Distribution of local relaxation events in an aging 3D glass: spatio-temporal correlation and dynamical heterogeneity

TL;DR

This study uses molecular dynamics simulations to analyze the spatial and temporal distribution of microscopic relaxation events in an aging 3D glass, revealing insights into dynamical heterogeneity and cluster formation.

Contribution

It introduces an efficient algorithm to identify particle hops and maps relaxation events, providing new insights into cluster growth and correlations during aging.

Findings

Identification of relaxation event clusters and their size distributions.

Correlation scales define collaboratively rearranging particle groups.

Observation of a single dominant cluster prior to the four-point susceptibility peak.

Abstract

We investigate the spatio-temporal distribution of microscopic relaxation events, defined through particle hops, in a model polymer glass using molecular dynamics simulations. We introduce an efficient algorithm to directly identify hops during the simulation, which allows the creation of a map of relaxation events for the whole system. Based on this map, we present density-density correlations between hops and directly extract correlation scales. These scales define collaboratively rearranging groups of particles and their size distributions are presented as a function of temperature and age. Dynamical heterogeneity is spatially resolved as the aggregation of hops into clusters, and we analyze their volume distribution and growth during aging. A direct comparison with the four-point dynamical susceptibility {\chi}4 reveals the formation of a single dominating cluster prior to the {\chi}4 peak, which indicates maximally correlated dynamics. An analysis of the fractal dimension of the hop clusters finds slightly non-compact shapes in excellent agreement with independent estimates from four-point correlations.