Fig. 1: Thermally activated events in Cu-Zr metallic glasses. | npj Computational Materials

Fig. 1: Thermally activated events in Cu-Zr metallic glasses.

From: Predicting the propensity for thermally activated β events in metallic glasses via interpretable machine learning

Fig. 1

a Schematic description of the β-process in the context of potential energy landscape (PEL). Red dashes illustrate several activated pathways from a local minimum. In practice, we initiate 50 independent events around each atom along random activation pathways using ART and extract an ensemble-averaged activation energy Eact for each atom. b Distribution of Eact in the six model glasses as well as their combined Eact spectrum. The median (quantile 50%) and quantiles 5% and 95% are marked as vertical dashed lines in the combined Eact spectrum, and the median (quantile 50%) is marked in the spectrum of each model glass.

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