Efficient Monte Carlo simulation of a glass forming binary mixture

TL;DR

This paper introduces a hybrid Monte Carlo algorithm combining configurational bias swaps and parallel tempering to improve simulations of glass-forming mixtures, revealing limitations of previous thermodynamic extrapolations near the mode-coupling temperature.

Contribution

A novel hybrid Monte Carlo method for simulating glass-forming mixtures, enabling more accurate analysis near the mode-coupling temperature and challenging previous thermodynamic assumptions.

Findings

Extrapolation ansatz breaks down near Tmct

Reevaluation of Kauzmann temperature estimates

Validation of Adam-Gibbs relations across temperatures

Abstract

We propose and use a novel, hybrid Monte Carlo algorithm that combines configurational bias particle swaps with parallel tempering. We use this new method to simulate a standard model of a glass forming binary mixture above and below the so-called mode-coupling temperature, Tmct. We find that an ansatz that was used previously to extrapolate thermodynamic quantities to temperatures below Tmct breaks down in the vicinity of the mode-coupling temperature. Thus, previous estimates of the so-called Kauzmann temperature need to be reexamined. Also, we find that the Adam-Gibbs relations D ~ exp(-a/TSc) and tau ~ exp(b/TSc), which connect the diffusion coefficient D and the relaxation time tau with the configurational entropy Sc, are valid for all temperatures for which the configurational and vibrational contributions to the free energy decouple.