Percolation in networks of 1-dimensional objects: comparison between Monte Carlo simulations and experimental observations

Abstract

Planar networks composed of 1-dimensional nanometer scale objects such as nanotubes or nanowires have been attracting growing interest in recent years. In this work we directly compare the percolation threshold of silver nanowire networks to predictions from Monte Carlo simulations, focusing particularly on understanding the impact of real world imperfections on the percolation onset in these systems. This work initially determines the percolation threshold as calculated from an ideal system using Monte Carlo methods. On this foundation we address the effects of perturbations in length, angular anisotropy and radius of curvature of the 1-dimensional objects, in line with those observed experimentally in purposely fabricated samples. This work explores why two-dimensional stick models in the literature currently underestimate the percolation onset in real systems and identifies which of the network's features play the most significant role in that deviation.