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During dynamic atomic force microscopy (AFM), the deflection of a scanning cantilever generates multiple frequency terms due to the nonlinear nature of AFM tip-sample interactions. Even though each frequency term is reasonably expected to encode information about the sample, only the fundamental frequency term is typically decoded to provide topographic mapping of the measured surface. One of main reasons for discarding higher harmonic signals is their low signal-to-noise ratio. Here, we introduce a new design concept for multi-harmonic AFM, exploiting intentional nonlinear internal resonance for the enhancement of higher harmonics. The nonlinear internal resonance, triggered by the non-smooth tip-sample dynamic interactions, results in nonlinear energy transfers from the directly excited fundamental bending mode to the higher-frequency mode and, hence, enhancement of the higher harmonic of the measured response. It is verified through detailed theoretical and experimental study that this AFM design can robustly incorporate the required internal resonance and enable high-frequency AFM measurements. Measurements on an inhomogeneous polymer specimen demonstrate the efficacy of the proposed design, namely that the higher harmonic of the measured response is capable of enhanced simultaneous topography imaging and compositional mapping, exhibiting less crosstalk with an abrupt height change.

We report floating-electrode-based thin-film transistors (F-TFTs) based on a purified semiconducting single-walled carbon nanotube (swCNT) network for a high source–drain voltage operation. At a high source–drain voltage, a conventional swCNT-TFT exhibited poor transistor performance with a small on–off ratio, which was attributed to the reduced Schottky barrier modulation at a large bias. In the F-TFT device, an swCNT network channel was separated into a number of channels connected by floating electrodes. The F-TFTs exhibited a much higher on–off ratio than a conventional swCNT-TFT with a single channel. This work should provide an important guideline in designing swCNT-TFTs for high voltage applications such as displays.

We report the fabrication and electrical characteristics of scalable nanowall network devices and their gas sensor applications. For the network device fabrications, two-dimensional ZnO nanowall networks were grown on AlN/Si substrates with a patterned SiO(2) mask layer using selective-area metal-organic vapor-phase epitaxy. The ZnO nanowalls with c-axis orientation were heteroepitaxially grown on AlN/Si substrates, and were single-crystalline, as determined by x-ray diffraction and transmission electron microscopy. The electrical conductivity of the nanowall networks was measured as a function of nanowall dimensions. The conductance increased linearly with the channel width for widths larger than 1 µm, but saturated at 36 µS for widths below 1 µm. This conductance scaling behavior is explained by enhanced conduction through the regions near the edge of the patterned growth areas, where the density of the networks was higher. Gas sensor applications were investigated using the nanowall network devices, and highly sensitive gas detection was demonstrated.

Nanoscale sensors based on single-walled carbon nanotube (SWNT) networks have been considered impractical due to several fundamental limitations such as a poor sensitivity and small signal-to-noise ratio. Herein, we present a strategy to overcome these fundamental problems and build highly-sensitive low-noise nanoscale sensors simply by controlling the structure of the SWNT networks. In this strategy, we prepared nanoscale width channels based on aligned SWNT networks using a directed assembly strategy. Significantly, the aligned network-based sensors with narrower channels exhibited even better signal-to-noise ratio than those with wider channels, which is opposite to conventional random network-based sensors. As a proof of concept, we demonstrated 100 nm scale low-noise sensors to detect mercury ions with the detection limit of approximately 1 pM, which is superior to any state-of-the-art portable detection system and is below the allowable limit of mercury ions in drinking water set by most government environmental protection agencies. This is the first demonstration of 100 nm scale low-noise sensors based on SWNT networks. Considering the increased interests in high-density sensor arrays for healthcare and environmental protection, our strategy should have a significant impact on various industrial applications.

We present a simple but efficient method to prepare carbon nanotube (CNT)-based flexible devices embedded in polymer substrates. In this strategy, a methyl-terminated self-assembled monolayer is first coated on a solid substrate as a release layer, and CNT-network devices fabricated on it are directly transferred into a poly(dimethylsiloxane) (PDMS) mold, resulting in flexible CNT-network devices embedded in PDMS. The embedded circuits exhibit stable operation even after significant bending. We also propose Raman spectroscopy as a powerful tool to remotely characterize the CNT-network device structures covered by a polymer layer. As a proof of concept, we demonstrate DNA sensors utilizing the fabricated CNT-network devices.

In our previous paper (Arif et al 2011 Nanotechnology 22 355709), we developed a method to prepare metallic nanowire-graphene hybrid nanostructures and applied it to the fabrication of flexible field emission devices. For the quantitative analysis of the devices, the basic Fowler-Nordheim model was used. However, as pointed out by Forbes (2012 Nanotechnology 23 288001) the basic Fowler-Nordheim model should be corrected when the quantum confinement effect and the screening effect are considered. Forbes also developed a method that checks quantitatively the consistency between the experimental data and the theoretical assumptions. These discussions should provide an important theoretical framework in the quantitative analysis of our devices as well as large area field emitters in general.

We report a simple but efficient method to prepare metallic nanowire–graphene (MN–G) hybrid nanostructures at a low temperature and show its application to the fabrication of flexible field emission devices. In this method, a graphene layer was transferred onto an anodic alumina oxide template, and vertically aligned Au nanowires were grown on the graphene surface via electrodeposition method. As a proof of concept, we demonstrated the fabrication of flexible field emission devices, where the MN–G hybrid nanostructures and another graphene layer on PDMS substrates were utilized as a cathode and an anode for highly flexible devices, respectively. Our field emission device exhibited stable and high field emission currents even when bent down to the radius of curvature of 25 mm. This MN–G hybrid nanostructure should prove tremendous flexibility for various applications such as bio-chemical sensors, field emission devices, pressure sensors and battery electrodes.

We have developed a method to selectively assemble and align carbon nanotubes (CNTs) on soft substrates for use as flexible biosensors. In this strategy, a thin oxide layer was deposited on soft substrates via low temperature plasma enhanced chemical vapor deposition, and a linker-free assembly process was applied on the oxide surface where the assembly of carbon nanotubes was guided by methyl-terminated molecular patterns on the oxide surface. The electrical characterization of the fabricated CNT devices exhibited a typical p-type gating effect and 1/f noise behavior. The bare oxide regions near CNTs were functionalized with glutamate oxidase to fabricate selective biosensors to detect two forms of glutamate substances existing in different situations: L-glutamic acid, a neurotransmitting material, and monosodium glutamate, a food additive.