Photoisomerization and Kinetic Characterization of Molecular Photoswitches Using a Semi-Automated Experimental System.

Molecular photoswitches occur widely in nature, where they play key roles in vision, and are increasingly utilized in emerging technologies. Their development, however, is often limited by the labor-intensive characterization of photochemical properties. This work presents an automated flow-based platform for efficient and reproducible photochemical characterization of molecular photoswitches. To accurately measure photoisomerization quantum yields, absorption profiles, and thermal back-conversion kinetics, the setup combines in-line UV-Vis spectroscopy with a programmable LED array. The automated fluid handling, temperature control, and real-time light flux calibration lead to improved reproducibility, reduced sample consumption, and minimal manual intervention compared to traditional methods. Large datasets are processed by a Python-based analytical framework that allows the extraction of kinetic and thermodynamic parameters from a variety of photoswitch classes. The platform is validated through testing known photoswitch systems, including azobenzene, and derivatives of bicyclooctadiene and norbornadiene, showing good agreement with literature values. By combining controlled irradiation, thermal relaxation studies, and automated data processing, this methodology provides a scalable framework for accelerating the discovery and characterization of functional molecular photoswitches.