On the Excess Entropy Scaling Law: a Potential Energy Landscape View

TL;DR

This paper investigates the connection between excess entropy and diffusion in liquids using simulations and machine learning, revealing that their relationship is rooted in the properties of the potential energy landscape.

Contribution

It introduces a landscape-based perspective to explain the excess entropy scaling law, linking it to different regimes of the potential energy landscape.

Findings

Exponential law correlates with the landscape-influenced regime.

Power-law relates to the free diffusion regime.

Supervised learning effectively determines excess entropy from simulations.

Abstract

The relationship between excess entropy and diffusion is revisited by means of large-scale computer simulation combined to supervised learning approach to determine the excess entropy for the Lennard-Jones potential. Results reveal that it finds its roots in the properties of the potential energy landscape (PEL). In particular the exponential law holding in the liquid is seen to be correlated with the landscape-influenced regime of the PEL while the fluid-like power-law corresponds to the free diffusion regime.