Density Functional Theory Screening on TM-Net-Graphene Single-Atom Electrocatalysts for High-Performance Oxygen Reduction and Evolution Reactions

作者：Jianjun Fang, Yuebo Gao, Tong Xing, Qi Xiang, Chenkun Li, Rongxing Zhang, Yu Wu, A. J. C. Varandas, Jing Li · 发表于：The Journal of Physical Chemistry C · 年份：2025 · DOI：10.1021/acs.jpcc.5c04663 · 被引用次数：3 · 研究领域：Electrocatalysts for Energy Conversion、Fuel Cells and Related Materials、Advanced Memory and Neural Computing

Developing highly efficient bifunctional electrocatalysts for oxygen reduction reactions (ORR) and oxygen evolution reactions (OER) is a crucial task in advancing energy conversion and storage technologies. In this work, we investigated the catalytic performance of single transition metal (TM) atoms coordinated with four nitrogen atoms (TMN 4 ) embedded in pristine graphene sheets by means of density functional theory (DFT). These TMN 4 units serve as active sites for both the ORR and the OER. We systematically evaluated the stability of these catalysts and performed Bader charge analysis to elucidate the charge redistribution in the doped structures. Furthermore, we screened TMN 4 -net-graphene configurations for their bifunctional activity by analyzing the overpotentials required for the ORR and the OER processes. To gain deeper insights into the catalytic behavior, we constructed volcano plots using relevant ORR and OER descriptors, enabling the prediction of catalytic activity across various metal/nitrogen codoped graphene systems. From our results, RhN 4 -net-graphene exhibited a very promising bifunctional performance, facilitating ORR/OER at considerable low overpotentials of 0.32 V/0.28 V, respectively. These values surpass those of currently established catalysts such as Pt (η ORR = 0.45 V) and RuO 2 (η OER = 0.42 V), highlighting the potential of RhN 4 -net-graphene as a superior bifunctional electrocatalyst. Our findings not only provide a comprehensive understandi...