Abstract

Electrophotocatalytic C-H hydroxylation of benzene is an emerging green technology with high potential for producing phenol in one step. However, it is still limited by efficiency and scale-up challenges in batch process. In this study, a novel electrophotochemical flow microreactor was designed and manufactured using 3D printing technology. Static mixers were incorporated to enhance the mixing. The effect of various parameters, such as electrode materials, reaction time, potential, and reactant concentration, etc., on the continuous synthesis of phenol in the as-developed microreactor was investigated. Furthermore, machine learning (ML) algorithms were employed to explore the impact of these parameters on the reaction efficiency. With cost-effective electrodes, higher phenol productivity was achieved in the present flow microreactor when comparing with batch counterpart and literature value. This study offers insights into the optimization of electrophotochemical microreactor for the hydroxylation of benzene, and provides guidance for exploring sustainable electrophotocatalytic organic synthesis in flow.

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