Prediction of glass transition temperatures of polyquinolines and polyquinoxalines

Abstract

Two molecular descriptors calculated directly from repeating units were used to predict the glass transition temperature (T g) values of polyquinolines and polyquinoxalines. These polymers were randomly divided into a training set (44 polymers) and a test set (19 polymers). By applying stepwise multiple linear regression analysis, the training set was used to construct a quantitative structure-property relationship model, which was evaluated externally with the test set. The descriptors used have definite physical meaning. Root mean square errors for the training set and the test set were 15.90 K and 17.33 K respectively, which were accurate and acceptable in comparison with existing models. The results indicate that chosen model containing only two molecular descriptors can be applied to predict T g of polyquinolines and polyquinoxalines, although these polymers have complicated structures.