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

Stochastic network description provide useful information about the link be tween the glass transition temperature T-g and network; connectivity. In mu lticomponent glasses, this permits to distinguish homogeneous compositions (random network) from inhomogeneous ones (local phase separation). The stoc hastic origin of the Gibbs-Di Marzio equation is predicted at low connectiv ity and the analytical expression of its parameter emerges naturally from t he calculation.