Clustering and assembly dynamics of a one-dimensional microphase former

TL;DR

This study investigates the structural and dynamical properties of disordered microphases in a 1D SALR model, revealing how clustering affects observables and how different algorithms influence equilibration, aiding future 3D microphase research.

Contribution

It provides a detailed analysis of disordered microphase formation in a 1D SALR model using transfer matrices and Monte Carlo simulations, highlighting the effects of clustering and algorithm efficiency.

Findings

Cluster moves significantly speed up mixing times.

Event chains are less effective in the clustering regime.

Disordered microphases exhibit distinct signatures in macroscopic observables.

Abstract

Both ordered and disordered microphases ubiquitously form in suspensions of particles that interact through competing short-range attraction and long-range repulsion (SALR). While ordered microphases are more appealing materials targets, understanding the rich structural and dynamical properties of their disordered counterparts is essential to controlling their mesoscale assembly. Here, we study the disordered regime of a one-dimensional (1D) SALR model, whose simplicity enables detailed analysis by transfer matrices and Monte Carlo simulations. We first characterize the signature of the clustering process on macroscopic observables, and then assess the equilibration dynamics of various simulation algorithms. We notably find that cluster moves markedly accelerate the mixing time, but that event chains are of limited help in the clustering regime. These insights will guide further study of three-dimensional microphase formers.