Electrical conductivity of random metallic nanowire networks: An analytical consideration along with computer simulation

TL;DR

This paper develops an analytical model for the electrical conductivity of random metallic nanowire networks, validated by computer simulations, providing insights into how physical parameters influence conductivity.

Contribution

It introduces a mean-field analytical model for nanowire network conductivity and validates it through computer simulations across various physical parameter regimes.

Findings

Analytical model accurately predicts conductivity over a wide density range.

Conductivity depends on wire density, resistances, and junction properties.

Simulation results agree with theoretical predictions.

Abstract

We have proposed an analytical model for the electrical conductivity in random, metallic, nanowire networks. We have mimicked such random nanowire networks as random resistor networks (RRN) produced by the homogeneous, isotropic, and random deposition of conductive zero-width sticks onto an insulating substrate. We studied the electrical conductivity of these RRNs using a mean-field approximation. An analytical dependency of the electrical conductivity on the main physical parameters (the number density and electrical resistances of these wires and of the junctions between them) has been derived. Computer simulations have been performed to validate our theoretical predictions. We computed the electrical conductivity of the RRNs against the number density of the conductive fillers for the junction-resistance-dominated case and for the case where the wire resistance and the junction resistance were equal. The results of the computations were compared with this mean-field approximation. Our computations demonstrated that our analytical expression correctly predicts the electrical conductivity across a wide range of number densities.