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Computer simulation of models for the structural glass transition

  • K. Binder
  • J. Baschnagel
  • W. Kob
  • K. Okun
  • W. Paul
  • K. Vollmayr
  • M. Wolfgardt
Conference paper
Part of the Lecture Notes in Physics book series (LNP, volume 492)

Abstract

In order to test theoretical concepts on the glass transition, we investigate several models of glassy materials by means of Monte Carlo (MC) and Molecular Dynamics (MD) computer simulations. It is shown that also simplified models exhibit a glass transition which is in qualitative agreement with experiment and that thus such models are useful to study this phenomenon. However, the glass transition temperture as well as the structural properties of the frozen-in glassy phase depend strongly on the cooling history, and the extrapolation to the limit of infinitely slow cooling velocity is nontrivial, which makes the identification of the (possible) underlying equilibrium transition very difficult. In addition we demonstrate that microscopic properties are much stronger cooling rate dependent than macroscopic properties like the enthalpy or the density.

These points are exemplified with results for three types of models: The first one is a model for silica, a prototype of a strong glass former, the second is a Lennard-Jones model, which is a fragile glass former and the third is the bond-fluctuation model of polymer melts. For this third model we also review evidence for a growing correlation length at low temperatures resulting from finite size and surface effects. Furthermore we compute the configurational entropy of this lattice model as a function of temperature, which in turn allows us to perform a critical test of the Gibbs-di Marzio entropy theory. It is shown that the vanishing of the entropy in the latter theory gives a reasonable estimate of the glass transition region, but that the actual entropy stays positive down to zero temperature.

Keywords

Cool Rate Glass Transition Monte Carlo Mode Coupling Theory Gyration Radius 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag 1997

Authors and Affiliations

  • K. Binder
    • 1
  • J. Baschnagel
    • 1
  • W. Kob
    • 1
  • K. Okun
    • 1
  • W. Paul
    • 1
  • K. Vollmayr
    • 1
  • M. Wolfgardt
    • 1
  1. 1.Institut für PhysikJohannes Gutenberg-UniversitätMainzGermany

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