Quantitative methods for correlating dispersion and electrical conductivity in conductor-polymer nanostrand composites

The development of electrically conductive polymer composite systems continues to be an area of wide interest. In this work, a method is presented for quantifying the macro-scale dispersion characteristics of electrically conductive nickel nanostrands in polymer systems. A single polymer system is considered at multiple volume fractions of nanostrands, with variations in dispersion processing practices. Image analysis methods based on statistical homology parameters are developed to characterize samples of the dispersed nanostructure, including nearest neighbor distance, mean cluster size, area/perimeter ratios, and topological Betti number metrics. It is found that the Betti numbers are particularly well suited for monitoring nanostrands dispersed in polymer systems. Correlation of the dispersed structure to the electrical conductivity properties of the nanocomposite system is demonstrated. The method is well suited as a batch sampling technique for monitoring nanostructures during dispersion processes, and is also analogous for any dispersed system that involves highly structured materials.