Transition‐Metal‐Doped Hexagonal Boron Nitride for Efficient and Selective Nitrate‐to‐Ammonia Electrocatalysis: Theoretical Perspective and Design Principles
Source abstract
Abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Ammonia Synthesis and Nitrogen Reduction · Electrocatalysts for Energy Conversion · Environmental remediation with nanomaterials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Chemistry Sungkyunkwan University Suwon Republic of Korea
College of Chemistry and Materials Science Jinan University Guangzhou China
Funding
National Research Foundation of Korea · Ministry of Education · Fundamental Research Funds for the Central Universities
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