Carbon nanotube network formation and configuration/morphology on reinforcing and conductive performance of polymer-based nanocomposites

Abstract

The present research work shows that carbon nanotube network formation and configuration/morphology play significant role in mechanical and conductive performance of polymer-based nanocomposites. Using several experimental techniques and theoretical approaches, the main entities of the established networks with aligned and random morphology were identified, the underlying mechanisms of network formation and the nature of its building blocks were revealed, and the corresponding network effects on the mechanical and electrical performances of such nanocomposites using single-walled carbon nanotubes in low- and high-density polyethylene matrices were thoroughly studied. Results show that the formed network is in majority constructed from nanotube bundles, considered as stiff rod-like Brownian particles, geometrically entangled at the critical volume fraction φcv (geometrical percolation threshold). The geometrical percolation threshold was found to be independent of the network morphology (aligned of injection molded samples and random of compression molded samples). Moreover, the mechanical and rheological properties were found to be independent of the nanocomposite morphology. However, the electrical performance of such materials was surprisingly different, strongly dependent on the morphology (aligned versus random as defined above). The random configuration significantly decreases the transition of the nanocomposites from isolator to conductor. The electrical percolation threshold, φcve, was found to be by one order of magnitude lower than the corresponding geometrical threshold, thus profoundly improving the conductivity of such nanocomposites. This key discovery enables the production of not only highly reinforced and conductive nanocomposites, but also the ones with remarkable conductivity and flexibility with minimal addition carbon nanotubes.