Predicting the failure of two-dimensional silica glasses

Being able to predict the failure of materials based on structural information is a fundamental issue with enormous practical and industrial relevance for the monitoring of devices and components. Thanks to recent advances in deep learning, accurate failure predictions are becoming possible even for...

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Detalles Bibliográficos
Autores principales: Font-Clos, Francesc, Zanchi, Marco, Hiemer, Stefan, Bonfanti, Silvia, Guerra, Roberto, Zaiser, Michael, Zapperi, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122924/
https://www.ncbi.nlm.nih.gov/pubmed/35595727
http://dx.doi.org/10.1038/s41467-022-30530-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122924/
https://www.ncbi.nlm.nih.gov/pubmed/35595727
http://dx.doi.org/10.1038/s41467-022-30530-1

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