The structure and dynamics of 2-dimensional fluids in swelling clays

The interlayer pores of swelling 2:1 clays provide an ideal 2-dimensional environment in which to study confined fluids. In this paper we discuss our understanding of the structure and dynamics of interlayer fluid species in expanded clays, based primarily on the outcome of recent molecular modelling and neutron scattering studies. Counterion solvation is compared with that measured in bulk solutions, and at a local level the cation-oxygen coordination is found to be remarkably similar in these two environments. However, for the monovalent ions the contribution to the first coordination shell from the clay surfaces increases with counterion radius. This gives rise to inner-sphere (surface) complexes in the case of potassium and caesium. In this context, the location of the negative clay surface charge (i.e. arising from octahedral or tetrahedral substitution) is also found to be of major importance. Divalent cations, such as calcium, eagerly solvate to form outer-sphere complexes. These complexes are able to pin adjacent clay layers together, and thereby prevent colloidal swelling. Confined water molecules form hydrogen bonds to each other and to the clays' surfaces. In this way their local environment relaxes to close to the bulk water structure within two molecular layers of the clay surface. Finally, we discuss the way in which the simple organic molecules methane, methanol and ethylene glycol behave in the interlayer region of hydrated clays. Quasi-elastic neutron scattering of isotopically labelled interlayer CH 3OD and (CH2OD)2 in deuterated clay allows us to measure the diffusion of the CH3- and CH2-groups in both clay and liquid environments. We find that in both the one-layer methanol solvates and the two-layer glycol solvates the diffusion of the most mobile organic molecules is close to that in the bulk solution.

Finite-size effects in on-line learning of multilayer neural networks

We complement recent advances in thermodynamic limit analyses of mean on-line gradient descent learning dynamics in multi-layer networks by calculating fluctuations possessed by finite dimensional systems. Fluctuations from the mean dynamics are largest at the onset of specialisation as student hidden unit weight vectors begin to imitate specific teacher vectors, increasing with the degree of symmetry of the initial conditions. In light of this, we include a term to stimulate asymmetry in the learning process, which typically also leads to a significant decrease in training time.

Finitely coordinated models for low-temperature phases of amorphous systems

We introduce models of heterogeneous systems with finite connectivity defined on random graphs to capture finite-coordination effects on the low-temperature behaviour of finite-dimensional systems. Our models use a description in terms of small deviations of particle coordinates from a set of reference positions, particularly appropriate for the description of low-temperature phenomena. A Born-von Karman-type expansion with random coefficients is used to model effects of frozen heterogeneities. The key quantity appearing in the theoretical description is a full distribution of effective single-site potentials which needs to be determined self-consistently. If microscopic interactions are harmonic, the effective single-site potentials turn out to be harmonic as well, and the distribution of these single-site potentials is equivalent to a distribution of localization lengths used earlier in the description of chemical gels. For structural glasses characterized by frustration and anharmonicities in the microscopic interactions, the distribution of single-site potentials involves anharmonicities of all orders, and both single-well and double-well potentials are observed, the latter with a broad spectrum of barrier heights. The appearance of glassy phases at low temperatures is marked by the appearance of asymmetries in the distribution of single-site potentials, as previously observed for fully connected systems. Double-well potentials with a broad spectrum of barrier heights and asymmetries would give rise to the well-known universal glassy low-temperature anomalies when quantum effects are taken into account. © 2007 IOP Publishing Ltd.

Simulation based knowledge elicitation:effect of visual representation and model parameters

Since much knowledge is tacit, eliciting knowledge is a common bottleneck during the development of knowledge-based systems. Visual interactive simulation (VIS) has been proposed as a means for eliciting experts’ decision-making by getting them to interact with a visual simulation of the real system in which they work. In order to explore the effectiveness and efficiency of VIS based knowledge elicitation, an experiment has been carried out with decision-makers in a Ford Motor Company engine assembly plant. The model properties under investigation were the level of visual representation (2-dimensional, 2½-dimensional and 3-dimensional) and the model parameter settings (unadjusted and adjusted to represent more uncommon and extreme situations). The conclusion from the experiment is that using a 2-dimensional representation with adjusted parameter settings provides the better simulation-based means for eliciting knowledge, at least for the case modelled.

Investigation of chaotic mixing in laminar fluid systems by the use of computational fluid dynamics

This work presents significant development into chaotic mixing induced through periodic boundaries and twisting flows. Three-dimensional closed and throughput domains are shown to exhibit chaotic motion under both time periodic and time independent boundary motions, A property is developed originating from a signature of chaos, sensitive dependence to initial conditions, which successfully quantifies the degree of disorder withjn the mixing systems presented and enables comparisons of the disorder throughout ranges of operating parameters, This work omits physical experimental results but presents significant computational investigation into chaotic systems using commercial computational fluid dynamics techniques. Physical experiments with chaotic mixing systems are, by their very nature, difficult to extract information beyond the recognition that disorder does, does not of partially occurs. The initial aim of this work is to observe whether it is possible to accurately simulate previously published physical experimental results through using commercial CFD techniques. This is shown to be possible for simple two-dimensional systems with time periodic wall movements. From this, and subsequent macro and microscopic observations of flow regimes, a simple explanation is developed for how boundary operating parameters affect the system disorder. Consider the classic two-dimensional rectangular cavity with time periodic velocity of the upper and lower walls, causing two opposing streamline motions. The degree of disorder within the system is related to the magnitude of displacement of individual particles within these opposing streamlines. The rationale is then employed in this work to develop and investigate more complex three-dimensional mixing systems that exhibit throughputs and time independence and are therefore more realistic and a significant advance towards designing chaotic mixers for process industries. Domains inducing chaotic motion through twisting flows are also briefly considered. This work concludes by offering possible advancements to the property developed to quantify disorder and suggestions of domains and associated boundary conditions that are expected to produce chaotic mixing.

Pattern generation by dissipative parametric instability

Nonlinear instabilities are responsible for spontaneous pattern formation in a vast number of natural and engineered systems, ranging from biology to galaxy buildup. We propose a new instability mechanism leading to pattern formation in spatially extended nonlinear systems, which is based on a periodic antiphase modulation of spectrally dependent losses arranged in a zigzag way: an effective filtering is imposed at symmetrically located wave numbers k and -k in alternating order. The properties of the dissipative parametric instability differ from the features of both key classical concepts of modulation instabilities, i.e., the Benjamin-Feir instability and the Faraday instabiltyity. We demonstrate how the dissipative parametric instability can lead to the formation of stable patterns in one- and two-dimensional systems. The proposed instability mechanism is generic and can naturally occur or can be implemented in various physical systems.

Dissipative parametric modulation instability and pattern formation in nonlinear optical systems

We present the essential features of the dissipative parametric instability, in the universal complex Ginzburg- Landau equation. Dissipative parametric instability is excited through a parametric modulation of frequency dependent losses in a zig-zag fashion in the spectral domain. Such damping is introduced respectively for spectral components in the +ΔF and in the -ΔF region in alternating fashion, where F can represent wavenumber or temporal frequency depending on the applications. Such a spectral modulation can destabilize the homogeneous stationary solution of the system leading to growth of spectral sidebands and to the consequent pattern formation: both stable and unstable patterns in one- and in two-dimensional systems can be excited. The dissipative parametric instability provides an useful and interesting tool for the control of pattern formation in nonlinear optical systems with potentially interesting applications in technological applications, like the design of mode- locked lasers emitting pulse trains with tunable repetition rate; but it could also find realizations in nanophotonics circuits or in dissipative polaritonic Bose-Einstein condensates.

The use of proteomics for the assessment of clinical samples in research

Proteomics, the analysis of expressed proteins, has been an important developing area of research for the past two decades [Anderson, NG, Anderson, NL. Twenty years of two-dimensional electrophoresis: past, present and future. Electrophoresis 1996;17:443-53]. Advances in technology have led to a rapid increase in applications to a wide range of samples; from initial experiments using cell lines, more complex tissues and biological fluids are now being assessed to establish changes in protein expression. A primary aim of clinical proteomics is the identification of biomarkers for diagnosis and therapeutic intervention of disease, by comparing the proteomic profiles of control and disease, and differing physiological states. This expansion into clinical samples has not been without difficulties owing to the complexity and dynamic range in plasma and human tissues including tissue biopsies. The most widely used techniques for analysis of clinical samples are surface-enhanced laser desorption/ionisation mass spectrometry (SELDI-MS) and 2-dimensional gel electrophoresis (2-DE) coupled to matrix-assisted laser desorption ionisation [Person, MD, Monks, TJ, Lau, SS. An integrated approach to identifying chemically induced posttranslational modifications using comparative MALDI-MS and targeted HPLC-ESI-MS/MS. Chem. Res. Toxicol. 2003;16:598-608]-mass spectroscopy (MALDI-MS). This review aims to summarise the findings of studies that have used proteomic research methods to analyse samples from clinical studies and to assess the impact that proteomic techniques have had in assessing clinical samples. © 2004 The Canadian Society of Clinical Chemists. All rights reserved.

Hypercoiling and hydrophobically associating polymers : interfacial synthesis, surface properties and pharmaceutical applications

The objective of the work described was to identify and synthesize a range of biodegradable hypercoiling or hydrophobically associating polymers to mimic natural apoproteins, such as those found in lung surfactant or plasma apolipoproteins. Stirred interfacial polymerization was used to synthesize potentially biodegradable aromatic polyamides (Mw of 12,000-26,000) based on L-Iysine, L-Iysine ethyl ester, L-ornithine and DL-diaminopropionic acid, by reaction with isophthaloyl chloride. A similar technique was used to synthesize aliphatic polyamides based on L-Iysine ethyl ester and either adipoyl chloride or glutaryl chloride resulting in the synthesis of poly(lysine ethyl ester adipamide) [PLETESA] or poly(lysine ethyl ester glutaramide) (Mw of 126,000 and 26,000, respectively). PLETESA was found to be soluble in both polar and non-polar solvents and the hydrophobic/hydrophilic balance could be modified by partial saponification (66-75%) of the ethyl ester side chains. Surface or interfacial tension/pH profiles were used to assess the conformation of both the poly(isophthalamides) and partially saponified PLETESA in aqueous solution. The results demonstrated that a loss of charge from the polymer was accompanied by an initial fall in surface activity, followed by a rise in activity, and ultimately, by polymer precipitation. These observations were explained by a collapse of the polymer chains into non-surface active intramolecular coils, followed by a transition to an amphipathic conformation, and finally to a collapsed hydrophobe. 2-Dimensional NMR analysis of polymer conformation in polar and non-polar solvents revealed intramolecular associations between the hydrophobic groups within partially saponified PLETESA. Unsaponified PLETESA appeared to form a coiled structure in polar solvents where the ethyl ester side chains were contained within the polymer coil. The implications of the secondary structure of PLETESA and potential biomedical applications are discussed.

Helicopter vibration sensor selection using data visualisation

The main objective of the project is to enhance the already effective health-monitoring system (HUMS) for helicopters by analysing structural vibrations to recognise different flight conditions directly from sensor information. The goal of this paper is to develop a new method to select those sensors and frequency bands that are best for detecting changes in flight conditions. We projected frequency information to a 2-dimensional space in order to visualise flight-condition transitions using the Generative Topographic Mapping (GTM) and a variant which supports simultaneous feature selection. We created an objective measure of the separation between different flight conditions in the visualisation space by calculating the Kullback-Leibler (KL) divergence between Gaussian mixture models (GMMs) fitted to each class: the higher the KL-divergence, the better the interclass separation. To find the optimal combination of sensors, they were considered in pairs, triples and groups of four sensors. The sensor triples provided the best result in terms of KL-divergence. We also found that the use of a variational training algorithm for the GMMs gave more reliable results.

Optical immersion of mid-infrared LEDs and photodiodes for gas-sensing applications

The high gains in performance predicted for optical immersion are difficult to achieve in practice due to total internal reflection at the lens/detector interface. By reducing the air gap at this interface optical tunneling becomes possible and the predicted gains can be realized in practical devices. Using this technique we have demonstrated large performance gains by optically immersing mid-infrared heterostructure InA1Sb LEDs and photodiodes using hypershperical germanium lenses. The development of an effective method of optical immersion that gives excellent optical coupling has produced a photodiode with a peak room temperature detectivity (D*) of 5.3 x 109 cmHz½W-1 at λpeak=5.4μm and a 40° field of view. A hyperspherically immersed LED showed a f-fold improvement in the external efficiency, and a 3-fold improvement in the directionality compared with a conventional planar LED for f/2 optical systems. The incorporation of these uncooled devices in a White cell produced a NO2 gas sensing system with 2 part-per-million sensitivity, with an LED drive current of <5mA. These results represent a significant advance in the use of solid state devices for portable gas sensing systems.

Granular superconductors:from the nonlinear σ model to the Bose-Hubbard description

We modify a nonlinear σ model (NLσM) for the description of a granular disordered system in the presence of both the Coulomb repulsion and the Cooper pairing. We show that under certain controlled approximations the action of this model is reduced to the Ambegaokar-Eckern-Schön (AES) action, which is further reduced to the Bose-Hubbard (or “dirty-boson”) model with renormalized coupling constants. We obtain an effective action which is more general than the AES one but still simpler than the full NLσM action. This action can be applied in the region of parameters where the reduction to the AES or the Bose-Hubbard model is not justified. This action may lead to a different picture of the superconductor-insulator transition in two-dimensional systems.

On the impact of Cu dispersion on CO2 photoreduction over Cu/TiO2

A family of Cu/TiO2 catalysts was prepared using a refined sol–gel method, and tested in the photocatalytic reduction of CO2 by H2O to CH4 using a stirred batch, annular reactor. The resulting photoactivity was benchmarked against pure TiO2 nanoparticles (synthesised by an identical sol–gel route). CO2 photoreduction exhibited a strong volcano dependence on Cu loading, reflecting the transition from 2-dimensional CuOx nanostructures to 3-dimensional crystallites, with optimum CH4 production observed for 0.03 wt.% Cu/TiO2.

A principled approach to interactive hierarchical non-linear visualization of high-dimensional data

Hierarchical visualization systems are desirable because a single two-dimensional visualization plot may not be sufficient to capture all of the interesting aspects of complex high-dimensional data sets. We extend an existing locally linear hierarchical visualization system PhiVis [1] in several directions: bf(1) we allow for em non-linear projection manifolds (the basic building block is the Generative Topographic Mapping -- GTM), bf(2) we introduce a general formulation of hierarchical probabilistic models consisting of local probabilistic models organized in a hierarchical tree, bf(3) we describe folding patterns of low-dimensional projection manifold in high-dimensional data space by computing and visualizing the manifold's local directional curvatures. Quantities such as magnification factors [3] and directional curvatures are helpful for understanding the layout of the nonlinear projection manifold in the data space and for further refinement of the hierarchical visualization plot. Like PhiVis, our system is statistically principled and is built interactively in a top-down fashion using the EM algorithm. We demonstrate the visualization system principle of the approach on a complex 12-dimensional data set and mention possible applications in the pharmaceutical industry.

Evidence for dissociation between the perceptual and visuomotor systems in humans

When a visual stimulus is continuously moved behind a small stationary window, the window appears displaced in the direction of motion of the stimulus. In this study we showed that the magnitude of this illusion is dependent on (i) whether a perceptual or visuomotor task is used for judging the location of the window, (ii) the directional signature of the stimulus, and (iii) whether or not there is a significant delay between the end of the visual presentation and the initiation of the localization measure. Our stimulus was a drifting sinusoidal grating windowed in space by a stationary, two-dimensional, Gaussian envelope (σ=1 cycle of sinusoid). Localization measures were made following either a short (200 ms) or long (4.2 s) post-stimulus delay. The visuomotor localization error was up to three times greater than the perceptual error for a short delay. However, the visuomotor and perceptual localization measures were similar for a long delay. Our results provide evidence in support of the hypothesis that separate cortical pathways exist for visual perception and visually guided action and that delayed actions rely on stored perceptual information.