Toward quantitative structure-property relationships for charge transfer rates of polycyclic aromatic hydrocarbons

Quantitative structure-property relationships (QSPRs) have been developed and assessed for predicting the reorganization energy of polycyc ic aromatic hydrocarbons (PAHs). Preliminary QSPR models, based on a combination of molecular signature and electronic eigenvalue difference descriptors, have been trained using more than 200 PAHs. Monte Carlo cross-validation systematically improves the performance of the models through progressive reduction of the training set and selection of best performing training subsets. The final biased QSPR model yields correlation coefficients q² and r² of 0.7 and 0.8, respectively, and an estimated error in predicting reorganization energy of ±0.014 eV.