Unconventional Ni–P alloy-catalyzed CVD of carbon coil-like micro- and nano-structures

Conventional catalyzed thermal CVD of carbon microcoils commonly suffers from poor control of the coil shape and morphology and rarely reaches the nanoscale size range. This article reports on an unconventional Ni-P alloy-catalyzed, high-throughput, highly reproducible CVD of ultra-long carbon coil-like micro- and nano-structures using acetylene precursor at relatively low process temperatures. Helical carbon microcoils with consistently uniform, circular cross-sections and a high degree of crystallinity have been synthesized at 750 °C. A further reduction of the temperature to 650 °C led to the growth of ultra-long (up to several mm) wave-like carbon nanofibers made of two nanowires with the diameters in the 100-200 nm range. The results of the XRD and Raman analysis reveal that the nanofibers feature only a slightly more disordered structure compared to the microcoils. Our results suggest that morphology and structure of the carbon coil-like micro- and nano-structures can be tailored by the appropriate alloying of the catalyst and the choice of the CVD process parameters.

Nanopowder management and plasma parameters in nanofabrication of low-dimensional quantum structures in reactive silane-based plasmas

Management of nanopowder and reactive plasma parameters in a low-pressure RF glow discharge in silane is studied. It is shown that the discharge control parameters and reactor volume can be adjusted to ensure lower abundance of nanopowders, which is one of the requirements of the plasma-assisted fabrication of low-dimensional quantum nanostructures. The results are relevant to micro- and nanomanufacturing technologies employing low-pressure glow discharge plasmas of silane-based gas mixtures.

Growth kinetics of carbon nanowall-like structures in low-temperature plasmas

The results of a hybrid numerical simulation of the growth kinetics of carbon nanowall-like nanostructures in the plasma and neutral gas synthesis processes are presented. The low-temperature plasma-based process was found to have a significant advantage over the purely neutral flux deposition in providing the uniform size distribution of the nanostructures. It is shown that the nanowall width uniformity is the best (square deviations not exceeding 1.05) in high-density plasmas of 3.0× 1018 m-3, worsens in lower-density plasmas (up to 1.5 in 1.0× 1017 m-3 plasmas), and is the worst (up to 1.9) in the neutral gas-based process. This effect has been attributed to the focusing of ion fluxes by irregular electric field in the vicinity of plasma-grown nanostructures on substrate biased with -20 V potential, and differences in the two-dimensional adatom diffusion fluxes in the plasma and neutral gas-based processes. The results of our numerical simulations are consistent with the available experimental reports on the effect of the plasma process parameters on the sizes and shapes of relevant nanostructures.

Anterior temporal cortex and semantic memory : reconciling findings from neuropsychology and functional imaging

Studies of semantic impairment arising from brain disease suggest that the anterior temporal lobes are critical for semantic abilities in humans; yet activation of these regions is rarely reported in functional imaging studies of healthy controls performing semantic tasks. Here, we combined neuropsychological and PET functional imaging data to show that when healthy subjects identify concepts at a specific level, the regions activated correspond to the site of maximal atrophy in patients with relatively pure semantic impairment. The stimuli were color photographs of common animals or vehicles, and the task was category verification at specific (e.g., robin), intermediate (e.g., bird), or general (e.g., animal) levels. Specific, relative to general, categorization activated the antero-lateral temporal cortices bilaterally, despite matching of these experimental conditions for difficulty. Critically, in patients with atrophy in precisely these areas, the most pronounced deficit was in the retrieval of specific semantic information.

Self-assembly of uniform carbon nanotip structures in chemically active inductively coupled plasmas

Self-assembly of carbon nanotip (CNTP) structures on Ni-based catalyst in chemically active inductively coupled plasmas of CH 4 + H 2 + Ar gas mixtures is reported. By varying the process conditions, it appears possible to control the shape, size, and density of CNTPs, content of the nanocrystalline phase in the films, as well as to achieve excellent crystallinity, graphitization, uniformity and vertical alignment of the resulting nanostructures at substrate temperatures 300-500°C and low gas pressures (below 13.2 Pa). This study provides a simple and efficient plasma-enhanced chemical vapor deposition (PECVD) technique for the fabrication of vertically aligned CNTP arrays for electron field emitters.

Optimizing I/O cost and managing memory for composition vector method based on correlation matrix calculation in bioinformatics

The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.

The brain-specific microRNA miR-128b regulates the formation of fear-extinction memory

MicroRNAs are small non-coding RNAs that mediate post-transcriptional gene silencing. Fear-extinction learning in C57/Bl6J mice led to increased expression of the brain-specific microRNA miR-128b, which disrupted stability of several plasticity-related target genes and regulated formation of fear-extinction memory. Increased miR-128b activity may therefore facilitate the transition from retrieval of the original fear memory toward the formation of a new fear-extinction memory.

Paradoxical enhancement of fear extinction memory and synaptic plasticity by inhibition of the histone acetyltransferase p300

It is well established that the coordinated regulation of activity-dependent gene expression by the histone acetyltransferase (HAT) family of transcriptional coactivators is crucial for the formation of contextual fear and spatial memory, and for hippocampal synaptic plasticity. However, no studies have examined the role of this epigenetic mechanism within the infralimbic prefrontal cortex (ILPFC), an area of the brain that is essential for the formation and consolidation of fear extinction memory. Here we report that a postextinction training infusion of a combined p300/CBP inhibitor (Lys-CoA-Tat), directly into the ILPFC, enhances fear extinction memory in mice. Our results also demonstrate that the HAT p300 is highly expressed within pyramidal neurons of the ILPFC and that the small-molecule p300-specific inhibitor (C646) infused into the ILPFC immediately after weak extinction training enhances the consolidation of fear extinction memory. C646 infused 6 h after extinction had no effect on fear extinction memory, nor did an immediate postextinction training infusion into the prelimbic prefrontal cortex. Consistent with the behavioral findings, inhibition of p300 activity within the ILPFC facilitated long-term potentiation (LTP) under stimulation conditions that do not evoke long-lasting LTP. These data suggest that one function of p300 activity within the ILPFC is to constrain synaptic plasticity, and that a reduction in the function of this HAT is required for the formation of fear extinction memory.

Toward an object-based semantic memory for long-term operation of mobile service robots

Throughout a lifetime of operation, a mobile service robot needs to acquire, store and update its knowledge of a working environment. This includes the ability to identify and track objects in different places, as well as using this information for interaction with humans. This paper introduces a long-term updating mechanism, inspired by the modal model of human memory, to enable a mobile robot to maintain its knowledge of a changing environment. The memory model is integrated with a hybrid map that represents the global topology and local geometry of the environment, as well as the respective 3D location of objects. We aim to enable the robot to use this knowledge to help humans by suggesting the most likely locations of specific objects in its map. An experiment using omni-directional vision demonstrates the ability to track the movements of several objects in a dynamic environment over an extended period of time.

Nonvolatile multilevel data storage memory device from controlled ambipolar charge trapping mechanism

The capability of storing multi-bit information is one of the most important challenges in memory technologies. An ambipolar polymer which intrinsically has the ability to transport electrons and holes as a semiconducting layer provides an opportunity for the charge trapping layer to trap both electrons and holes efficiently. Here, we achieved large memory window and distinct multilevel data storage by utilizing the phenomena of ambipolar charge trapping mechanism. As fabricated flexible memory devices display five well-defined data levels with good endurance and retention properties showing potential application in printed electronics.

Engineering the mechanical properties of graphene nanotube hybrid structures through structural modulation

The excellent multi-functional properties of carbon nanotube (CNT) and graphene have enabled them as appealing building blocks to construct 3D carbon-based nanomaterials or nanostructures. The recently reported graphene nanotube hybrid structure (GNHS) is one of the representatives of such nanostructures. This work investigated the relationships between the mechanical properties of the GNHS and its structure basing on large-scale molecular dynamics simulations. It is found that increasing the length of the constituent CNTs, the GNHS will have a higher Young’s modulus and yield strength. Whereas, no strong correlation is found between the number of graphene layers and Young’s modulus and yield strength, though more graphene layers intends to lead to a higher yield strain. In the meanwhile, the presences of multi-wall CNTs are found to greatly strengthen the hybrid structure. Generally, the hybrid structures exhibit a brittle behavior and the failure initiates from the connecting regions between CNT and graphene. More interestingly, affluent formations of monoatomic chains and rings are found at the fracture region. This study provides an in-depth understanding of the mechanical performance of the GNHSs while varying their structures, which will shed lights on the design and also the applications of the carbon-based nanostructures.

Phonon modes of MgB2 : Super-lattice structures and spectral response

Micrometre-sized MgB2 crystals of varying quality, synthesized at low temperature and autogeneous pressure, are compared using a combination of Raman and Infra-Red (IR) spectroscopy. These data, which include new peak positions in both spectroscopies for high quality MgB2, are interpreted using DFT calculations on phonon behaviour for symmetry-related structures. Raman and IR activity additional to that predicted by point group analyses of the P6/mmm symmetry are detected. These additional peaks, as well as the overall shapes of calculated phonon dispersion (PD) models are explained by assuming a double super-lattice, consistent with a lower symmetry structure for MgB2. A 2x super-lattice in the c-direction allows a simple correlation of the pair breaking energy and the superconducting gap by activation of corresponding acoustic frequencies. A consistent physical interpretation of these spectra is obtained when the position of a phonon anomaly defines a super-lattice modulation in the a-b plane.