Deep learning model to predict fracture mechanisms of graphene
Abstract Understanding fracture is critical to the design of resilient nanomaterials. Molecular dynamics offers a way to study fracture at an atomistic level, but is computationally expensive with limitations of scalability. In this work, we build upon machine-learning approaches for predicting nano...
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Autores principales: | Andrew J. Lew, Chi-Hua Yu, Yu-Chuan Hsu, Markus J. Buehler |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/6ca34e2dd038452d92d4550ba477cea5 |
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