Hydrogen production via electrolysis and ultrasound-assisted sonoelectrolysis: evaluating NiO, CoO, and MnO2 catalyst performance and process efficiency

Abstract

This study investigates the optimization of hydrogen production by comparing standard electrolysis with ultrasound-assisted sonoelectrolysis. The catalytic performance of NiO, CoO, and MnO₂ was evaluated at operating temperatures of 30 °C, 45 °C, and 60 °C to determine the most effective conditions for maximising H₂ production rate and energy efficiency. Using a design of experiments (DOE) framework and response surface methodology (RSM), predictive models were developed and experimentally validated. Sonoelectrolysis achieved a higher production rate (67.2 cm³ h⁻¹) than standard electrolysis (62 cm³ h⁻¹) but with reduced energy efficiency (2.14% vs. 4.37%) due to additional ultrasonic energy demands. For both methods, optimal conditions were consistently found at 60 °C with NiO as the catalyst. Statistical analysis showed that standard electrolysis followed a simple linear model, while sonoelectrolysis required a more complex quadratic model to capture the significant effects of temperature and catalyst type. The regression models were validated with low error rates (0.23–1.10%), providing a quantitative understanding of the performance gains and efficiency trade-offs in sonoelectrolysis, and offering guidance for advancing green hydrogen technologies.