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

M Micoulaut, GG Naumis - Europhysics Letters, 1999 - iopscience.iop.org
Stochastic network description provide useful information about the link between the glass
transition temperature T g and network connectivity. In multicomponent glasses, this permits
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.

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

M Micoulaut, GG Naumis - arXiv preprint cond-mat/9906190, 1999 - arxiv.org
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.
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