AI-driven design of novel norbornadiene systems for molecular solar thermal application

Abstract

Certain molecular photoswitches can undergo isomerization to a metastable, high-energy state upon exposure to sunlight. These photoisomers can then revert to their ground state either thermally or under catalytic conditions, releasing the stored energy as heat. This reversible photochemical cycle forms the basis for molecular solar thermal (MOST) energy storage systems. Among the various photoswitchable scaffolds investigated, the norbornadiene (NBD)-quadricyclane (QC) isomeric pair stands out as particularly promising. For practical and efficient MOST performance, several key criteria must be met: absorption characteristics well matched to the solar spectrum (including appropriate λ_max and λ_onset values), minimal spectral overlap between the two isomers, a high photoisomerization quantum yield, an extended lifetime of the metastable QC isomer, and a substantial energy difference (ΔH) between the NBD and QC forms. Additionally, the compounds should be readily accessible and amenable to straightforward preparative scalability. To address these requirements systematically, we compiled an experimental dataset comprising approximately 250 literature-reported norbornadiene derivatives, each characterized with respect to relevant physicochemical and photochemical properties.