Glass transition temperature variation, cross-linking and structure in network glasses

TL;DR

This paper develops topological rules to predict how glass transition temperature varies with cross-linking and composition, distinguishing homogeneous from inhomogeneous glasses and deriving the Gibbs-Di Marzio equation analytically.

Contribution

It introduces general topological rules for predicting $T_g$ variation and provides an analytical derivation of the Gibbs-Di Marzio equation from network topology.

Findings

Topological rules accurately predict $T_g$ trends.

Chemical trends distinguish homogeneous and inhomogeneous glasses.

Analytical expression of Gibbs-Di Marzio parameter derived.

Abstract

We give general topological rules which very accurately predict the chemical trends in glass transition temperature $T_g$ variation as a function of cross-linking. In multicomponent glasses, these chemical trends permit to distinguish homogeneous compositions (random network) from inhomogeneous ones (local phase separation). The stochastic origin of the Gibbs-Di Marzio equation is predicted at low connectivity and the analytical expression of its parameter emerges naturally from the calculation.