Driving photoelectrochemical water oxidation towards H2O2 via regulation of energy band structure of BiVO4

Release time:2025-07-14| Hits:

Key Words:PHOTOANODES; HOMOJUNCTION; PERFORMANCE; ZNO

Abstract:Photoelectrochemical water oxidation (PEC-WO) as a green and sustainable route to produce H2O2 has attracted extensive attentions. However, water oxidation to H2O2 via a 2e pathway is thermodynamically more difficult than to O2 via a 4e pathway. Herein, with a series of BiVO4-based photoanodes, the decisive factors determining the PEC activity and selectivity are elucidated, combining a comprehensive experimental and theoretical investigations. It is discovered that the ZnO/BiVO4 photoanode (ZnO/ BVO) forms a Type-II heterojunction in energy level alignment. The accelerated photogenerated charge separation/transfer dynamics generates denser surface holes and higher surface photovoltage. Therefore, the activity of water oxidation reaction is promoted. The selectivity of PEC-WO to H2O2 is found to be potential-dependent, i.e., at the lower potentials (PEC-dominated), surface hole density determines the selectivity; and at the higher potentials (electrochemical-dominated), surface reaction barriers govern the selectivity. For the ZnO/BVO heterojunction photoanode, the higher surface hole density facilitates the generation of OH and the subsequent OH /OH coupling to form H2O2, thus rising up with potentials; at the higher potentials, the 2-electron pathway barrier over ZnO/BVO surface is lower than over BVO surface, which benefits from the electronic structure regulation by the underlying ZnO alleviating the over-strong adsorption of *OH on BVO, thus, the two-electron pathway to produce H2O2 is more favored than on BVO surface. This work highlights the crucial role of band energy structure of semiconductors on both PEC reaction activity and selectivity, and the knowledge gained is expected to be extended to other photoeletrochemical reactions. (c) 2024 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.

Volume:103

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Translation or Not:no