Promoting oxygen evolution in proton exchange membrane water electrolysis: controlling the oxidation state of electrochemically fabricated iridium-cobalt oxide catalysts

Abstract

The harsh corrosive environment and sluggish oxygen evolution reaction (OER) kinetics at the anode of proton exchange membrane water electrolysis (PEMWE) cells warrant the use of excess Ir, thereby hindering large-scale industrialization. To mitigate these issues, the present study aimed at fabricating a robust low-Ir-loading electrode via one-pot synthesis for efficient PEMWE. The pre-electrode was first prepared by alloying through the co-electrodeposition of Ir and Co, followed by the fabrication of Ir- Co oxide (Co-incorporated Ir oxide) electrodes via electrochemical dealloying. Two distinct dealloying techniques resulted in a modified valence state of Ir, and the effects of Co incorporation on the activity and stability of the OER catalysts were clarified using density functional theory (DFT) calculations, which offered theoretical insights into the reaction mechanism. While direct experimental validation of the oxygen evolution mechanism remains challenging under the current conditions, DFT-based theoretical modeling provided valuable perspectives on how Co incorporation could influence key steps in oxygen evolution catalysis. The Ir-Co oxide electrode with a selectively modulated valence state showed impressive performance with an overpotential of 258 mV at 10 mA cm-2, a low Tafel slope of 29.4 mV dec-1, and stability for 100 hat 100 mA cm-2 in the OER, in addition to a low overpotential of 16 mV at -10 mA cm-2 and high stability for 24 h in the hydrogen evolution reaction. The PEMWE cell equipped with the bifunctional Ir-Co oxide electrode as the anode and cathode exhibited outstanding performance (11.4 A cm-2 at 2.3 Vcell) despite having a low noble-metal content of 0.4 mgNM cm-2. (c) 2025 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. and Science Press. All rights are reserved, including those for text and data mining, AI training, and similar technologies.