Disconnecting structure and dynamics in glassy thin films

TL;DR

This study reveals that local microscopic structure does not account for the distinct dynamical behavior of nanometrically thin glassy films compared to bulk glasses, challenging existing structure-dynamics correlations.

Contribution

It demonstrates that machine-learning based structural indicators fail to predict dynamics in thin films, highlighting a disconnect between structure and dynamics in these systems.

Findings

Machine-learning methods do not detect key aspects of thin film dynamics.

Local structural features cannot distinguish particles in different film layers.

Structural correlations effective in bulk do not apply to thin films.

Abstract

Nanometrically thin glassy films depart strikingly from the behavior of their bulk counterparts. We investigate whether the dynamical differences between bulk and thin film glasses can be understood by differences in local microscopic structure. We employ machine-learning methods that have previously identified strong correlations between local structure and particle rearrangement dynamics in bulk systems. We show that these methods completely fail to detect key aspects of thin-film glassy dynamics. Furthermore, we show that no combination of local structural features drawn from a very general set of two- and multi-point functions is able to distinguish between particles at the center of film and those in intermediate layers where the dynamics are strongly perturbed.