AI-Powered Mining of Highly Customized and Superior ESIPT-Based Fluorescent Probes.

ABSTRACT: Excited-state intramolecular proton transfer (ESIPT) has attracted great attention in fluorescent sensors and luminescent materials due to its unique photobiological and photochemical features. However, the current structures are far from meeting the specific demands for ESIPT molecules in different scenarios; the try-and-error development method is labor-intensive and costly. Therefore, it is imperative to devise novel approaches for the exploration of promising ESIPT fluorophores. This research proposes an artificial intelligence approach aiming at exploring ESIPT molecules efficiently. The first high-quality ESIPT dataset and a multi-level prediction system are constructed that realized accurate identification of ESIPT molecules from a large number of compounds under a stepwise distingu

SUBMITTER: Huang W 

PROVIDER: S-EPMC11425259 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature