Predicting the failure of two-dimensional silica glasses

Font-Clos F, Zanchi M, Hiemer S, Bonfanti S, Guerra R, Zaiser M, Zapperi S (2022)


Publication Type: Journal article

Publication year: 2022

Journal

Book Volume: 13

Journal Issue: 1

DOI: 10.1038/s41467-022-30530-1

Abstract

The sheer number of parameters in deep learning makes the physical interpretation of failure predictions in glasses challenging. Here the authors use Grad-CAM to reveal the role of topological defects and local potential energies in failure predictions.

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How to cite

APA:

Font-Clos, F., Zanchi, M., Hiemer, S., Bonfanti, S., Guerra, R., Zaiser, M., & Zapperi, S. (2022). Predicting the failure of two-dimensional silica glasses. Nature Communications, 13(1). https://dx.doi.org/10.1038/s41467-022-30530-1

MLA:

Font-Clos, Francesc, et al. "Predicting the failure of two-dimensional silica glasses." Nature Communications 13.1 (2022).

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