Gaussian excitations model for glass-former dynamics and thermodynamics

TL;DR

This paper introduces a Gaussian excitations model that links thermodynamics and dynamics of glass-forming liquids, explaining fragility and relaxation behavior through a hierarchical excitation process and energy landscape fluctuations.

Contribution

It presents a three-parameter model connecting excess entropy, heat capacity, and relaxation dynamics, revealing the role of energy landscape ruggedness in glass transition phenomena.

Findings

Fragile behavior signals an impending hidden first-order transition.

Relaxation rates exhibit super-Arrhenius temperature dependence.

Configurational heat capacity influences relaxation times, aligning with experimental data.

Abstract

We describe a model for the thermodynamics and dynamics of glass-forming liquids in terms of excitations from an ideal glass state to a Gaussian manifold of configurationally excited states. The quantitative fit of this three parameter model to the experimental data on excess entropy and heat capacity shows that ``fragile'' behavior, indicated by a sharply rising excess heat capacity as the glass transition is approached from above, occurs in anticipation of a first-order transition -- usually hidden below the glass transition -- to a ``strong'' liquid state of low excess entropy. The dynamic model relates relaxation to a hierarchical sequence of excitation events each involving the probability of accumulating sufficient kinetic energy on a separate excitable unit. Super-Arrhenius behavior of the relaxation rates, and the known correlation of kinetic with thermodynamic fragility, both follow from the way the rugged landscape induces fluctuations in the partitioning of energy between vibrational and configurational manifolds. A relation is derived in which the configurational heat capacity, rather than the configurational entropy of the Adam Gibbs equation, controls the temperature dependence of the relaxation times, and this gives a comparable account of the experimental observations.