Glass transition temperature variation, cross-linking and structure in network glasses: A stochastic approach

Abstract

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