Kinetic profiling of multi-enzymatic activity in iron single-atom nanozymes via single-particle impact electrochemistry

Nanozymes endowed with multi-enzymatic functionalities represent a class of high-performance heterogeneous catalysts for the efficient regulation of intricate biochemical cascades, offering profound potential in targeted clinical therapeutics, high-sensitivity biosensing, and sustainable environmental remediation. However, the rational design of such nanozymes is often constrained by the complexities of deconvoluting the synergistic catalytic mechanisms and quantifying their intrinsic kinetic parameters within ensemble-based measurements. In this study, single-particle impact electrochemistry was utilized to systematically investigate the intrinsic catalytic kinetics of an iron single-atom nanozyme (Fe-SAN) possessing five biomimetic activities: peroxidase (POD), glutathione peroxidase (GP_x), catalase (CAT), glucose oxidase (GO_x), and superoxide dismutase (SOD) activities. The turnover numbers (TON) and catalytic rate constants (k_cat) for individual Fe-SAN were directly determined without the use of external indicators. The results demonstrated a clear catalytic preference, with k_cat values descending in the order of CAT > GO_x > POD > SOD > GP_x. Enzymatic mimics capable of generating reactive oxygen species (ROS), specifically POD, GP_x, and GO_x, exhibited robust catalytic performance, yielding single-particle k_cat values around 10⁷ s⁻¹. Notably, the CAT-like activity reached (1.252 ± 0.0131) ×10⁹ s⁻¹ in a neutral environment, indicating an exceptional capacity for ROS elimination. This comprehensive single-particle kinetic characterization, complemented by DFT simulations, provided critical insights into the correlation between Fe-N_x active sites and the resultant catalytic performance, thereby offering a promising framework that may potentially be extended to guide the future kinetic deconvolution and rational design of other multifunctional single-atom nanozyme systems.