DOI: https://doi.org/10.29363/nanoge.hfuture.2024.021
Publication date: 27th February 2024
Funneling sunlight to perform chemical reactions by means of photoelectrochemical (PEC) devices opens an intriguing avenue to manufacture a wide range of chemicals in a sustainable manner. Amongst the many semiconductor photoanodes described in the literature, BiVO4 stands out for its early photocurrent onset potential and a relatively high saturation photocurrent, in some cases, reaching close-to-theoretical values. In recent years, the role of the surface composition of BiVO4 photoanodes at controlling the PEC oxygen evolution reaction (OER) has drawn increasing attention [1]. In fact, several reports have pointed out the critical role that the surface Bi:V ratio plays at controlling the performance and delivering benchmarking values [2]. However, to date, there exists a very limited portfolio of strategies to engineer the atomic termination in a controlled manner, while the actual mechanism whereby the surface composition governs the performance remains to be elucidated.
In this talk, a new methodology to tailor the surface termination of BiVO4 will be discussed, while the comprehensive characterization of the electrodes will unravel how the surface Bi:V ratio dictates the solar water oxidation performance [3]. Briefly, annealing in the presence of ammonium metavanadate affords to accurately control the surface Bi:V ratio. Subsequent analyses revealed that the improved response with the decreasing Bi:V ratio originated from the passivation of vanadium vacancies-related recombination centers. In addition, in an attempt to explore the prospects of chemical manufacturing using PEC devices, BiVO4 photoanodes were used to carry out the halogenation of various organic substrates, gaining new insights on the impact of the chemical environment and the reaction mechanism.
N.G. thanks the Spanish Ministry of Science & Innovation for the “Ramon y Cajal” Program (RYC2018-023888-I) and for support via de project TED2021-132697B-100. This project has also received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No.948829). J.L. acknowledges the funding support from the National Key Research and Development Program of China (Grant No. 2019YFE0123400), the Excellent Young Scholar Fund from the National Science Foundation of China (22122903), the Tianjin Distinguished Young Scholar Fund (20JCJQJC00260) and the “111” Project (Grant No. B16027). Q.W. acknowledges the funding support from the China Scholarship Council (202206200070).
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