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Numerical simulation of graphene fracture using molecular mechanics based nonlinear finite elements AITranslate

University of Patras; University of Patras
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Publisher: Elsevier
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Abstract AITranslate

Highlights • The atomistic details have been encapsulated into the finite element formulation. • Typical fracture modes have been investigated using the proposed approach. • Graphene behavior depends on both load and graphene geometry. A previously developed specialty molecular mechanics based finite element for graphene is extended to enable prediction of mechanical failure and crack propagation in graphene sheets. The failure mechanisms at the atomistic level are based on bond breaking and elimination of atomic interactions. The developed molecular finite element method is employed to simulate modes I, II and III types of fracture in finite size graphene. Numerical results investigate the effect of chirality, and quantify crack propagation.

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Basic Information:

DOI:https://doi.org/10.1016/j.commatsci.2013.09.032

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Citation Information:

Highlights • The atomistic details have been encapsulated into the finite element formulation. • Typical fracture modes have been investigated using the proposed approach. • Graphene behavior depends on both load and graphene geometry. A previously developed specialty molecular mechanics based finite element for graphene is extended to enable prediction of mechanical failure and crack propagation in graphene sheets. The failure mechanisms at the atomistic level are based on bond breaking and elimination of atomic interactions. The developed molecular finite element method is employed to simulate modes I, II and III types of fracture in finite size graphene. Numerical results investigate the effect of chirality, and quantify crack propagation.

quote

GB/T 7714-2015 [1] T.C. Theodosiou, D.A. Saravanos. Computational Materials Science, 2014(82). DOI:10.1016/j.commatsci.2013.09.032.
MLA [1] T.C. Theodosiou, and D.A. Saravanos. Computational Materials Science, no. 82, 2014, https://doi.org/10.1016/j.commatsci.2013.09.032.
APA [1] T.C. Theodosiou, & D.A. Saravanos. (2014). Computational Materials Science(82). https://doi.org/10.1016/j.commatsci.2013.09.032
IEEE [1] T.C. Theodosiou and D.A. Saravanos, Computational Materials Science, no. 82, 2014, doi: 10.1016/j.commatsci.2013.09.032.