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

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 twodimensional
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.