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.

The landmark theoretical properties of low dimensional materials have driven more than a decade of research on carbon nanotubes (CNTs) and related nanostructures. While studies on isolated CNTs report behavior that aligns closely with theoretical predictions, studies on cm-scale aligned CNT arrays (>10(10) CNTs) oftentimes report properties that are orders of magnitude below those predicted by theory. Using simulated arrays comprised of up to 10(5) CNTs with realistic stochastic morphologies, we show that the CNT waviness, quantified via the waviness ratio (w), is responsible for more than three orders of magnitude reduction in the effective CNT stiffness. Also, by including information on the volume fraction scaling of the CNT waviness, the simulation shows that the observed non-linear enhancement of the array stiffness as a function of the CNT close packing originates from the shear and torsion deformation mechanisms that are governed by the low shear modulus (∼1 GPa) of the CNTs.

The average inter-wire spacing in aligned nanowire systems strongly influences both the physical and transport properties of the bulk material. Because most studies assume that the nanowire coordination is constant, a model that provides an analytical relationship between the average inter-wire spacings and measurable physical properties, such as nanowire volume fraction, is necessary. Here we report a continuous coordination number model with an analytical relationship between the average nanowire coordination, diameter, and volume fraction. The model is applied to vertically aligned carbon nanotube (VACNT) and nanofiber (VACNF) arrays, and the effective nanowire coordination number is established from easily accessible measures, such as the nanowire spacing and diameter. VACNT analysis shows that the coordination number increases with increasing nanowire volume fraction, leading the measured inter-CNT spacing values to deviate by as much as 13% from the spacing values predicted by the typically assumed hexagonal packing. VACNF analysis suggests that, by predicting an inter-fiber spacing that is within 6% of the reported value, the continuous coordination model outperforms both square and hexagonal packing in real nanowire arrays. Using this model, the average inter-wire spacing of nanowire arrays can be predicted, thus allowing more precise morphology descriptions, and thereby supporting the development of more accurate structure-property models of bulk materials comprised of aligned nanowires.

The energy losses and geometric constraints associated with conventional curing techniques of polymeric systems motivate the study of a highly scalable out-of-oven curing method using a nanostructured resistive heater comprised of aligned carbon nanotubes (A-CNT). The experimental results indicate that, when compared to conventional oven based techniques, the use of an "out-of-oven" A-CNT integrated heater leads to orders of magnitude reductions in the energy required to process polymeric layered structures such as composites. Integration of this technology into structural systems enables the in situ curing of large-scale polymeric systems at high efficiencies, while adding sensing and control capabilities.

Tailorable anisotropic intrinsic and scale-dependent properties of carbon nanotubes (CNTs) make them attractive elements in next-generation advanced materials. However, in order to model and predict the behavior of CNTs in macroscopic architectures, mechanical constitutive relations must be evaluated. This study presents the full stiffness tensor for aligned CNT-reinforced polymers as a function of the CNT packing (up to ∼ 20 vol. %), revealing noticeable anisotropy. Finite element models reveal that the usually neglected CNT waviness dictates the degree of anisotropy and packing dependence of the mechanical behavior, rather than any of the usually cited aggregation or polymer interphase mechanisms. Combined with extensive morphology characterization, this work enables the evaluation of structure-property relations for such materials, enabling design of aligned CNT material architectures.

Here we report the synthesis of graphene oxide nanoscrolls (GONS) with tunable dimensions via low and high frequency ultrasound solution processing techniques. GONS can be visualized as a graphene oxide (GO) sheet rolled into a spiral-wound structure and represent an alternative to traditional carbon nano-morphologies. The scrolling process is initiated by the ultrasound treatment which provides the scrolling activation energy for the formation of GONS. The GO and GONS dimensions are observed to be a function of ultrasound frequency, power density, and irradiation time. Ultrasonication increases GO and GONS C-C bonding likely due to in situ thermal reduction at the cavitating bubble-water interface. The GO area and GONS length are governed by two mechanisms; rapid oxygen defect site cleavage and slow cavitation mediated scission. Structural characterization indicates that GONS with tube and cone geometries can be formed with both narrow and wide dimensions in an industrial-scale time window. This work paves the way for GONS implementation for a variety of applications such as adsorptive and capacitive processes.

The promise of enhanced and tailored properties motivates the study of one-dimensional nanomaterials, especially aligned carbon nanotubes (A-CNTs), for the reinforcement of polymeric materials. While CNTs have remarkable theoretical properties, previous work on aligned CNT polymer matrix nanocomposites (A-PNCs) reported mechanical properties that are orders of magnitude lower than those predicted by rule of mixtures. This large difference primarily originates from the morphology of the CNTs, because the CNTs that comprise the A-PNCs have significant local curvature commonly referred to as waviness. Here we present a simulation framework capable of analyzing 10(5) wavy CNTs with realistic three-dimensional morphologies to quantify the impact of waviness on the effective elastic modulus contribution of wavy CNTs. The simulation results show that due to the low shear modulus of the reinforcing CNT 'fibers', and large ([Formula: see text]) compliance contribution of the shear deformation mode, waviness reduces the effective stiffness contribution of the A-CNTs by two to three orders of magnitude. Also, the mechanical property predictions resulting from the simulation framework outperform those previously reported using finite element analysis since representative descriptions of the morphology are required to accurately predict properties of the A-PNCs. Further work to quantify the morphology of A-PNCs in three-dimensions, simulate their full non-isotropic constitutive relations, and predict their failure mechanisms is planned.

Polymer derived carbon ceramics are highly desirable for lightweight, high strength, extreme environment material architectures, but their mechanical performance as a function of structure and processing is not currently understood and cannot be predicted. In this study, the mechanical behavior for bulk-scale pyrolytic carbons (PyCs) made via polymer pyrolysis of phenolformaldehyde precursors are established as a function of heat treatment temperature and the resulting average nano-and meso-scale order and disorder via X-ray diffraction, Raman spectroscopy, and Fourier transform infrared spectroscopy. The PyCs exhibit crystallite evolution on both the atomic-and meso-scale for pyrolysis temperatures of 600 • C to 1000 • C, whereas only atomic-scale crystallite evolution is observed for pyrolysis temperatures of 1000 • C to 1400 • C. The measured Vickers hardness of the PyCs is observed to scale non-monotonically as a function of the pyrolysis temperature reaching a peak at ∼ 4 GPa for samples prepared at 1000 • C. New modeling results, based on the elastic constants of disordered graphite, indicate that this counter-intuitive Vickers hardness scaling, which is a decades-old open question, originates from the PyC inter-layer shear elastic constant and the crystallite aspect ratio evolution with processing temperature. PyCs studied here are shown to be the lightest super-hard materials, having Vickers hardness-to-density ratios that are comparable to super-hard carbides, oxides, nitrides, and phosphides.