Identity Ordering and Metastable Clusters in Fluids with Random Interactions

TL;DR

This study uses Langevin dynamics to explore how random binary interactions influence clustering and ordering in dense 2D fluids, revealing stronger effects with exponential interaction distributions and implications for alloy structuring.

Contribution

It introduces a comparative analysis of neighborhood identity ordering and metastable clustering in fluids with random interactions drawn from different distributions.

Findings

Stronger NIO and clustering in exponential distribution systems

Both systems exhibit metastable clusters near the liquid-solid transition

Implications for controlling alloy microstructures

Abstract

We use Langevin dynamics simulations to study dense two-dimensional systems of particles where all binary interactions are different (AID) in the sense that each interaction parameter is characterized by a randomly chosen number. We compare two systems that differ by the probability distributions from which the interaction parameters are drawn: uniform (U) and exponential (E). Both systems undergo neighborhood identity ordering (NIO) and form metastable clusters in the fluid phase near the liquid-solid transition but the effects are much stronger in E than in U systems. Possible implications of our results for the control of the structure of multicomponent alloys are discussed.