Calorimetric glass transition explained by hierarchical dynamic facilitation

TL;DR

This paper presents a hierarchical facilitation model based on the East-model to explain the calorimetric behavior of glasses during transition, linking dynamic heterogeneity and non-equilibrium thermodynamics.

Contribution

It introduces a hierarchical facilitation framework that quantitatively explains the glass transition and calorimetric responses using localized excitations and their correlations.

Findings

Model predicts heat capacity differences on cooling and heating.

Correlation length increases with slower cooling rates.

Model parameters match experimental calorimetry data.

Abstract

The glass transition refers to the non-equilibrium process by which an equilibrium liquid is transformed to a non-equilibrium disordered solid, or vice versa. Associated response functions, such as heat capacities, are markedly different on cooling than on heating, and the response to melting a glass depends markedly on the cooling protocol by which the glass was formed. This paper shows how this irreversible behavior can be interpreted quantitatively in terms of an East-model picture of localized excitations (or soft spots) in which molecules can move with a specific direction, and from which excitations with the same directionality of motion can appear or disappear in adjacent regions. As a result of this facilitated dynamics, excitations become correlated in a hierarchical fashion. These correlations are manifested in the dynamic heterogeneity of the supercooled liquid phase. While equilibrium thermodynamics is virtually featureless, a non-equilibrium glass phase emerges when the model is driven out of equilibrium with a finite cooling rate. The correlation length of this emergent phase is large and increases with decreasing cooling rate. A spatially and temporally resolved fictive temperature encodes memory of its preparation. Parameters characterizing the model can be determined from reversible transport data, and with these parameters, predictions of the model agree well with irreversible differential scanning calorimetry.