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

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