Abstract
Abstract
Carbon nanotube (CNT) type and length are two key factors that affect the electrical behavior of CNT/polymer nanocomposites. However, numerical studies that consider these two factors simultaneously are limited. This paper presented a stochastic multiscale numerical model to predict the electrical conductivity and percolation threshold of polymer nanocomposites containing single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs). The combined effects of CNT type and length on the electrical conductivity and percolation threshold of the polymer nanocomposites were investigated. The model predictions were validated against experimental data of commercially available CNTs. Our results showed that the effect of CNT type varied based on both the length and aspect ratio of the CNTs. Long SWCNTs exhibited the greatest enhancement of the polymer’s electrical conductivity with the lowest percolation threshold among all the CNT types studied.
Funder
Natural Sciences and Engineering Research Council of Canada
Subject
Metals and Alloys,Polymers and Plastics,Surfaces, Coatings and Films,Biomaterials,Electronic, Optical and Magnetic Materials