Proposing explainable descriptors towards enhanced N2 reduction performance on the two-dimensional bismuthine nanosheets modified by p-block element-based electrocatalysts

Abstract

p-Block element-based electrocatalysts featuring a tunable electronic structure to achieve exceptional N₂ activation and proton suppression have garnered extensive interest for the electrochemical N₂ reduction reaction (NRR). Albeit various reaction mechanisms were proposed to understand and optimize the NRR performance, methods to effectively design and rapidly screen potential candidates are still elusive. Herein, a couple of explicit and interpretable descriptors on the entire p-block element-based electrocatalysts are put forward to predict NRR activity and selectivity via high-throughput theoretical simulations and a symbolic regression algorithm, taking two-dimensional (2D) bismuthine with p-block elements doped in or adsorbed as an example. The descriptors are merely composed of inherent atomic properties (p orbital electron number, electron affinity, electronegativity, atomic radius, etc.) combined with algebraic operators, independent of the intricate DFT calculations. Multi-task regression results demonstrate that the doped and adsorbed bismuthine systems possess the same descriptors, namely, the descriptors of doped-Bi can accurately forecast the NRR performance of adsorbed-Bi, and vice versa. Five potential candidates (5/40) with outstanding NRR activity, selectivity and stability are screened. C-doped and Si-doped bismuthine possess less negative limiting potentials of the NRR [U_L(NRR)] of −0.46 and −0.68 V and positive [U_L(NRR) − U_L(HER)] values of 1.15 and 0.13 V, respectively, superior to those of the majority of reported p-block element-based electrocatalysts, which are expected to be verified by the experimental research. This work offers a feasible solution for developing promising electrocatalysts for the NRR and potentially other electrochemical reactions on the basis of explainable descriptors using geometric information and intrinsic atomic quantities.