2024/06/09 by Sean A. Ridout, Andrea J. Liu, Ridout, Sean A. +1
Materials Science · #FOS: Physical sciences #Material Dynamics and Properties #Soft Condensed Matter (cond-mat.soft)
paper · pdf · doi:10.48550/arxiv.2406.05868
openalex publication_date 2024/06/09 · openalex created_date 2024/06/12 · openalex updated_date 2026/07/28
The dynamics of supercooled liquids slow down and become increasingly heterogeneous as they are cooled. Recently, local structural variables identified using machine learning, such as "softness", have emerged as predictors of local dynamics. Here we construct a model using softness to describe the structural origins of dynamical heterogeneity in supercooled liquids. In our model, the probability of particles to rearrange is determined by their softness, and each rearrangement induces changes in the softness of nearby particles, describing facilitation. We show how to ensure that these changes respect the underlying time-reversal symmetry of the liquid's dynamics. The model reproduces the salient features of dynamical heterogeneity, and demonstrates how long-ranged dynamical correlations can emerge at long time scales from a relatively short softness correlation length.