Investigation of mechanical strength of 2D nanoscale structures using a molecular dynamics based computational intelligence approach

Abstract

A molecular dynamics (MD) based computational intelligence (CI) approach is proposed to investigate the Young modulus of two graphene sheets: Armchair and Zigzag. In this approach, the effect of aspect ratio, the temperature, the number of atomic planes and the vacancy defects on the Young modulus of two graphene sheets are first analyzed using the MD simulation. The data obtained using the MD simulation is then fed into the paradigm of a CI cluster comprising of genetic programming, which was specifically designed to formulate the explicit relationship of Young modulus of two graphene structures. We find that the MD-based-CI model is able to model the Young modulus of two graphene structures very well, which compiles in good agreement with that of experimental results obtained from the literature. Additionally, we also conducted sensitivity and parametric analysis and found that the number of defects has the most dominating influence on the Young modulus of two graphene structures.