2019 Volume 20 Pages 84-91
In polymer material development, we often need to optimize some physical and chemical properties simultaneously. On the other hand, there is no established method to predict some different properties of polymers by the same approach. In this study, property values of various polymers were collected from the literature. Their relevance was considered by hierarchical clustering. PLSR models were constructed which predicted density, glass transition temperature, and dissolution parameter using descriptors obtained from the monomer unit structure information. R2 of the models were 0.88 ~ 0.97. The concept of informatics has shown the possibility to predict different polymer properties in a similar way.