Here we quantify the electron transport properties of aligned carbon nanotube (CNT) networks as a function of the CNT length, where the electrical conductivities may be tuned by up to 10× with anisotropies exceeding 40%. Testing at elevated temperatures demonstrates that the aligned CNT networks have a negative temperature coefficient of resistance, and application of the fluctuation induced tunneling model leads to an activation energy of ≈ 14 meV for electron tunneling at the CNT-CNT junctions. Since the tunneling activation energy is shown to be independent of both CNT length and orientation, the variation in electron transport is attributed to the number of CNT-CNT junctions an electron must tunnel through during its percolated path, which is proportional to the morphology of the aligned CNT network.The quantum confinement mediated landmark properties of one dimensional materials, such as nanowires, nanofibers, and nanotubes, makes them attractive to a number of high value applications. Recently, carbon nanotubes (CNTs) were extensively studied in scalable aligned architectures, commonly known as forests, which promise the design and facile manufacture of multifunctional material architectures with tunable properties.

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Carbon nanotube (CNT) reinforced polymers are next-generation, high-performance, multifunctional materials with a wide array of promising applications. The successful introduction of such materials is hampered by the lack of a quantitative understanding of process-structure-property relationships. These relationships can be developed only through the detailed characterization of the nanoscale reinforcement morphology within the embedding medium. Here, we reveal the three-dimensional (3D) nanoscale morphology of high volume fraction (V(f)) aligned CNT/epoxy-matrix nanocomposites using energy-filtered electron tomography. We present an automated phase-identification method for fast, accurate, representative rendering of the CNT spatial arrangement in these low-contrast bimaterial systems. The resulting nanometer-scale visualizations provide quantitative information on the evolution of CNT morphology and dispersion state with increasing V(f), including network structure, CNT alignment, bundling and waviness. The CNTs are observed to exhibit a nonlinear increase in bundling and alignment and a decrease in waviness as a function of increasing V(f). Our findings explain previously observed discrepancies between the modeled and measured trends in bulk mechanical, electrical and thermal properties. The techniques we have developed for morphological quantitation are applicable to many low-contrast material systems.