Prediction of Refractive Index of Polymers Using Artificial Neural Networks
Gonzalo Astray, A. Cid, O. Moldes, Juan Angel Ferreiro-Lage, J. F. Gálvez, Juan Carlos Mejuto · Journal of Chemical & Engineering Data · 2010
Density functional theory (DFT) calculations were carried out in the prediction of the refractive index ( n ) of different polymers at the B3LYP/6-31G(d) level. A set of quantum chemical descriptors calculated from monomers of polymers, the energy of the lowest unoccupied molecular orbital ( E LUMO ), molecular average polarizability (α), heat capacity at constant volume ( C V ), and the most positive net atomic charge on hydrogen atoms in a molecule (e) were used to build a general quantitative structure−property relationship (QSPR) model for the refractive index. The proposed model gives the mean error of prediction of 1.048 % for the validation set.