Electronegativity-oriented coordination regulation of main-group metal single-atom catalysts for oxygen reduction to H₂O₂: A combined study of first-principles and machine learning

Electrochemical two-electron oxygen reduction reaction (2e^- ORR) is a green and attractive method for hydrogen peroxide synthesis. However, rapid and efficient development of high-performance catalyst remains a great challenge. Different from traditional trial and error methods, this study employs density functional theory and machine learning method to efficiently screen the promising main-group metal single-atom catalysts (SACs) and systematically investigate the influence of electronegativity of coordination atoms on the adsorption behavior of key intermediates in ORR process. It is found that the K SAC with N/B in the first coordination sphere and Sn SAC with N/C in the first coordination sphere and O in the second coordination sphere exhibit both excellent 2e^- ORR activity and selectivity by showing extremely low overpotentials of 0.029 V and 0.064 V, respectively, as well as barrier-free processes from *OOH to H₂O₂. Bagging displays prominent advantages among seven popular algorithms because of its ensemble strategy. This provides a low-cost approach for designing and screening electrocatalyst candidates, and it will be informative for experimental study in the future to accelerate the development of catalysts for oxygen reduction and other types of reactions.