Pair interaction ordering in fluids with random interactions

TL;DR

This study uses molecular dynamics simulations to explore how multi-component fluids with randomly assigned pair interactions organize themselves, revealing a non-random, clustered state based on particle identities at high temperatures.

Contribution

It introduces a novel simulation approach to analyze particle-identity ordering in fluids with random interactions, highlighting the emergence of structured clustering.

Findings

Particles form clusters based on interaction parameters

The non-random state persists above the freezing transition

Clustering depends on the distribution of interaction parameters

Abstract

We use molecular dynamics simulations in 2d to study multi-component fluid in the limiting case where {\it all the particles are different} (APD). The particles are assumed to interact via Lennard-Jones (LJ) potentials, with identical size parameters but their pair interaction parameters are generated at random from a uniform or from a peaked distribution. We analyze both the global and the local properties of these systems at temperatures above the freezing transition and find that APD fluids relax into a non-random state characterized by clustering of particles according to the values of their pair interaction parameters (particle-identity ordering).