ABSTRACT
String-like motions (SLMs)-cooperative, "snake"-like movements of particles-are crucial for dynamics in diverse glass formers. Despite their ubiquity, questions persist: Do SLMs prefer specific paths? If so, can we predict these paths? Here, in Al-Sm glasses, our isoconfigurational ensemble simulations reveal that SLMs do follow certain paths. By designing a graph neural network (GNN) to featurize the environment around directional paths, we achieve a high-fidelity prediction of likely SLM pathways, solely based on the static structure. GNN gauges a structural measure to assess each path's propensity to engage in SLMs, akin to a "softness" metric, but for paths rather than for atoms. Our GNN interpretation reveals the critical role of the bottleneck zone along a path in steering SLMs. By monitoring "path softness," we elucidate that SLM-favored paths transit from fragmented to interconnected upon glass transition. Our findings reveal that, beyond atoms or clusters, glasses have another dimension of structural heterogeneity: "paths."
ABSTRACT
Glassy materials are nonequilibrium and their energy states have crucial influences on properties. Recent studies have shown that oscillating deformations (vibrations) can cause either accelerated aging (lowering energy) or rejuvenation (elevating energy); however, the underlying atomic mechanisms remain elusive. Using metallic glasses (MGs) as model systems, we show that the vibration-induced accelerated aging is correlated with the strain field of the stringlike atomic motions stemming from the Johari-Goldstein (ß) relaxation, whereas the rejuvenation is associated with nonlinear response and the formation of nanoscale shear bands attributing to the activation of α relaxation. Both processes are affected by thermal fluctuations, which result in an optimal temperature for accelerated aging. These results suggest intrinsic correlations among relaxation dynamics, mechanical properties, and the vibration induced structural rearrangements in MGs.
