Prediction of the Glass-Transition Temperatures of Linear Homo/Heteropolymers and Cross-Linked Epoxy Resins

This work proposes
a unified approach to predict glass-transition
temperatures (Tg) of linear homo/heteropolymers
and cross-linked epoxy resins by machine-learning approaches based
on descriptors of reagents undergoing polymerization, represented
in a formal way such as to encompass all three scenarios: linear homo-
and heteropolymers plus network heteropolymers. The “formal”
representation of reagents is a problem-specific, herein designed
standardization protocol of compounds, unlike typical structure curation
rules in chemoinformatics. For example, heteropolymers are represented
by the two partner reagents, whereas homopolymers are depicted as
formal “heteropolymers” with identical partners. The
key rule proposed here is to choose “formal” monomers
such as to minimize the number of marked atoms, involved in bonds
being formed or changing bond order. Accordingly, carbonyl compounds
are rendered as the less-stable vinyl alcohol tautomer, following
the same formalism as in olefin polymerization, to minimize the total
number of formal polymerization mechanisms and herewith provide the
most general framework encompassing a maximum of polymerization processes.
ISIDA (in silico design and data analysis) fragment counts with special
status given to the “marked atoms” participating in
the polymerization process were combined using “mixture”
strategies to generate the final polymer descriptors. Three predictive
models based on SVR (support vector regression) are discussed here.
After reproducing results of Katritzky et al. with a local model applicable
only to linear homo/heteropolymers, an epoxy resin-specific model
applicable to both linear and network forms was built. Eventually,
the general model applicable to all these families was constructed.
In 12 × repeated 3-fold cross-validation challenges, it displayed
the highest accuracy of Q2 = 0.920, RMSE
= 34.3 K over the training set of 270 polymers, and R2 = 0.779, RMSE 35.9 K for an external test set of 119
polymers. GTM (Generative Topographic Mapping) analysis produced a
2D map of “polymer chemical space”, highlighting the
various classes of polymers included in the study and their relationship
with respect to Tg values. The epoxy-specific
and general models are publicly available on our web server: http://infochim.u-strasbg.fr/webserv/VSEngine.html.