Enhancing the conductivity of carbon nanotube filled blends by tuning their phase separated morphology with a copolymer

We describe an approach to engineer bi-continuous conductive blends of polymers and multiwall carbon nanotubes (MWNTs) by formation of a percolating network of MWNTs in one phase of the blend. Thereto, spinodal decomposition combined with compatibilization by an interfacially segregated random copolymer (rcp) is proposed. A systematic study of the effect of the concentration of the random copolymer poly(styrene-random-methyl methacrylate) (PS-r-PMMA) on the electrical conductivity of a phase separating poly[(alpha-methyl styrene)-co-acrylonitrile]/poly(methyl methacrylate) (P alpha MSAN/PMMA) blend with MWNTs was performed above the spinodal temperature (at 220 degrees C) and at room temperature. Compatibilization results in a huge conductivity increase, whereby blends with 0.5 wt% MWNTs and 0.25 wt% copolymer exhibit the same conductivity as percolating bi-phasic blends with 2 wt% MWNTs. In addition, the linear viscoelastic moduli show a power law increase with the concentration of copolymer. It was deduced that the observed increase in conductivity was caused by a substantial morphology refinement and increased degree of cocontinuity after copolymer addition leading to the formation of double percolated networks in the blends. These findings were corroborated with optical micrographs and scanning transmission electron microscopy (STEM) images for blends with 0.5 wt% and 2 wt% carbon nanotubes, respectively. The morphology changes can be explained by an interfacial tension reduction, which alters structure dynamics during annealing. The effectiveness of the long random copolymer in compatibilizing the blend is attributed to multiple interface crossings coupled with the ability of the copolymer blocks to anchor into the homopolymers. This simple approach can provide a pathway to develop low cost and ubiquitous high performance dielectric materials with ultra-low percolation thresholds. (C) 2015 Elsevier Ltd. All rights reserved.