• DFT screening of edge-supported iron SACs and DACs for NO reduction reaction (NORR) • Graphitic edge supports enhance catalyst stability, activity, and HER selectivity. • Iron SACs benefit most from graphitic edges, showing higher NORR activities. • NORR activity of edge-supported Fe DACs depends on support type and site poisoning. • Electronic states of adsorbates and intermediates dictate catalytic performance. Global warming remains a critical challenge, driven largely by a sharp increase in greenhouse gas emissions, with nitric oxide (NO) being particularly harmful yet often overlooked. Combining with the urgency of producing environmentally friendly ammonia (NH 3 ), we can reduce nitric oxide using an electrochemical reaction via the Nitric Oxide Reduction Reaction (NORR). Single-atom catalysts (SACs) and double-atom catalysts (DACs) with iron active sites supported on graphene have been developed to facilitate this reaction. Recently, the use of porous graphene in the form of graphitic edge for SACs and DACs has shown promising catalytic performance in several electrochemical reactions, but its effectiveness in NORR remains unproven. Therefore, this study investigates NORR within the iron-based SAC and DAC with graphitic edge supports using density functional theory (DFT) simulations. A systematic analysis was conducted using four screening steps, encompassing catalyst formation energy, NO adsorption capability, NORR electrocatalytic activity, and selectivity against the hydrogen evolution reaction (HER). The results demonstrate that iron-based SAC with a graphitic edge support exhibits superior catalytic performance, i.e., low formation energies, higher NORR activity, and higher selectivity compared to catalysts with graphene interior supports. The independent nature of this type of catalyst also strengthens its use for NORR. Further analysis on catalyst descriptor and electronic properties shows that moderate NO and potential determining step (PDS) species result in excellent NORR catalytic performances.
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Reva Budiantono
Kenta Hongo
Ni Luh Wulan Septiani
Fuel
Kumamoto University
Japan Advanced Institute of Science and Technology
Bandung Institute of Technology
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Budiantono et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69d895206c1944d70ce0618d — DOI: https://doi.org/10.1016/j.fuel.2026.139398