Abstract
Fullerene-supported single-atom catalysts (SACs) have emerged as a promising class of materials for electrocatalytic overall water splitting, offering a route to reduce reliance on scarce and costly precious metals. This review systematically summarizes recent advances in the design, synthesis, and application of fullerene-based SACs, with an emphasis on their unique structural, electronic, and catalytic properties. The exceptional stability, conductivity, and surface chemistry of fullerenes enable strong interactions with metal atoms, allowing high dispersion and enhanced catalytic performance for both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Recent studies demonstrate that C(60)- and C(24)-based materials, when combined with transition metals such as Pt, Ru, and V, exhibit superior HER/OER activity, bifunctionality, and spin-selective catalytic pathways. The vast structural space of fullerene-metal combinations presents new opportunities, which can be efficiently explored using machine learning and high-throughput simulations. By integrating density functional theory, transition state modeling, and data-driven techniques, this emerging research frontier is paving the way for rational catalyst design. The review concludes by proposing a machine learning-assisted framework to predict and screen high-performance fullerene-based SACs, ultimately accelerating the development of efficient, stable, and scalable electrocatalysts for sustainable hydrogen production.