Electrochemical Nitrogen Reduction to Ammonia with Mesoporous Molybdenum-Carbon Electrocatalysts in a Gas Diffusion Flow Cell
Abstract
Abstract Commercialization of electrochemical nitrogen reduction (eNRR) is hindered by limited catalyst performance, the lack of scalable electrochemical cell architectures, and an incomplete understanding of performance-limiting processes. This work aims to address these challenges through a systematic investigation of catalyst composition and microstructure, device configuration, and reaction mechanisms. Molybdenum (Mo) metal single atoms and clusters supported on mesoporous nitrogen-doped carbon were synthesized with tunable pore sizes via a five-second photothermal pyrolysis of a self-assembled bottlebrush block copolymer (BBCP) template. For eNRR, improved Mo dispersion enhanced electrochemical accessibility, while the coexistence of atomically dispersed Mo species and Mo clusters produced a structurally heterogeneous catalytic environment that benefits eNRR. A gas-diffusion electrode (GDE) flow cell was constructed for continuous operation testing; the catalyst–device system achieved a Faradaic efficiency of 21.6% and an ammonia yield rate of 34.7 μg h–1 mg–1. Intermediate pore sizes and balanced electrode wettability promoted effective triple-phase boundary formation and active-site utilization. Electrochemical characterization combined with machine-learning analysis of flow-cell parameters indicated that activation polarization is the dominant loss mechanism, governed primarily by intrinsic active-site kinetics and electrochemically accessible surface area. In contrast, pore size, metal dispersion, and electrode wettability primarily regulate site accessibility rather than mass-transport limitations. Together, these results provide a framework linking catalyst structure, electrode architecture, and kinetic limitations in eNRR flow-cell systems and offer practical design guidelines for advancing scalable eNRR technology.
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Authors: Chaoyun Tang, Dipankar Saha, Jiacheng Wang, Arvind Chandrasekar, Negar Sabouhanian, Connor L. Witt, Yulei Wang, Aicheng Chen, Wei Fan, Chung‐Li Dong, Zhu Chen, James J. Watkins, Nianqiang Wu
Institutions: University of Guelph, Tamkang University