Photoredox Chemistry with Organic Catalysts: Role of Computational Methods

Advancing Organic Photoredox Catalysis: Mechanistic Insight through Time-Resolved Spectroscopy

The rapid development of light-activated organic photoredox catalysts has led to the proliferation of powerful synthetic chemical strategies with industrial and pharmaceutical applications. Despite the advancement in synthetic approaches, a detailed understanding of the mechanisms governing these reactions has lagged. Time-resolved optical spectroscopy provides a method to track organic photoredox catalysis processes and reveal the energy pathways that drive reaction mechanisms. These measurements are sensitive to key processes in organic photoredox catalysis such as charge or energy transfer, lifetimes of singlet or triplet states, and solvation dynamics. The sensitivity and specificity of ultrafast spectroscopic measurements can provide a new perspective on the mechanisms of these reactions, including electron-transfer events, the role of solvent, and the short lifetimes of radical intermediates.

Enhancing the photocatalytic upcycling of polystyrene to benzoic acid: a combined computational-experimental approach for acridinium catalyst design

Converting polystyrene into value-added oxygenated aromatic compounds is an attractive end-of-life upcycling strategy. However, identification of appropriate catalysts often involves laborious and time-consuming empirical screening. Herein, after demonstrating the feasibility of using acridinium salts for upcycling polystyrene into benzoic acid by photoredox catalysis for the first time, we applied low-cost descriptor-based combinatorial in silico screening to predict the photocatalytic performance of a family of potential candidates. Through this approach, we identified a non-intuitive fluorinated acridinium catalyst that outperforms other candidates for converting polystyrene to benzoic acid in useful yields at low catalyst loadings (≤5 mol%). In addition, this catalyst also proved effective with real-life polystyrene waste containing dyes and additives. Our study underscores the potential of computer-aided catalyst design for valorizing polymeric waste into essential chemical feedstock for a more sustainable future.