Superior single-atom and single-cluster catalysts towards electrocatalytic nitrogen reduction reactions: a theoretical perspective

Haihong Meng , Yinghe Zhao , Fengyu Li , Zhongfang Chen

Journal of Materials Informatics ›› 2025, Vol. 5 ›› Issue (1) : 3

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Journal of Materials Informatics ›› 2025, Vol. 5 ›› Issue (1) :3 DOI: 10.20517/jmi.2024.74
Review

Superior single-atom and single-cluster catalysts towards electrocatalytic nitrogen reduction reactions: a theoretical perspective

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Abstract

The traditional Haber-Bosch process for ammonia synthesis is both energy-intensive and capital-demanding. Electrocatalytic nitrogen reduction reaction (NRR) has emerged as a promising, sustainable alternative, with recent advantages highlighting its potential. Single-atom catalysts (SACs) and single-cluster catalysts (SCCs) are promising catalysts for NRR due to their atomically dispersed active sites, maximized atom utilization, and distinctive coordination and electronic structures, all of which facilitate mechanism insights at the atomic level. Benefiting from efficient atom utilization, for example, the ammonia yield rate on Au1/C3N4 is roughly 22.5 times as high as that of supported Au nanoparticles, fully demonstrating the significant advantages of SACs over nanoparticles. In this review, we focus on the theoretical progress in SACs and SCCs for electrocatalyzing NRR, including nitrogenase-like bio-inspired catalysts and other metal-based catalysts. We further examine key adsorption energy and electronic descriptors that enhance our understanding of catalytic performance. Finally, we discuss the remaining challenges and future directions for advancing SACs and SCCs in electrocatalytic NRR applications.

Keywords

Nitrogen reduction reaction / electrocatalysts / single-atom catalysts / single-cluster catalysts / theoretical perspective

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Haihong Meng, Yinghe Zhao, Fengyu Li, Zhongfang Chen. Superior single-atom and single-cluster catalysts towards electrocatalytic nitrogen reduction reactions: a theoretical perspective. Journal of Materials Informatics, 2025, 5(1): 3 DOI:10.20517/jmi.2024.74

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