Properties of the energy landscape of network models for covalent glasses

TL;DR

This study explores the energy landscape of 2D network models for covalent glasses using the lid algorithm, revealing exponential growth in local states and minima, and identifying a peak in specific heat akin to the glass transition.

Contribution

It provides a detailed analysis of the energy landscape and configurational entropy of network models for covalent glasses, linking these properties to glass transition phenomena.

Findings

Exponential growth of local densities of states and minima.

Identification of a peak in excess specific heat at a critical temperature.

Correlation between energy landscape features and glass transition behavior.

Abstract

We investigate the energy landscape of two dimensional network models for covalent glasses by means of the lid algorithm. For three different particle densities and for a range of network sizes, we exhaustively analyse many configuration space regions enclosing deep-lying energy minima. We extract the local densities of states and of minima, and the number of states and minima accessible below a certain energy barrier, the 'lid'. These quantities show on average a close to exponential growth as a function of their respective arguments. We calculate the configurational entropy for these pockets of states and find that the excess specific heat exhibits a peak at a critical temperature associated with the exponential growth in the local density of states, a feature of the specific heat also observed in real glasses at the glass transition.