Abstract

Vacancy defects are unavoidable in graphene sheets, and the random distribution of vacancy defects has a significant influence on the mechanical properties of graphene. This leads to a crucial issue in the research on nanomaterials. Previous methods, including the molecular dynamics theory and the continuous medium mechanics, have limitations in solving this problem. In this study, the Monte Carlo-based finite element method, one of the stochastic finite element methods, is proposed and simulated to analyze the buckling behavior of vacancy-defected graphene. The critical buckling stress of vacancy-defected graphene sheets deviated within a certain range. The histogram and regression graphs of the probability density distribution are also presented. Strengthening effects on the mechanical properties by vacancy defects were detected. For high-order buckling modes, the regularity and geometrical symmetry in the displacement of graphene were damaged because of a large amount of randomly dispersed vacancy defects.

Highlights

  • Graphene sheets is a promising nanomaterial with extraordinary properties for a wide range of applications

  • A detailed study of the elastic buckling of rectangular graphene sheets with different different amounts of vacancy defects was carried out using the MC–finite element method (FEM)

  • The random dispersion of amounts of vacancy defects was carried out using the MC–FEM

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Summary

Introduction

Graphene sheets is a promising nanomaterial with extraordinary properties for a wide range of applications. A great amount of academic research and experiments have been conducted to explore the properties of single-layer graphene sheets [1,2,3,4]. The existence of vacancy defects is unavoidable and difficult to predict. The large deviation observed in simulations and experiments has been attributed to the presence of defects in the nanotube structure [5,6]. Vacancy defects crucially impact on the mechanical properties of graphene sheets. Research on the vacancy defects of graphene sheets is essential to better understand the reasons of the described experimental deviations

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