Monte Carlo simulation of critical phenomena near the percolation threshold in two-dimensional networks consisting of curvy nanowires

Employing Monte Carlo simulations, we compute critical phenomena including the percolation probability and the critical curviness angle in 2D networks consisting of curvy nanowires. In most computational work, nanowires in 2D networks have been modeled as straight sticks. However, experimentally deposited nanowires exhibit some degree of curviness. We generate curved nanowires using third order Bezier curves characterized by the curviness angle. By computing percolation probability as a function of curviness angle at fixed nanowire density, we first extract the critical curviness angle at different densities using finite size scaling analysis. We find that the critical curviness angle increases with increasing density. Second, we find that nanowire alignment significantly changes the shape of the percolation probability versus curviness angle curve near the percolation threshold. We also extract the curl ratio critical exponent at the percolation threshold using finite size scaling. These results show that computational studies are an essential tool for providing insights into the insulator-to-conductor transition in nanowire networks, which are promising candidates for applications such as flexible transparent conductors, thin film transistors, and resistive switching memory.