Langevin dynamics modeling of the water diffusion tensor in partially aligned collagen networks

In this work, a Langevin dynamics model of the diffusion of water in articular cartilage was developed. Numerical simulations of the translational dynamics of water molecules and their interaction with collagen fibers were used to study the quantitative relationship between the organization of the collagen fiber network and the diffusion tensor of water in model cartilage. Langevin dynamics was used to simulate water diffusion in both ordered and partially disordered cartilage models. In addition, an analytical approach was developed to estimate the diffusion tensor for a network comprising a given distribution of fiber orientations. The key findings are that (1) an approximately linear relationship was observed between collagen volume fraction and the fractional anisotropy of the diffusion tensor in fiber networks of a given degree of alignment, (2) for any given fiber volume fraction, fractional anisotropy follows a fiber alignment dependency similar to the square of the second Legendre polynomial of cos(θ), with the minimum anisotropy occurring at approximately the magic angle (θMA), and (3) a decrease in the principal eigenvalue and an increase in the transverse eigenvalues is observed as the fiber orientation angle θ progresses from 0◦ to 90◦. The corresponding diffusion ellipsoids are prolate for θ < θMA, spherical for θ ≈ θMA, and oblate for θ > θMA. Expansion of the model to include discrimination between the combined effects of alignment disorder and collagen fiber volume fraction on the diffusion tensor is discussed.

An English-translated parallel corpus for the CJK Wikipedia collections

In this paper, we describe a machine-translated parallel English corpus for the NTCIR Chinese, Japanese and Korean (CJK) Wikipedia collections. This document collection is named CJK2E Wikipedia XML corpus. The corpus could be used by the information retrieval research community and knowledge sharing in Wikipedia in many ways; for example, this corpus could be used for experimentations in cross-lingual information retrieval, cross-lingual link discovery, or omni-lingual information retrieval research. Furthermore, the translated CJK articles could be used to further expand the current coverage of the English Wikipedia.

An evaluation of corpus-driven measures of medical concept similarity for information retrieval

Measures of semantic similarity between medical concepts are central to a number of techniques in medical informatics, including query expansion in medical information retrieval. Previous work has mainly considered thesaurus-based path measures of semantic similarity and has not compared different corpus-driven approaches in depth. We evaluate the effectiveness of eight common corpus-driven measures in capturing semantic relatedness and compare these against human judged concept pairs assessed by medical professionals. Our results show that certain corpus-driven measures correlate strongly (approx 0.8) with human judgements. An important finding is that performance was significantly affected by the choice of corpus used in priming the measure, i.e., used as evidence from which corpus-driven similarities are drawn. This paper provides guidelines for the implementation of semantic similarity measures for medical informatics and concludes with implications for medical information retrieval.

Enhanced hydrogen separation by vertically-aligned carbon nanotube membranes with zeolite imidazolate frameworks as a selective layer

Vertically-aligned carbon nanotube (VACNT) membranes show very high permeation fluxes due to the inherent smooth and frictionless nature of the interior of the nanotubes. However, the hydrogen selectivities are all in the Knudsen range and are quite low. In this study we grew molecular sieve zeolite imidazolate frameworks (ZIFs) via secondary seeded growth on the VACNT membranes as a gas selective layer. The ZIF layer has a thickness of 5–6 μm and shows good contact with the VACNT membrane surface. The VACNT supported ZIF membrane shows much higher H2 selectivity than Ar (7.0); O2 (13.6); N2 (15.1) and CH4 (9.8). We conclude that tailoring metal–organic frameworks on the membrane surface can be an effective route to improve the gas separation performance of the VACNT membrane.

Vertically-aligned carbon nanotube membranes for hydrogen separation

Vertically-aligned carbon nanotube membranes have been fabricated and characterized and the corresponding gas permeability and hydrogen separation were measured. The carbon nanotube diameter and areal density were adjusted by varying the catalyst vapour concentration (Fe/C ratio) in the mixed precursor. The permeances are one to two magnitudes higher than the Knudsen prediction, while the gas selectivities are still in the Knudsen range. The diameter and areal density effects were studied and compared, the temperature dependence of permeation is also discussed. The results confirm the existence of non-Knudsen transport and that surface adsorption diffusion may affect the total permeance at relative low temperature. The permeance of aligned carbon nanotube membranes can be improved by increasing areal density and operating at an optimum temperature.

Aligned poly(L-lactic-co-ε-caprolactone) electrospun microfibers and knitted structure: a novel composite scaffold for ligament tissue engineering

We developed a novel technique involving knitting and electrospinning to fabricate a composite scaffold for ligament tissue engineering. Knitted structures were coated with poly(L-lactic-co-e-caprolactone) (PLCL) and then placed onto a rotating cylinder and a PLCL solution was electrospun onto the structure. Highly aligned 2-μm-diameter microfibers covered the space between the stitches and adhered to the knitted scaffolds. The stress–strain tensile curves exhibited an initial toe region similar to the tensile behavior of ligaments. Composite scaffolds had an elastic modulus (150 ± 14 MPa) similar to the modulus of human ligaments. Biological evaluation showed that cells proliferated on the composite scaffolds and they spontaneously orientated along the direction of microfiber alignment. The microfiber architecture also induced a high level of extracellular matrix secretion, which was characterized by immunostaining. We found that cells produced collagen type I and type III, two main components found in ligaments. After 14 days of culture, collagen type III started to form a fibrous network. We fabricated a composite scaffold having the mechanical properties of the knitted structure and the morphological properties of the aligned microfibers. It is difficult to seed a highly macroporous structure with cells, however the technique we developed enabled an easy cell seeding due to presence of the microfiber layer. Therefore, these scaffolds presented attractive properties for a future use in bioreactors for ligament tissue engineering.

The efficiency of corpus-based distributional models for literature-based discovery on large data sets

This paper evaluates the efficiency of a number of popular corpus-based distributional models in performing discovery on very large document sets, including online collections. Literature-based discovery is the process of identifying previously unknown connections from text, often published literature, that could lead to the development of new techniques or technologies. Literature-based discovery has attracted growing research interest ever since Swanson's serendipitous discovery of the therapeutic effects of fish oil on Raynaud's disease in 1986. The successful application of distributional models in automating the identification of indirect associations underpinning literature-based discovery has been heavily demonstrated in the medical domain. However, we wish to investigate the computational complexity of distributional models for literature-based discovery on much larger document collections, as they may provide computationally tractable solutions to tasks including, predicting future disruptive innovations. In this paper we perform a computational complexity analysis on four successful corpus-based distributional models to evaluate their fit for such tasks. Our results indicate that corpus-based distributional models that store their representations in fixed dimensions provide superior efficiency on literature-based discovery tasks.

Diffusion tensor of water in partially aligned fibre networks

Monte Carlo simulations were used to investigate the relationship between the morphological characteristics and the diffusion tensor (DT) of partially aligned networks of cylindrical fibres. The orientation distributions of the fibres in each network were approximately uniform within a cone of a given semi-angle (θ0). This semi-angle was used to control the degree of alignment of the fibres. The networks studied ranged from perfectly aligned (θ0 = 0) to completely disordered (θ0 = 90°). Our results are qualitatively consistent with previous numerical models in the overall behaviour of the DT. However, we report a non-linear relationship between the fractional anisotropy (FA) of the DT and collagen volume fraction, which is different to the findings from previous work. We discuss our results in the context of diffusion tensor imaging of articular cartilage. We also demonstrate how appropriate diffusion models have the potential to enable quantitative interpretation of the experimentally measured diffusion-tensor FA in terms of collagen fibre alignment distributions.

Uniform, dense arrays of vertically aligned, large-diameter single-walled carbon nanotubes

Precisely controlled reactive chemical vapor synthesis of highly uniform, dense arrays of vertically aligned single-walled carbon nanotubes (SWCNTs) using tailored trilayered Fe/Al2O3/SiO2 catalyst is demonstrated. More than 90% population of thick nanotubes (>3 nm in diameter) can be produced by tailoring the thickness and microstructure of the secondary catalyst supporting SiO2 layer, which is commonly overlooked. The proposed model based on the atomic force microanalysis suggests that this tailoring leads to uniform and dense arrays of relatively large Fe catalyst nanoparticles on which the thick SWCNTs nucleate, while small nanotubes and amorphous carbon are effectively etched away. Our results resolve a persistent issue of selective (while avoiding multiwalled nanotubes and other carbon nanostructures) synthesis of thick vertically aligned SWCNTs whose easily switchable thickness-dependent electronic properties enable advanced applications in nanoelectronic, energy, drug delivery, and membrane technologies.

Enhancement of electron field emission of vertically aligned carbon nanotubes by nitrogen plasma treatment

The electron field emission (EFE) characteristics from vertically aligned carbon nanotubes (VACNTs) without and with treatment by the nitrogen plasma are investigated. The VACNTs with the plasma treatment showed a significant improvement in the EFE property compared to the untreated VACNTs. The morphological, structural, and compositional properties of the VACNTs are extensively examined by scanning electron microscopy, transmission electron microscopy, Raman spectroscopy, and energy dispersive X-ray spectroscopy. It is shown that the significant EFE improvement of the VACNTs after the nitrogen plasma treatment is closely related to the variation of the morphological and structural properties of the VACNTs. The high current density (299.6 μA/cm2) achieved at a low applied field (3.50 V/μm) suggests that the VACNTs after nitrogen plasma treatment can serve as effective electron field emission sources for numerous applications.

Plasma-enabled growth of separated, vertically aligned copper-capped carbon nanocones on silicon

The formation of vertically aligned, clearly separated, copper-capped carbon nanocones with a length of up to 500 nm and base diameter of about 150 nm via three-stage process involving magnetron sputtering, N2 plasma treatment, and CH4 + N2 plasma growth is studied. The width of gaps between the nanocones can be controlled by the gas composition. The nanocone formation mechanism is explained in terms of strong passivation of carbon in narrow gaps, where the access of plasma ions is hindered and the formation of large Cn H2n+2 molecules is possible. This plasma-enabled approach can be used to fabricate nanoelectronic, nanofluidic, and optoelectronic components and devices. © 2010 American Institute of Physics.

Plasma-controlled adatom delivery and (re)distribution: Enabling uninterrupted, low-temperature growth of ultralong vertically aligned single walled carbon nanotubes

Large-scale (∼109 atoms) numerical simulations reveal that plasma-controlled dynamic delivery and redistribution of carbon atoms between the substrate and nanotube surfaces enable the growth of ultralong single walled carbon nanotubes (SWCNTs) and explain the common experimental observation of slower growth at advanced stages. It is shown that the plasma-based processes feature up to two orders of magnitude higher growth rates than equivalent neutral-gas systems and are better suited for the SWCNT synthesis at low nanodevice friendly temperatures. © 2008 American Institute of Physics.

Self-organized vertically aligned single-crystal silicon nanostructures with controlled shape and aspect ratio by reactive plasma etching

The formation of vertically aligned single-crystalline silicon nanostructures via "self-organized" maskless etching in Ar+ H 2 plasmas is studied. The shape and aspect ratio can be effectively controlled by the reactive plasma composition. In the optimum parameter space, single-crystalline pyramid-like nanostructures are produced; otherwise, nanocones and nanodots are formed. This generic nanostructure formation approach does not involve any external material deposition. It is based on a concurrent sputtering, etching, hydrogen termination, and atom/radical redeposition and can be applied to other nanomaterials.

Low-temperature growth of large area, vertically aligned carbon nanotubes for field emission applications

Large area, highly uniform vertically aligned carbon nanotips (VACNTP) and other nanostructures have been grown on silicon (100) substrates with Ni catalyst in the low-temperature, low-frequency, high-density inductively coupled plasmas (ICP) of methane-hydrogen-argon gas mixtures. The control strategies for the morphology, crystalline structure and chemical states of the resulting nanostructures by varying the growth conditions are proposed. XRD and Roman analyses confirm that the nanotips are well graphitized, which is favorable for the field emission applications.

Effect of plasma environment on synthesis of vertically aligned carbon nanofibers in plasma-enhanced chemical vapor deposition

We present a theoretical model describing a plasma-assisted growth of carbon nanofibers (CNFs), which involves two competing channels of carbon incorporation into stacked graphene sheets: via surface diffusion and through the bulk of the catalyst particle (on the top of the nanofiber), accounting for a range of ion- and radical-assisted processes on the catalyst surface. Using this model, it is found that at low surface temperatures, Ts, the CNF growth is indeed controlled by surface diffusion, thus quantifying the semiempirical conclusions of earlier experiments. On the other hand, both the surface and bulk diffusion channels provide a comparable supply of carbon atoms to the stacked graphene sheets at elevated synthesis temperatures. It is also shown that at low Ts, insufficient for effective catalytic precursor decomposition, the plasma ions play a key role in the production of carbon atoms on the catalyst surface. The model is used to compute the growth rates for the two extreme cases of thermal and plasma-enhanced chemical vapor deposition of CNFs. More importantly, these results quantify and explain a number of observations and semiempirical conclusions of earlier experiments.