Effect of nanowire curviness on the percolation resistivity of transparent, conductive metal nanowire networks

Abstract

We study the effect of nanowire curviness on the percolation resistivity of transparent, conductive metal nanowire networks by Monte Carlo simulations. We generate curvy nanowires as one-dimensional sticks using 3rd-order Bézier curves. The degree of curviness in the network is quantified by the concept of curviness angle and curl ratio. We systematically study the interaction between the effect of curviness and five other nanowire/device parameters on the network resistivity, namely nanowire density, nanowire length, device length, device width, and nanowire alignment. We find that the resistivity exhibits a power law dependence on the curl ratio, which is a signature of percolation transport. In each case, we extract the power-law scaling critical exponents and explain the results using geometrical and physical arguments. The value of the curl ratio critical exponent is not universal, but increases as the other nanowire/device parameters drive the network toward the percolation threshold. We find that, for randomly oriented networks, curviness is undesirable since it increases the resistivity. For well-aligned networks, on the other hand, some curviness is highly desirable, since the resistivity minimum occurs for partially curvy nanowires. We explain these results by considering the two competing effects of curviness on the percolation resistivity. The results presented in this work can be extended to any network, film, or nanocomposite consisting of one-dimensional nanoelements. Our results show that Monte Carlo simulations are an essential predictive tool for both studying the percolation transport and optimizing the electronic properties of transparent, conductive nanowire networks for a wide range of applications.