ABSTRACT Escalating nitrate contamination in water resources underscores the urgent demand for remediation strategies that not only eliminate nitrates but also enable valorization. The electrochemical nitrate reduction reaction (NO 3 RR) offers such a dual solution by converting NO 3 − into ammonia (NH 3 ), a cornerstone chemical in fertilizers and energy applications. Here, we employ first‐principles calculations to systematically evaluate a family of transition‐metal‐doped hexagonal boron nitride (TM@h‐BN, TM = Ti‐Au) monolayers. Our results identify Fe@h‐BN and Ir@h‐BN as highly promising single‐atom catalysts, exhibiting low limiting potentials of −0.45 V and −0.31 V, respectively, for efficient NH 3 production. The exceptional performance of these catalysts arises from their balanced interaction with NO 3 − , which provides sufficient adsorption without over‐stabilization, while their intrinsically weak hydrogen binding suppresses the competing hydrogen evolution reaction (HER). Moreover, the elevated potentials for byproduct pathways (NO 2 , NO, N 2 O, N 2 ) impart excellent selectivity toward NH 3 formation. To generalize these mechanistic insights, we integrate a SISSO‐based machine learning framework that uncovers key descriptors governing NO 3 RR catalyst performance and establishes a general equation linking limiting potential and fundamental catalyst properties. Collectively, this work not only expands the design landscape of h‐BN‐anchored single‐atom catalysts but also provides a transferable design principle for next‐generation electrocatalysts, paving the way toward sustainable NH 3 production and water resources.
Yin et al. (Wed,) studied this question.