Preparation and characterization of a novel pyrrole-benzophenone copolymerized silica nanocomposite as a reagent in a visual immunologic-agglutination test.

Biological sensing is explored through novel stable colloidal dispersions of pyrrole-benzophenone and pyrrole copolymerized silica (PPy-SiO(2)-PPyBPh) nanocomposites, which allow covalent linking of biological molecules through light mediation. The mechanism of nanocomposite attachment to a model protein is studied by gold labeled cholera toxin B (CTB) to enhance the contrast in electron microscopy imaging. The biological test itself is carried out without gold labeling, i.e., using CTB only. The protein is shown to be covalently bound through the benzophenone groups. When the reactive PPy-SiO(2)-PPyBPh-CTB nanocomposite is exposed to specific recognition anti-CTB immunoglobulins, a qualitative visual agglutination assay occurs spontaneously, producing as a positive test, PPy-SiO(2)-PPyBPh-CTB-anti-CTB, in less than 1 h, while the control solution of the PPy-SiO(2)-PPyBPh-CTB alone remained well-dispersed during the same period. These dispersions were characterized by cryogenic transmission microscopy (cryo-TEM), scanning electron microscopy (SEM), FTIR and X-ray photoelectron spectroscopy (XPS).

High-resolution γ-ray spectroscopy: A versatile tool for nuclear β-decay studies at TRIUMF-ISAC

High-resolution γ-ray spectroscopy is essential to fully exploit the unique, high-quality beams available at the next generation of radioactive ion beam facilities such as the TRIUMF isotope separator and accelerator (ISAC). The 8π spectrometer, which consists of 20 Compton-suppressed HPGe detectors, has recently been reconfigured for a vigorous research programme in weak interaction and nuclear structure physics. With the addition of a variety of ancillary detectors it has become the world's most powerful device dedicated to β-decay studies. This paper provides a brief overview of the apparatus and highlights from recent experiments. © 2005 IOP Publishing Ltd.

Raman spectroscopy as a versatile tool for studying the properties of graphene.

Raman spectroscopy is an integral part of graphene research. It is used to determine the number and orientation of layers, the quality and types of edge, and the effects of perturbations, such as electric and magnetic fields, strain, doping, disorder and functional groups. This, in turn, provides insight into all sp(2)-bonded carbon allotropes, because graphene is their fundamental building block. Here we review the state of the art, future directions and open questions in Raman spectroscopy of graphene. We describe essential physical processes whose importance has only recently been recognized, such as the various types of resonance at play, and the role of quantum interference. We update all basic concepts and notations, and propose a terminology that is able to describe any result in literature. We finally highlight the potential of Raman spectroscopy for layered materials other than graphene.

Plasma enhanced chemical vapour deposited carbon nanotubes for field emission applications

Plasma Enhanced Chemical Vapour Deposition is an extremely versatile technique for directly growing multiwalled carbon nanotubes onto various substrates. We will demonstrate the deposition of vertically aligned nanotube arrays, sparsely or densely populated nanotube forests, and precisely patterned arrays of nanotubes. The high-aspect ratio nanotubes (∼50 nm in diameter and 5 microns long) produced are metallic in nature and direct contact electrical measurements reveal that each nanotube has a current carrying capacity of 107-108 A/cm2, making them excellent candidates as field emission sources. We examined the field emission characteristics of dense nanotube forests as well as sparse nanotube forests and found that the sparse forests had significantly lower turn-on fields and higher emission currents. This is due to a reduction in the field enhancement of the nanotubes due to electric field shielding from adjacent nanotubes in the dense nanotube arrays. We thus fabricated a uniform array of single nanotubes to attempt to overcome these issues and will present the field emission characteristics of this.

Collective Cell Migration: Leadership, Invasion and Segregation

A number of biological processes, such as embryo development, cancer metastasis or wound healing, rely on cells moving in concert. The mechanisms leading to the emergence of coordinated motion remain however largely unexplored. Although biomolecular signalling is known to be involved in most occurrences of collective migration, the role of physical and mechanical interactions has only been recently investigated. In this paper, a versatile framework for cell motility is implemented in-silico in order to study the minimal requirements for the coordination of a group of epithelial cells. We find that cell motility and cell-cell mechanical interactions are sufficient to generate a broad array of behaviours commonly observed in vitro and in vivo. Cell streaming, sheet migration and susceptibility to leader cells are examples of behaviours spontaneously emerging from these simple assumptions, which might explain why collective effects are so ubiquitous in nature. This analysis provides also new insights into cancer metastasis and cell sorting, suggesting in particular that collective invasion might result from an emerging coordination in a system where single cells are mechanically unable to invade.

The modified Kanerva model for automatic speech recognition

A parallel processing network derived from Kanerva's associative memory theory Kanerva 1984 is shown to be able to train rapidly on connected speech data and recognize further speech data with a label error rate of 0·68%. This modified Kanerva model can be trained substantially faster than other networks with comparable pattern discrimination properties. Kanerva presented his theory of a self-propagating search in 1984, and showed theoretically that large-scale versions of his model would have powerful pattern matching properties. This paper describes how the design for the modified Kanerva model is derived from Kanerva's original theory. Several designs are tested to discover which form may be implemented fastest while still maintaining versatile recognition performance. A method is developed to deal with the time varying nature of the speech signal by recognizing static patterns together with a fixed quantity of contextual information. In order to recognize speech features in different contexts it is necessary for a network to be able to model disjoint pattern classes. This type of modelling cannot be performed by a single layer of links. Network research was once held back by the inability of single-layer networks to solve this sort of problem, and the lack of a training algorithm for multi-layer networks. Rumelhart, Hinton & Williams 1985 provided one solution by demonstrating the "back propagation" training algorithm for multi-layer networks. A second alternative is used in the modified Kanerva model. A non-linear fixed transformation maps the pattern space into a space of higher dimensionality in which the speech features are linearly separable. A single-layer network may then be used to perform the recognition. The advantage of this solution over the other using multi-layer networks lies in the greater power and speed of the single-layer network training algorithm. © 1989.

Numerical simulation of the growth of ZnO nanostructures in a tube furnace by physical vapour deposition

Zinc oxide is a versatile II-VI naturally n-type semiconductor that exhibits piezoelectric properties. By controlling the growth kinetics during a simple carbothermal reduction process a wide range of 1D nanostructures such as nanowires, nanobelts, and nanotetrapods have been synthesized. The driving force: for the nanostructure growth is the Zn vapour supersaturation and supply rate which, if known, can be used to predict and explain the type of crystal structure that results. A model which attempts to determine the Zn vapour concentration as a function of position in the growth furnace is described. A numerical simulation package, COMSOL, was used to simultaneously model the effects of fluid flow, diffusion and heat transfer in a tube furnace made specifically for ZnO nanostructure growth. Parameters such as the temperature, pressure, and flow rate are used as inputs to the model to show the effect that each one has on the Zn concentration profile. An experimental parametric study of ZnO nanostructure growth was also conducted and compared to the model predictions for the Zn concentration in the tube. © 2008 Materials Research Society.

Altering the ordering and disordering of a triangular nanographene at room temperature.

Molecular self-organization has the potential to serve as an efficient and versatile tool for the spontaneous creation of low-dimensional nanostructures on surfaces. We demonstrate how the subtle balance between intermolecular interactions and molecule-surface interactions can be altered by modifying the environment or through manipulation by means of the tip in a scanning tunnelling microscope (STM) at room temperature. We show how this leads to the distinctive ordering and disordering of a triangular nanographene molecule, the trizigzag-hexa-peri-hexabenzocoronenes-phenyl-6 (trizigzagHBC-Ph6), on two different surfaces: graphite and Au(111). The assembly of submonolayer films on graphite reveals a sixfold packing symmetry under UHV conditions, whereas at the graphite-phenyloctane interface, they reorganize into a fourfold packing symmetry, mediated by the solvent molecules. On Au(111) under UHV conditions in the multilayer films we investigated, although disorder prevails with the molecules being randomly distributed, their packing behaviour can be altered by the scanning motion of the tip. The asymmetric diode-like current-voltage characteristics of the molecules are retained when deposited on both substrates. This paper highlights the importance of the surrounding medium and any external stimulus in influencing the molecular organization process, and offers a unique approach for controlling the assembly of molecules at a desired location on a substrate.

Modal liquid crystal devices in optical tweezing: 3D control and oscillating potential wells

We investigate the use of liquid crystal (LC) adaptive optics elements to provide full 3 dimensional particle control in an optical tweezer. These devices are suitable for single controllable traps, and so are less versatile than many of the competing technologies which can be used to control multiple particles. However, they have the advantages of simplicity and light efficiency. Furthermore, compared to binary holographic optical traps they have increased positional accuracy. The transmissive LC devices could be retro-fitted to an existing microscope system. An adaptive modal LC lens is used to vary the z-focal position over a range of up to 100 μm and an adaptive LC beam-steering device is used to deflect the beam (and trapped particle) in the x-y plane within an available radius of 10 μm. Furthermore, by modifying the polarisation of the incident light, these LC components also offer the opportunity for the creation of dual optical traps of controllable depth and separation. © 2006 Optical Society of America.

High efficiency liquid crystal lasers giving "white light" emission from arrays and flexible substrates

The self-organization of the helical structure of chiral nematic liquid crystals combined with their sensitivity to electric fields makes them particularly interesting for low-threshold, wavelength tunable laser devices. We have studied these organic lasers in detail, ranging from the influence specific macroscopic properties, such as birefringence and order parameter, have on the output characteristics, to practical systems in the form of two-dimensional arrays, double-pass geometries and paintable lasers. Furthermore, even though chiral nematics are responsive to electric fields there is no facile means by which the helix periodicity can be adjusted, thereby allowing laser wavelength tuning, without adversely affecting the optical quality of the resonator. Therefore, in addition to studying the liquid crystal lasers, we have focused on finding a novel method with which to alter the periodicity of a chiral nematic using electric fields without inducing defects and degrading the optical quality factor of the resonator. This paper presents an overview of our research, describing (i) the correlation between laser output and material properties,(ii) the importance of the gain medium,(iii) multicolor laser arrays, and (iv) high slope efficiency (>60%) silicon back-plane devices. Overall we conclude that these materials have great potential for use in versatile organic laser systems.

Optimal design of Functionally Graded Materials using a procedural model and Particle Swarm Optimization

A new method for the optimal design of Functionally Graded Materials (FGM) is proposed in this paper. Instead of using the widely used explicit functional models, a feature tree based procedural model is proposed to represent generic material heterogeneities. A procedural model of this sort allows more than one explicit function to be incorporated to describe versatile material gradations and the material composition at a given location is no longer computed by simple evaluation of an analytic function, but obtained by execution of customizable procedures. This enables generic and diverse types of material variations to be represented, and most importantly, by a reasonably small number of design variables. The descriptive flexibility in the material heterogeneity formulation as well as the low dimensionality of the design vectors help facilitate the optimal design of functionally graded materials. Using the nature-inspired Particle Swarm Optimization (PSO) method, functionally graded materials with generic distributions can be efficiently optimized. We demonstrate, for the first time, that a PSO based optimizer outperforms classical mathematical programming based methods, such as active set and trust region algorithms, in the optimal design of functionally graded materials. The underlying reason for this performance boost is also elucidated with the help of benchmarked examples. © 2011 Elsevier Ltd. All rights reserved.

The shear mode of multilayer graphene

The quest for materials capable of realizing the next generation of electronic and photonic devices continues to fuel research on the electronic, optical and vibrational properties of graphene. Few-layer graphene (FLG) flakes with less than ten layers each show a distinctive band structure. Thus, there is an increasing interest in the physics and applications of FLGs. Raman spectroscopy is one of the most useful and versatile tools to probe graphene samples. Here, we uncover the interlayer shear mode of FLGs, ranging from bilayer graphene (BLG) to bulk graphite, and suggest that the corresponding Raman peak measures the interlayer coupling. This peak scales from ∼43cm -1 in bulk graphite to ∼31cm -1 in BLG. Its low energy makes it sensitive to near-Dirac point quasiparticles. Similar shear modes are expected in all layered materials, providing a direct probe of interlayer interactions. © 2012 Macmillan Publishers Limited. All rights reserved.

Patterned low temperature copper-rich deposits using inkjet printing

Discrete inkspots of very high copper content were produced using inkjet technology. The reagent disproportionates at low temperature to deposit copper on glass. These deposits were shown to be more than 90% copper by weight by electron probe microanalysis and microbeam Rutherford backscatttering spectroscopy.

Nanobodies raised against monomeric α-synuclein distinguish between fibrils at different maturation stages.

Nanobodies are single-domain fragments of camelid antibodies that are emerging as versatile tools in biotechnology. We describe here the interactions of a specific nanobody, NbSyn87, with the monomeric and fibrillar forms of α-synuclein (αSyn), a 140-residue protein whose aggregation is associated with Parkinson's disease. We have characterized these interactions using a range of biophysical techniques, including nuclear magnetic resonance and circular dichroism spectroscopy, isothermal titration calorimetry and quartz crystal microbalance measurements. In addition, we have compared the results with those that we have reported previously for a different nanobody, NbSyn2, also raised against monomeric αSyn. This comparison indicates that NbSyn87 and NbSyn2 bind with nanomolar affinity to distinctive epitopes within the C-terminal domain of soluble αSyn, comprising approximately amino acids 118-131 and 137-140, respectively. The calorimetric and quartz crystal microbalance data indicate that the epitopes of both nanobodies are still accessible when αSyn converts into its fibrillar structure. The apparent affinities and other thermodynamic parameters defining the binding between the nanobody and the fibrils, however, vary significantly with the length of time that the process of fibril formation has been allowed to progress and with the conditions under which formation occurs, indicating that the environment of the C-terminal domain of αSyn changes as fibril assembly takes place. These results demonstrate that nanobodies are able to target forms of potentially pathogenic aggregates that differ from each other in relatively minor details of their structure, such as those associated with fibril maturation.