Modeling of Electrical Conductivity of Nickel Nanostrand Filled Polymer Matrix Composites

A microstructure-based model for predicting the effective electrical conductivity of nickel nanostrand filled polymer composites is developed by using the Voronoi tessellation technique and the resistor network theory. To simulate the microstructures of nanostrand networks, Voronoi diagrams with different degrees of cell shape irregularity (amplitude a) and cell wall thickness non-uniformity (amplitude b) are generated by perturbing a regular packing of seeds. Ten resistor networks are constructed for each type of nanostrand network samples (with the same value of a or b) to obtain the mean value and standard deviation of the effective electrical conductivity. Kallmes and Corte's statistical model is employed to relate the utilized volume fraction and the initial volume fraction of nanostrands. The simulation results indicate that the effective electrical conductivity decreases as cell shapes (i.e., nanostrand spatial arrangement) become more irregular or cell wall thickness (i.e., nanostrand diameter) becomes less uniform. The use of a regular hexagonal network (lattice) of nanostrands can lead to a moderate improvement in the conductivity over that of a completely random network. The values of conductivity predicted by the current model are found to agree fairly well with existing experimental data and predictions based on the Monte Carlo technique. In addition, it is revealed that the polymer nanocomposites behave isotropically in terms of its electrical conductivity regardless of changes in the cell shape irregularity and the nanostrand volume fraction.