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Afterword

  • K.L. NgaiEmail author
Chapter
Part of the Partially Ordered Systems book series (PARTIAL.ORDERED)

Abstract

It is hard to believe that a problem in physics introduced at the beginning of the scientific age still remains unsolved till now, the electronic and information age. The glass transition problem is such the case. The long history of the glass transition problem can be appreciated by citing just two among many general phenomena, namely the fractional exponential time dependence of relaxation in glass-forming systems and the super-Arrhenius temperature dependence of the relaxation time. One hundred and forty six years have gone by since the discoveries of the stretched exponential time relaxation function \(\phi (t) = \exp[-(t/\tau)^{\,1 - n}]\) by Kohlrausch in 1854 and almost a century since the super-Arrhenius temperature dependence of the relaxation time published by Vogel in 1921. However, till 2010, researchers are still engaged in various attempts to explain these two phenomena [24, 25, 26(a)–26(z)], let alone many other critical experimental facts found in diverse types of glassformers that have accumulated over the intervening years. Evidently at this time there is no universally accepted theoretical or even phenomenological solution of the glass transition problem. The importance of the glass transition problem in condensed matter physics and physical chemistry and the challenge for solution are recognized by Nobel laureates, many eminent scientists, and even recently the NY Times in a 2008 editorial for the benefit of the general public. The large number of papers related to the glass transition published in recent years is astounding and is evidence of the awareness of the importance of the problem by the research community. The problem is not only fundamental in physics and chemistry but also occurs in many practical applications involving a broad range of materials and processes.

Keywords

Glass Transition Coupling Model Structural Relaxation Basic Structural Unit Boson Peak 
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 Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.CNR-IPCF Associate, Dipartimento di FisicaUniversità di PisaPisaItaly
  2. 2.Formerly at Naval Research LaboratoryWashingtonUSA

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