Design Rules for Tuning Thermal Lifetimes of Arylazopyrazole Photoswitches

Predicting thermal relaxation rates in molecular photoswitches remains a major challenge, as competing reaction pathways and multiple electronic states govern their isomerization dynamics. Arylazopyrazoles exemplify this complexity while offering nearly quantitative bidirectional photoconversion and widely tunable thermal half-lives. Here, we map the isomerization landscapes of nearly 30,000 arylazopyrazole derivatives using a machine-learned interatomic potential trained on density functional theory data, enabling high-throughput simultaneous exploration of adiabatic and nonadiabatic pathways. The workflow identifies minima, transition states, and minimum-energy crossing points, allowing thermal relaxation rates to be computed at scale. Comparison with available experimental data demonstrates reliable prediction of absolute rate constants. Across chemical space, we uncover clear structure-mechanism-property relationships linking substituent position, pyrazole methylation, and electronic substitution patterns to mechanistic preference and overall relaxation kinetics. These results provide practical design rules for tuning the thermal stability of arylazopyrazole photoswitches and establish a general strategy for predicting relaxation kinetics in complex molecular switches.