Mechanical properties of graphene nanowiggles

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPIn this work we have investigated the mechanical properties and fracture patterns of some graphene nanowiggles (GNWs). Graphene nanoribbons are finite graphene segments with a large aspect ratio, while GNWs are nonaligned periodic repetitions of graphene nanoribbons. We have carried out fully atomistic molecular dynamics simulations using a reactive force field (ReaxFF), as implemented in the LAMPPS (Large-scale Atomic/Molecular Massively Parallel Simulator) code. Our results showed that the GNW fracture patterns are strongly dependent on the nanoribbon topology and present an interesting behavior, since some narrow sheets have larger ultimate failure strain values. This can be explained by the fact that narrow nanoribbons have more angular freedom when compared to wider ones, which can create a more efficient way to accumulate and to dissipate strain/stress. We have also observed the formation of linear atomic chains (LACs) and some structural defect reconstructions during the material rupture. The reported graphene failure patterns, where zigzag/armchair edge terminated graphene structures are fractured along armchair/zigzag lines, were not observed in the GNW analyzed cases.16581418CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPSem informaçãoSem informação2013/08293-7Symposium RR - Large-Area Graphene and Other 2D-Layered Materials - Synthesis, Properties and Applications1 a 6 de Dezembro de 2013Boston, MA, Estados UnidosThis work was supported in part by the Brazilian Agencies CNPq, CAPES and FAPESP. The authors would like to thank the Center for Computational Engineering and Sciences at Unicamp for financial support through the FAPESP/CEPID Grant 2013/08293-7