Design of Single‐Atom Catalysts Anchored in N‐Doped Biphenylene Using Symbolic Regression for Electrocatalytic Nitrate Reduction to Ammonia

Abstract Electrocatalytic nitrate reduction (NO 3 RR) presents a synergistic strategy, achieving dual benefits in energy transformation and environmental remediation through a single process. However, the complexity of its reaction pathway and the lack of descriptors impede the rational design of high‐performance NO 3 RR electrocatalysts. Herein, employing a series of transition metal doped and nitrogen decorated biphenylene network (TM‐C x N y @BPN), an inclusive recipe toward the stability, reaction mechanism, and activity trend of single atomic catalysts (SACs) for NO 3 RR is proposed by integrating multidimensional insights from coordination environment, thermodynamic and electrochemical stability, Gibbs free energy profiles, electronic properties, and activity descriptors. It is revealed that the NO 3 RR performance of SACs is highly correlated with their local environments. Furthermore, the hybridization between the TM‐3 d orbitals and 2π* orbitals of NO 3 − gives rise to the formation of d ‐π* orbitals, thus promoting the NO 3 − activation. A symbolic regression is designed to capture the hidden descriptors of NO 3 RR, outperforming than using single adsorbate or electronic descriptors for hyper dimensional system entailing large geometric variability.