3D self-consistent percolative model for networks of randomly aligned carbon nanotubes

Abstract

A numerical percolative model for simulations of random networks of carbon nanotubes is presented. This algorithm takes into account the real 3D nature of these networks, allowing for a better understanding of their electrical properties. The nanotubes are modeled as non-rigid bendable cylinders with geometrical properties derived according to some statistical distributions inferred from the experiments. For the transport mechanisms we refer to the theory of one-dimensional ballistic channels which is based on the computation of the density of states. The behavior of the entire network is then simulated by coupling a SPICE program with an iterative algorithm that calculates self-consistently the electrostatic potential and the current flow in each node of the network. We performed several simulations on the resistivity of networks with different thicknesses and over different simulation domains. Our results confirm the percolative nature of the electrical transport, which are more pronounced in films close to their percolation threshold.