On the relationship between morphology and conductivity in nanosheet networks

Abstract

It is well-known that the morphology of nanostructured networks is closely linked to network properties. However, controlling and characterizing the morphology of networks of 2D nanosheets has not been explored. In this work, we use networks of liquid-exfoliated graphene nanosheets as a model system to examine the relationship between network morphology and conductivity in nanosheet networks. We use a combination of heat and pressure to controllably alter the morphology of the network, resulting in the annihilation of large pores (>40 nm) and improved nanosheet alignment within the sample. Such compression can result in a tenfold increase in network conductivity. Analysis shows both in-plane and out-of-plane conductivities to scale with porosity in line with percolation theory. The conductivity anisotropy was ∼3000 at low-porosity and was projected to fall to 1 in the limit of high porosity. Computational studies link the conductivity increase to an increase in network connectivity and a reduction in junction resistance as the porosity is decreased.