Enthalpy landscapes and the glass transition

John C. Mauro, Roger J. Loucks, Arun K. Varshneya, Prabhat K. Gupta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

A fundamental understanding of the glass transition is essential for enabling future breakthroughs in glass science and technology. In this paper, we review recent advances in the modeling of glass transition range behavior based on the enthalpy landscape approach. We also give an overview of new simulation techniques for implementation of enthalpy landscape models, including techniques for mapping the landscape and computing the long-time dynamics of the system. When combined with these new computational techniques, the enthalpy landscape approach can provide for the predictive modeling of glass transition and relaxation behavior on a laboratory time scale. We also discuss new insights from the enthalpy landscape approach into the nature of the supercooled liquid and glassy states. In particular, the enthalpy landscape approach provides for natural resolutions of both the Kauzmann paradox and the question of residual entropy of glass at absolute zero. We further show that the glassy state cannot be described in terms of a mixture of equilibrium liquid states, indicating that there is no microscopic basis for the concept of a fictive temperature distribution and that the glass and liquid are two fundamentally different states. We also discuss the connection between supercooled liquid fragility and the ideal glass transition.

Original languageEnglish (US)
Title of host publicationScientific Modeling and Simulations
EditorsSidney Yip, Tomas Diaz de la Rubia
Pages241-281
Number of pages41
DOIs
StatePublished - 2009

Publication series

NameLecture Notes in Computational Science and Engineering
Volume68 LNCSE
ISSN (Print)1439-7358

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • General Engineering
  • Discrete Mathematics and Combinatorics
  • Control and Optimization
  • Computational Mathematics

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