Deep learning model to predict fracture mechanisms of graphene
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 nanoscopic fr...
Main Authors: | Lew, Andrew James, Yu, Chi-Hua, Hsu, Yu-Chuan, Buehler, Markus J |
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Other Authors: | Massachusetts Institute of Technology. Laboratory for Atomistic and Molecular Mechanics |
Format: | Article |
Published: |
Springer Science and Business Media LLC
2021
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Online Access: | https://hdl.handle.net/1721.1/132662 |
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