Abstract
QSPR models have been developed to predict of polycyclic aromatic hydrocarbons (PAHs) based on quantum chemical and integral spectroscopic descriptors. The first ionization potentials calculated from the energies of the highest occupied molecular orbital (HOMO), relative autocorrelation empirical parameters and the total number of electrons of non-ionized molecules were used as quantum chemical descriptors. Ionization potentials, electron affinities, boiling points, molecular masses, saturation vapor pressure of PAHs were studied as physical-chemical properties. Ionization potentials and electron affinities (IPs and EAs) are calculated by the use of density functional theory (DFT). The predictive power of resulting model is demonstrated by testing it on unseen data that were not used during model generation. The obtained models make it possible to estimate physical and chemical properties with sufficient accuracy for practical applications.
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