Selectively Tuning the Substrate Adhesion Strength of Aligned Carbon Nanotube Arrays via Thermal Postgrowth Processing.

The excellent intrinsic properties of aligned nanofibers, such as carbon nanotubes (CNTs), and their ability to be easily formed into multifunctional 3D architectures motivate their use for a variety of commercial applications, such as batteries, chemical sensors for environmental monitoring, and energy harvesting devices. While controlling nanofiber adhesion to the growth substrate is essential for bulk-scale manufacturing and device performance, experimental approaches and models to date have not addressed tuning the CNT array-substrate adhesion strength with thermal processing conditions. In this work, facile "one-pot" thermal postgrowth processing (at temperatures = 700-950 °C) is used to study CNT-substrate pull-off strength for millimeter-tall aligned CNT arrays.

Substrate adhesion evolves non-monotonically with processing time in millimeter-scale aligned carbon nanotube arrays.

The advantageous intrinsic and scale-dependent properties of aligned nanofibers (NFs) and their assembly into 3D architectures motivate their use as dry adhesives and shape-engineerable materials. While controlling NF-substrate adhesion is critical for scaled manufacturing and application-specific performance, current understanding of how this property evolves with processing conditions is limited. In this report, we introduce substrate adhesion predictive capabilities by using an exemplary array of NFs, aligned carbon nanotubes (CNTs), studied as a function of their processing.

Aligned carbon nanotube morphogenesis predicts physical properties of their polymer nanocomposites.

Carbon nanostructure (CNS) based polymer nanocomposites (PNCs) are of interest due to the superior properties of the CNS themselves, scale effects, and the ability to transfer these properties anisotropically to the bulk material. However, measurements of physical properties of such materials are not in agreement with theoretical predictions. Recently, the ability to characterize the 3D morphology of such PNCs at the nanoscale has been significantly improved, with rich, quantitative data extracted from tomographic transmission electron microscopy (TEM).

Process-morphology scaling relations quantify self-organization in capillary densified nanofiber arrays.

Capillary-mediated densification is an inexpensive and versatile approach to tune the application-specific properties and packing morphology of bulk nanofiber (NF) arrays, such as aligned carbon nanotubes. While NF length governs elasto-capillary self-assembly, the geometry of cellular patterns formed by capillary densified NFs cannot be precisely predicted by existing theories. This originates from the recently quantified orders of magnitude lower than expected NF array effective axial elastic modulus (E), and here we show via parametric experimentation and modeling that E determines the width, area, and wall thickness of the resulting cellular pattern.

Synthesis of polymer bead nano-necklaces on aligned carbon nanotube scaffolds.

Here, we report the fabrication of aligned carbon nanotube (A-CNT)/conducting polymer (CP) heterostructures with both uniform conformal and periodic beaded polymer morphologies via oxidative chemical vapor deposition of poly(ethylenedioxythiophene). Periodic beaded CP morphologies are realized utilizing the Plateau-Rayleigh instability to transform the original uniform conformal film, yielding a beaded CP morphology with a >50% enhancement in specific surface area (SSA). Modeling indicates that this SSA increase originates from the internal volume of the A-CNTs becoming available for adsorption, and that these internal A-CNT surfaces, if they could be made accessible to electrolyte ions, could lead to >30% enhancement of specific gravimetric and volumetric capacitances of current state-of-the-art A-CNT/CP heterostructures.

Porosimetry and packing morphology of vertically aligned carbon nanotube arrays via impedance spectroscopy.

Vertically aligned one-dimensional nanostructure arrays are promising in many applications such as electrochemical systems, solar cells, and electronics, taking advantage of high surface area per unit volume, nanometer length scale packing, and alignment leading to high conductivity. However, many devices need to optimize arrays for device performance by selecting an appropriate morphology. Developing a simple, non-invasive tool for understanding the role of pore volume distribution and interspacing would aid in the optimization of nanostructure morphologies in electrodes.

Fabrication and morphology tuning of graphene oxide nanoscrolls.

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.

Packing morphology of wavy nanofiber arrays.

Existing theories for quantifying the morphology of nanofibers (NFs) in aligned arrays either neglect or assume a simple functional form for the curvature of the NFs, commonly known as the NF waviness. However, since such assumptions cannot adequately describe the waviness of real NFs, errors that can exceed 10% in the predicted inter-NF separation can result. Here we use a theoretical framework capable of simulating >10(5) NFs with stochastic three-dimensional morphologies to quantify NF waviness on an easily accessible measure of the morphology, the inter-NF spacing, for a range of NF volume fractions.

Mechanics of aligned carbon nanotube polymer matrix nanocomposites simulated via stochastic three-dimensional morphology.

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.

Aligned carbon nanotube array stiffness from stochastic three-dimensional morphology.

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.

Aligned carbon nanotube film enables thermally induced state transformations in layered polymeric materials.

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.

Exohedral physisorption of ambient moisture scales non-monotonically with fiber proximity in aligned carbon nanotube arrays.

Here we present a study on the presence of physisorbed water on the surface of aligned carbon nanotubes (CNTs) in ambient conditions, where the wet CNT array mass can be more than 200% larger than that of dry CNTs, and modeling indicates that a water layer >5 nm thick can be present on the outer CNT surface. The experimentally observed nonlinear and non-monotonic dependence of the mass of adsorbed water on the CNT packing (volume fraction) originates from two competing modes. Physisorbed water cannot be neglected in the design and fabrication of materials and devices using nanowires/nanofibers, especially CNTs, and further experimental and ab initio studies on the influence of defects on the surface energies of CNTs, and nanowires/nanofibers in general, are necessary to understand the underlying physics and chemistry that govern this system.

Coordination number model to quantify packing morphology of aligned nanowire arrays.

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.