CRC 325

Assembly Controlled Chemical Photocatalysis

The goal of chemical photocatalysis is to create new structures and explore novel reactions by capturing light, ideally visible light. The dramatic advancements in the field over the past ten years have transformed organic synthesis. Light-driven reactions facilitate the generation of reactive intermediates, which are key components in bond-forming events. The selectivity and productivity of photocatalytic transformations depend significantly on the interactions between the substrate and the catalytically active species before, during, and after light excitation. However, for most reported photocatalytic and photochemical reactions, these interactions are ill-defined or unknown. This CRC aims to explore new frontiers in photocatalysis for organic synthesis through the designed control of catalyst-substrate interactions. The results of this research initiative will enable the broader application of light-initiated chemical transformations as essential tools for the selective and efficient synthesis of complex molecules in academic research and industrial production. The interdisciplinary research approach combines experimental, spectroscopic, and computational techniques to analyze and apply various catalyst-substrate interactions, including reversible coordination and reversible covalent bonding, hydrogen bonding, ionic and dipolar interactions, London forces, and solvation. During the first funding period, the CRC established itself as one of the most active research hubs in the field of chemical photocatalysis. Collaborative research endeavors have led to the identification of key interactions responsible for assembly control in photocatalysis. Building on the CRC's success, activities in the second funding period aim to leverage pivotal results from the first funding period and expand the diversity of the covered science. This will involve incorporating new spectroscopic techniques into the CRC and broadening expertise, particularly by integrating three additional Principal Investigators specializing in quantum-chemical calculations and machine learning.

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