Dynamics of viscous liquids and the Random Barrier Model

TL;DR

This study uses advanced simulation techniques to compare the Random Barrier Model and von Schweidler law in describing the dynamics of viscous Lennard-Jones liquids, finding the RBM generally provides a better fit and more accurate diffusion predictions.

Contribution

It demonstrates that the RBM, with no free parameters, better models the inherent dynamics of viscous liquids than the von Schweidler law, challenging existing assumptions.

Findings

RBM fits the inherent mean-squared displacement data better than von Schweidler law.

RBM predicts the diffusion coefficient more accurately from short-time data.

Despite its assumptions, RBM reproduces the inherent dynamics effectively.

Abstract

This paper combines the particle-swap Monte Carlo algorithm with long GPU molecular dynamics simulations to analyze the dynamics of a ternary Lennard-Jones glass-forming liquid in the extremely viscous regime. The focus is on the inherent dynamics, obtained by quenching configurations along the configuration-space trajectory into their inherent state. We compare how two functional forms, the von Schweidler law and the random barrier model (RBM) prediction in the extreme disorder limit, fit data for the inherent mean-squared displacement as a function of time. We find that the RBM, which has no dimensionless free parameters, generally fits the data better than the von Schweidler law, despite the latters one dimensionless free parameter. In particular, this implies that the RBM predicts the value of the diffusion coefficient from short-time simulation data more accurately than does the von Schweidler expression. It remains an open question why the RBM reproduces well the inherent data despite this models (unrealistic) assumption of identical energy minima.