all cases, spin polarization is needed to observe the catalytic effect. We establish the optimal NRR path and confirm that it remains unchanged in the presence of a solvent. We find three groups of descriptors that can well predict the materials' properties and exhibit linear relationships with the NRR limiting potential.

Automated summary

In the study, it was found that introducing N vacancies and embedding three metal atom clusters in a two-dimensional metal nitride, W2N3, can enhance the electrocatalytic nitrogen reduction reaction (NRR). Among all the proposed catalysts, the VNiCu cluster showed the best catalytic activity. The Fe3 and Fe2Co clusters also exhibited excellent catalytic performance. Three groups of descriptors were identified to predict the materials' properties and were found to have linear relationships with the NRR limiting potential.