Electric field-enhanced electrocatalysis represents an innovative strategy for improving the efficiency of electrochemical transformations. However, quantitative evaluation of microscopic electric-field effects under operando conditions remains challenging, limiting a rigorous, predictive understanding of field-mediated reaction regulation. Here, by integrating rigorous numerical methods, constant-potential microkinetic simulations, and machine learning models, we establish electric-field intensity as a quantitative descriptor that directly correlates local fields with catalytic performance. Using curvature-engineered M–N–C single-atom catalysts as a model platform, we demonstrate that curvature-induced electric fields modulate electron occupation at active sites and shift the potential of zero charge in a controllable manner. This field-driven electronic perturbation selectively tunes adsorbate binding energetics, thereby dictating limiting potentials, steering reaction pathways, and governing the thermodynamics and kinetics of interfacial proton-coupled electron transfer in nitrogen electroreduction. Notably, we uncover an inverted volcano–type dependence of catalytic activity on curvature, wherein optimal activity is achieved within a moderate field-strength window. This nonmonotonic trend underscores the necessity of balanced curvature regulation, rather than simply maximizing field intensity, in optimizing electrocatalytic performance. These findings provide a quantitative framework for monitoring and regulating catalytic trends under realistic operating conditions via curvature-induced electric fields, offering generalizable design principles for diverse SAC systems and electrochemical reactions.
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Hu et al. (2026) studied this question.
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