ScholarWorks@성균관대학교

초록

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 (NO3RR) offers such a dual solution by converting NO3 - into ammonia (NH3), 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 NH3 production. The exceptional performance of these catalysts arises from their balanced interaction with NO3 -, 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 (NO2, NO, N2O, N2) impart excellent selectivity toward NH3 formation. To generalize these mechanistic insights, we integrate a SISSO-based machine learning framework that uncovers key descriptors governing NO3RR 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 NH3 production and water resources.

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