Photoelectrocatalytic System as a Reaction Platform for Selective Radical–Radical Coupling

The selection of electrode material is crucial for the selectivity of electrochemical organic reactions, yet the fundamental principles behind this relationship remain largely unexplored. Recently, semiconductor photoelectrodes have garnered significant attention for organic synthesis due to their energy-harvesting capabilities and sustainable characteristics. Yet, in most cases, semiconductor photoelectrodes are only used as replacements for conventional conductive electrodes in electron-transfer reactions, rather than being utilized for their unique charge-transfer properties. Limited research has been conducted to understand the impact of semiconducting materials on reaction outcomes from an electrochemical perspective.
Herein, taking advantage of intrinsic charge-transfer features, we propose that a photoelectrocatalytic (PEC) system can be a promising platform for selective radical–radical coupling reactions. As a model reaction, radical trifluoromethylation of aromatic compounds is demonstrated with a hematite (Fe2O3) photoanode, without employing any homogeneous catalyst. The PEC platform exhibited superior mono- to bis-trifluoromethylated product selectivity compared to conventional electrochemical methods utilizing conductive anodes. Electroanalytical studies and density functional theory (DFT) calculations revealed that direct anodic oxidation of arenes is crucial for enhancing the mono-/bis- selectivity. Only the PEC configuration could generate sufficiently high-energy charge carriers with controlled kinetics due to the generation of photovoltage and charge-carrier recombination, which are characteristic features of semiconductor photoelectrodes. We anticipate that the understanding the physicochemical properties of semiconductor electrodes and their impact on reaction outcomes achieved by this study will stimulate the development of more efficient PEC organic synthesis methods and enhance our understanding of mechanistic features.