info:eu-repo/semantics/article
Simulated mechanical properties of finite-size graphene nanoribbons
Fecha
2020-01Registro en:
Aparicio, Emiliano; Tangarife, E.; Munoz, F.; Gonzalez, R. I.; Valencia, F. J.; et al.; Simulated mechanical properties of finite-size graphene nanoribbons; IOP Publishing; Nanotechnology; 32; 4; 1-2020
0957-4484
CONICET Digital
CONICET
Autor
Aparicio, Emiliano
Tangarife, E.
Munoz, F.
Gonzalez, R. I.
Valencia, F. J.
Careglio, Claudio Ariel
Bringa, Eduardo Marcial
Resumen
There are many simulation studies of mechanical properties of graphene nanoribbons (GNR), but there is a lack of agreement regarding elastic and plastic behavior. In this paper we aim to analyze mechanical properties of finite-size GNR, including elastic modulus and fracture, as a function of ribbon size. We present classical molecular dynamics simulations for three different empirical potentials which are often used for graphene simulations: AIREBO, REBO-scr and REAXFF. Ribbons with and without H-passivation at the borders are considered, and the effects of strain rate and different boundaries are also explored. We focus on zig-zag GNR, but also include some armchair GNR examples. Results are strongly dependent on the empirical potential employed. Elastic modulus under uniaxial tension can depend on ribbon size, unlike predictions from continuum-scale models and from some atomistic simulations, and fracture strain and progress vary significantly amongst the simulated potentials. Because of that, we have also carried out quasi-static ab-initio simulations for a selected size, and find that the fracture process is not sudden, instead the wave function changes from Blöch states to a strong interaction between localized waves, which decreases continuously with distance. All potentials show good agreement with DFT in the linear elastic regime, but only the REBO-scr potential shows reasonable agreement with DFT both in the nonlinear elastic and fracture regimes. This would allow more reliable simulations of GNRs and GNR-based nanostructures, to help interpreting experimental results and for future technological applications.