Numerical simulation of thermomagnetic carbon nanotube-graphene nanoplatelet polymeric conductive composites

Abstract

A numerical simulation based on Monte Carlo conductive network path finding method has been developed to investigate thermomagnetic carbon nanotube (CNT)-graphene nanoplatelet (GNP) polymeric conductive composites. The modeling methodology consists of three sequential phases: the initial estimation of resistivity followed by an assessment of the displacement of nanofillers and the resulting alterations in resistance by variations of intrinsic resistance with temperature. The formation of a continuous conductive path through the touching of the conductive fillers causes the resistivity to decrease 10 orders of magnitude in the percolation region. GNP gives a higher percolation threshold than CNT, with a 60% decrease with doubling its aspect ratio from 200. The material displayed a good response to strain, generating a gauge factor of about 3.6 for 0.5 vol% CNT polymer nanocomposite that reduced by 40% with doubling CNT volume fraction.