Numerical simulation of graphene fracture using molecular mechanics based nonlinear finite elements AITranslate
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.
KeyWords AITranslate
Basic Information:
DOI:https://doi.org/10.1016/j.commatsci.2013.09.032
Chinese Library Classification Number:
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. |
