A general QSPR model for the prediction of theta (lower critical solution temperature) in polymer solutions with topological indices

Abstract

The quantitative structure-property relationship (QSPR) study was performed between topological indices representing the molecular structures and theta (LCST, lower critical solution temperature) with a database of 169 data points including 12 polymers and 67 solvents. A linear 10-parameter model was developed to predict theta (LCST) with squared correlation coefficient (R(2)) of 0.8874 and standard error of estimation (SEE) of 24.57 for the training set of 112 systems. The mean relative error (MRE) for the calculation of theta (LCST) was 3.49%. The stability of the proposed model was validated using Leave-One-Out cross-validation and randomization experiments. The model is generally predictive and requires only topological indices during the predictions with the advantage of the relative ease in calculating descriptors which makes it easy to apply. A satisfactory MRE of 4.95% for a test set of 57 systems indicates that the model would be very useful to obtain reliable estimates of theta (LCST) in polymer solutions before they are actually synthesized.