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Transition metal carbides are attractive, low-cost alternatives to Pt group metals, exhibiting multifunctional acidic, basic, and metallic sites for catalysis. Their widespread applications are often impeded by a high surface affinity for oxygen, which blocks catalytic sites. However, recent reports indicate that the α-MoC phase is a stable and effective cocatalyst for reactions in oxidative or aqueous environments. In this work, we elucidate the factors affecting the stability and catalytic activity of α-MoC under mild electrooxidation conditions (0–0.8 V SHE) using density functional theory calculations, kinetics-informed surface Pourbaix diagram analysis, electronic structure analysis, and cyclic voltammetry. Both computational and experimental data indicate that α-MoC is significantly more resistant to electrooxidation by H2O than β-Mo2C. This higher stability is attributed to structural and kinetic factors, as the Mo-terminated α-MoC surface disfavors substitutional oxidation of partially exposed, less oxophilic C* atoms by hindering CO/CO2 removal. The α-MoC surface exposes H2O-protected [MoC2O2] and [MoC(CO)O2] oxycarbidic motifs available for catalysis in a wide potential window. At higher potentials, they convert to unstable [Mo(CO)2O2], resulting in material degradation. Using formic acid as a probe molecule, we obtain evidence for Pt-like O*-mediated O–H and C–H bond activation pathways. The largest kinetic barrier, observed for the C–H bond activation, correlates with the hydrogen affinity of the site in the order O*/Mofcc > O*/Ctop > O*/Motop. To mitigate the site-blocking effect of surface-bound H2O and bidentate formate, doping with Pt was investigated computationally to make the surface less oxophilic and more carbophilic, indicating a possible design strategy toward more active and selective carbide electrocatalysts. 

The surface oxidation of molybdenum carbide nanoparticles was controlled by the electrochemical method. The impact of surface oxidation on catalytic properties was studied by both spectroscopic and computational methods.