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Computer Simulations of Undercooled Fluids and Glasses

  • Kurt Binder
  • Daniel Herzbach
  • Jürgen Horbach
  • Martin H. Müser
Chapter
Part of the Springer Series in Materials Science book series (SSMATERIALS, volume 93)

Abstract

An introduction to the Molecular Dynamics (MD) simulation of chemically realistic models for undercooled fluids and glasses is given, emphasizing silicatic materials such as molten silicon dioxide and its mixtures with sodium oxide and aluminium oxide, and comparing the simulation results to experimental data whenever possible.

A key ingredient to the computer simulation of materials is a sufficiently accurate description of the force fields with which the atoms interact. The need to simulate large systems for sufficiently long times makes the use of effective potentials for classical MD methods desirable. The validation of such effective potentials is best done studying the corresponding crystalline states of the material. As an example, the use of the so-called BKS-potential studying the structural and thermal properties of quartz crystals is described, and a comparison to other potentials is discussed.

When one studies undercooled fluids and glasses, a second problem enters, the disparity between experimental cooling rates and the much larger rates of the simulation. The extent to which a meaningful comparison to experiments is nevertheless possible is discussed. It is shown that the simulations can reproduce the structural and dynamic properties of molten silica (including self diffusion coefficients, viscosity, sound velocity, etc.) and its mixtures with other oxides. Evidence for the formation of sodium-rich channels responsible for anomalously large diffusion constants of sodium in mixtures containing sodium oxide will be discussed. No enhanced diffusion of aluminium occurs, however, due to “tricluster” formation in such mixtures.

Keywords

Monte Carlo Classical Molecular Dynamics Sodium Oxide Molecular Dynamics Result Verlet Algorithm 
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 Berlin Heidelberg 2007

Authors and Affiliations

  • Kurt Binder
    • 1
  • Daniel Herzbach
    • 1
  • Jürgen Horbach
    • 1
  • Martin H. Müser
    • 2
  1. 1.Institut für PhysikJohannes Gutenberg-Universität MainzMainzGermany
  2. 2.Department of Applied MathematicsUniversity of Western OntarioLondonCanada

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