A novel approach to predict the electrical conductivity of nanocomposites by a weak interphase around graphene network

Herein, we offer a model for estimating the tunneling conductivity of polymer-graphene nanocomposites based on interfacial properties, the proportion of networked graphene, and the wettability value between the polymer medium and the filler. The interfacial properties are influenced by the minimum diameter of the nanosheets (Dc), whose conductivity can be transferred to the medium via interfacial conduction (tau). These parameters impact the actual aspect ratio and the volume proportion of the filler, which, in turn, control the onset of percolation and the proportion of nanosheets in the network. We apply all these parameters to develop a novel model for estimating the conductivity of graphene systems. The predictions obtained from this model across different parameter ranges are discussed. Additionally, experimental measurements are employed to evaluate the proposed equations. High filler conductivity enhances the nanocomposite's conductivity by a strong interfacial conduction. However, the conductivity cannot be transferred to the polymer medium under condition of weak interfacial conduction. Furthermore, a robust interphase and a small Dc contribute to increased conductivity. Ultimately, the developed equations accurately predict the onset of percolation and conductivity, validated by real experimental data.