Premium
Modeling of Glass Transition Temperatures for Polymeric Coating Materials: Application of QSPR Mixture‐based Approach
Author(s) -
Petrosyan Lyudvig S.,
Sizochenko Natalia,
Leszczynski Jerzy,
Rasulev Bakhtiyor
Publication year - 2019
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.201800150
Subject(s) - quantitative structure–activity relationship , partition coefficient , copolymer , glass transition , molecular descriptor , cheminformatics , materials science , partition (number theory) , thermodynamics , chemistry , organic chemistry , computational chemistry , mathematics , polymer , stereochemistry , physics , combinatorics
Cross‐linked block copolymers are structurally complex, and utilization of traditional methods of molecular representation in chemoinformatics is only of limited applicability. Therefore, we introduced new techniques of structural representation for block copolymers. We developed additive and combinatorial approaches that treat a copolymer as a mixture system. In this approach, DRAGON descriptors are concentration‐weighted for all chemicals in the reaction mixture. As a proof of concept, we have studied glass transition temperatures of block copolymers of hydroxyalkyl‐ and dihydroxyalkyl carbamate terminated poly(dimethylsiloxane) oligomers with poly(‐caprolactone) and developed four quantitative structure‐property relationships (QSPR) models. The correlation coefficient (R 2 ) for mentioned QSPR models ranges from 0.851 to 0.911 for the training set. In addition to the newly introduced technique we found that the octanol−water partition coefficient and 3D‐MoRSE unweighted descriptors were the most important descriptors for the studied property. The results of the study demonstrated that all chemicals in reaction mixture influenced the glass transition temperatures.