Encoding alternatives for the prediction of polyacrylates glass transition temperature by quantitative structure-property relationships

Abstract

The glass transition temperature, Tg, is one of the most important properties of amorphous polymers. The ability to predict the Tg value of a polymer prior to its synthesis it is of great value. For this reason we performed a predictive Quantitative Structure-Property Relationships (QSPR) analysis of Tg. The study explored the best way to encode the polymers structure for this type of studies, finding that the optimal option is using three monomeric units. The best linear model constructed from 126 molecular structures incorporated eight molecular descriptors and showed very good predictive ability, being a very simple and straight forward method for the prediction of Tg for polyacrylates since three dimensional descriptors were not used.