Abstract
A model for the heterogeneity of local dynamics in polymer and other glass-forming materials is provided here. The fundamental characteristics of the glass transition phenomenology emerge when simulating a condensed matter open cluster that has a strong interaction with its heterogeneous environment. General glass transition features, such as non-exponential structural relaxations, the slowing down of relaxation times with temperature and specific off-equilibrium glassy dynamics can be reproduced by non-Markovian dynamics simulations with the minimum computer resources. Non-Markovian models are shown to be useful tools for obtaining insights into the complex dynamics involved in the glass transition phenomenon, including whether or not there is a need for a growing correlation length or the relationship between the non-exponentiality of structural relaxations and dynamic heterogeneity.
Highlights
When a liquid is subjected to cooling, a crystallization process can be induced within it, in some cases its molecules do not become ordered and the liquid continues with disordered but less mobile structure, and turns into a glass
The evolution of systems around glass transition in computer simulations can be represented by complex Markov processes [4] in which the transitions among the distinct configurations are given by certain probabilities that depend on the model
The energy starts to rise with temperature, arising the glass transition phenomenon, since the probability of transitions towards high energy levels increases at high temperatures
Summary
When a liquid is subjected to cooling, a crystallization process can be induced within it, in some cases its molecules do not become ordered and the liquid continues with disordered but less mobile structure, and turns into a glass. This process is frequently found in polymers and other materials. The general purpose molecular dynamics or Monte Carlo methods are complex and require a large amount of computer resources New algorithms such as the swap Monte Carlo and other related protocols [5,6] have significantly reduced the computation time, they focus on size polydisperse fluids. Even in very simplified models, the evolution of a glass towards equilibrium or the calculation of its own equilibrium state becomes difficult and at very low temperatures requires long computational times
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