Exploring the Electrocatalytic Oxygen Evolution/Urea Oxidation Activity of Solution-Combusted CuO/MnO2: Machine Learning Insights from OER Performance

Abstract

Driven by strategic and environmental imperatives, replacing fossil fuels with hydrogen from water splitting as a suitable and promising substitute energy carrier is essential. The electrochemical oxygen evolution reaction (OER) plays a crucial role in water splitting, yet its practical implementation is restricted by complex multi-step mechanisms and sluggish kinetics. As an alternative, the urea oxidation reaction (UOR) offers an energy-saving route for hydrogen generation owing to its significantly lower thermodynamic potential than OER. Herein, CuO, MnO2, and CuO/MnO2 mixed oxides at molar ratios of 75:25, 50:50, and 25:75 were synthesized via solution combustion synthesis method at fuel-to-oxidizer ratio of 0.3. XRD and FE-SEM results indicated the crystalline CuO/MnO2 combusted powders with various morphology. HT-XRD demonstrate the high thermal stability of the prepared nanoparticles. Obtained results from BET/BJH, and AFM analyses depicted remarkable specific surface area of 104 m2.g-1 and surface roughness of 396 nm. Linear sweep voltammetry (LSV), and electrochemical impedance spectroscopy (EIS) exhibited outstanding bifunctional OER/UOR activity, achieving an overpotential (η100) of 250/90 mV, Tafel slope of 46/199 mV.dec-1 and charge-transfer resistance (Rct) of 0.75/4.52 Ω.cm2 for the equimolar CuO/MnO2 electrode. Chronopotentiometry (CHP) results confirmed excellent stability, maintaining the electrode performance for up to 30 h with only a 34-mV potential increment. This study employs machine learning to correlate physicochemical parameters with OER activity in the CuO/MnO2 system offering insights into optimizing next-generation and energy-efficient electrocatalysts.