Machine-Learning Predictions of Rate Constants of Internal Conversion Using Electronic and Structural Descriptors

Dataset for the article on machine-learning prediction of internal conversion (IC) rate constants for the electronic transition from the first excited singlet state to the ground state. It contains TDDFT-based electronic energies and IC rate constants, together with molecular descriptors (harmonic frequencies, Huang–Rhys factors, and NACME). The dataset covers 5292 derivatives of porphyrins, hetero[8]circulenes, and pyrromethenes.