Fabrication of magnetic luminescent nanocomposites by a layer-by-layer self-assembly approach

Magnetic luminescent nanocomposites were prepared via a layer-by-layer (LbL) assembly approach. The Fe3O4 magnetic nanoparticles of 8.5 nm were used as a template for the deposition of the CdTe quantum dots (QDs)/polyelectrolyte (PE) multilayers. The number of polyelectrolyte multilayers separating the nanoparticle layers and the number of QDs/ polyelectrolyte deposition cycles were varied to obtain two kinds of magnetic luminescent nanocomposites, Fe3O4/PEn/CdTe and Fe3O4/(PE3/CdTe)(n), respectively. The assembly processes were monitored through microelectrophoresis and UV-vis spectra. The topography and the size of the nanocomposites were studied by transmission electron microscopy. The LbL technique for fabricating magnetic luminescent nanocomposites has some advantages to tune their properties. It was found that the selection of a certain number of the inserted polyelectrolyte interlayers and the CdTe QDs loading on the nanocomposites could optimize the photoluminescence properties of the nanocomposites. Furthermore, the nanocomposites could be easily separated and collected in an external magnetic field.

Modification of electrode surface through electrospinning followed by self-assembly multilayer film of polyoxometalate and its photochromic

Electrospun poly (vinyl alcohol) (PVA) nanofibers mat was collected on indium tin oxide (ITO) substrate. Heat crosslinked nanofibers mat became water-insoluble and firmly fixed on ITO substrate even in water. Oppositely charged poly (allylamine hydrochloride) (PAH) and Dawson-type polyoxometalate (POM), Na6P2Mo18O62 (P2Mo18), were alternately assembled on PVA nanofibers-coated ITO substrate to construct multilayer film through an electrostatic layer-by-layer (LBL) technique. The scanning electron microscope (SEM) images showed that P2Mo18 multilayer film was selectively deposited on PVA nanofibers while the unoccupied space by nanofibers on bare ITO was acted as substrate at the same time because the electrospun nanofibers have larger surface area and surface energy than the flat substrate. The cyclic voltammograms current responses of the P2Mo18 multilayer film on PVA/ITO electrode showed three well-defined redox couples of P2Mo18, but very small because P2Mo18 multilayer film was selectively deposited on PVA nanofibers with poor conductivity. In addition, the photochromic behavior of P2Mo18 multilayer film on PVA/ITO was investigated through UV-vis spectra and electron spin resonance (ESR). Fourier-transform infrared (FT-IR) spectroscopy and X-ray photoelectron spectroscopy (XPS) proved that the charge-transfer complex was formed between PAH and P2Mo18 after UV irradiation.

Syntheses of Ag, PbSe, and PbTe nanocrystals and their binary self-assembly exploration at low size-ratio

Nanocrystals of Ag, PbSe, and PbTe were prepared via a high-temperature organic solution approach, respectively. Using a size-selection technique, the size-distribution of each set of nanocrystals could be fine-tuned and finally monodisperse products were achieved. Superlattice structure of binary self-assemblies in low size-ratio were also explored and characterized by transmission electron microscopy. It is realized that a success of achieving binary self-assembly pattern is greatly dependent on several key factors including particle size-distributions, relative concentrations of both components, as well as the size-ratios between Ag and PbSe (or PbTe) nanocrystals.

Toluidine blue modified self-assembled silica gel coated gold electrode as biosensor for NADH

A toluidine blue modified gold electrode was constructed using self-assembled silica gel technique. Firstly, toluidine blue was encapsulated within 3D network of silica self-assembly monolayer on the surface of gold electrode. Secondly, another layer of silica sol was further assembled to protect from leaching of mediator or possible contamination. The electrochemical characteristics of toluidine blue immobilized within self-assembled silica gel were studied in detail. The modified electrode was applied for electrochemical oxidation of NADH with satisfactory results.

Possibility of design of nanodevices by confined macromolecular self-assembly

Computer simulation has revealed that dual nanostructures for the development of nanodevices as nanowires, optical nanofibres and nanobatteries be obtained by the self-assembly of block copolymers confined geometry. The formation of individual nanostructures depends on the structures of block copolymers the confinement geometry and the interactions block copolymers and the boundary of the confinement geometry. In order to obtain individual nanostructures experimentally, attention needs to be paid to the manufacture of the confinement geometry and the design of the interactions between block copolymers and the boundary of the confinement geometry, The recently developed lithography technique should make experiments successful.

Investigation of the structures of the product ions produced via self-CI of acetone

The ion-molecule reactions in acetone were investigated which were induced under the chemical ionization. The structural information of the reaction products were obtained by using collision-induced dissociation (CID) technique performed at ion kinetic energies of 30eV.

Reliable Cellular Automata with Self-Organization

In a probabilistic cellular automaton in which all local transitions have positive probability, the problem of keeping a bit of information for more than a constant number of steps is nontrivial, even in an infinite automaton. Still, there is a solution in 2 dimensions, and this solution can be used to construct a simple 3-dimensional discrete-time universal fault-tolerant cellular automaton. This technique does not help much to solve the following problems: remembering a bit of information in 1 dimension; computing in dimensions lower than 3; computing in any dimension with non-synchronized transitions. Our more complex technique organizes the cells in blocks that perform a reliable simulation of a second (generalized) cellular automaton. The cells of the latter automaton are also organized in blocks, simulating even more reliably a third automaton, etc. Since all this (a possibly infinite hierarchy) is organized in "software", it must be under repair all the time from damage caused by errors. A large part of the problem is essentially self-stabilization recovering from a mess of arbitrary-size and content caused by the faults. The present paper constructs an asynchronous one-dimensional fault-tolerant cellular automaton, with the further feature of "self-organization". The latter means that unless a large amount of input information must be given, the initial configuration can be chosen to be periodical with a small period.

Identifying the damage mechanisms in paper using the acoustic emission monitoring technique

This paper investigates the use of the acoustic emission (AE) monitoring technique for use in identifying the damage mechanisms present in paper associated with its production process. The microscopic structure of paper consists of a random mesh of paper fibres connected by hydrogen bonds. This implies the existence of two damage mechanisms, the failure of a fibre-fibre bond and the failure of a fibre. This paper describes a hybrid mathematical model which couples the mechanics of the mass-spring model to the acoustic wave propagation model for use in generating the acoustic signal emitted by complex structures of paper fibres under strain. The derivation of the mass-spring model can be found in [1,2], with details of the acoustic wave equation found in [3,4]. The numerical implementation of the vibro-acoustic model is discussed in detail with particular emphasis on the damping present in the numerical model. The hybrid model uses an implicit solver which intrinsically introduces artificial damping to the solution. The artificial damping is shown to affect the frequency response of the mass-spring model, therefore certain restrictions on the simulation time step must be enforced so that the model produces physically accurate results. The hybrid mathematical model is used to simulate small fibre networks to provide information on the acoustic response of each damage mechanism. The simulated AEs are then analysed using a continuous wavelet transform (CWT), described in [5], which provides a two dimensional time-frequency representation of the signal. The AEs from the two damage mechanisms show different characteristics in the CWT so that it is possible to define a fibre-fibre bond failure by the criteria listed below. The dominant frequency components of the AE must be at approximately 250 kHz or 750 kHz. The strongest frequency component may be at either approximately 250 kHz or 750 kHz. The duration of the frequency component at approximately 250 kHz is longer than that of the frequency component at approximately 750 kHz. Similarly, the criteria for identifying a fibre failure are given below. The dominant frequency component of the AE must be greater than 800 kHz. The duration of the dominant frequency component must be less than 5.00E-06 seconds. The dominant frequency component must be present at the front of the AE. Essentially, the failure of a fibre-fibre bond produces a low frequency wave and the failure of a fibre produces a high frequency pulse. Using this theoretical criteria, it is now possible to train an intelligent classifier such as the Self-Organising Map (SOM) [6] using the experimental data. First certain features must be extracted from the CWTs of the AEs for use in training the SOM. For this work, each CWT is divided into 200 windows of 5E-06s in duration covering a 100 kHz frequency range. The power ratio for each windows is then calculated and used as a feature. Having extracted the features from the AEs, the SOM can now be trained, but care is required so that the both damage mechanisms are adequately represented in the training set. This is an issue with paper as the failure of the fibre-fibre bonds is the prevalent damage mechanism. Once a suitable training set is found, the SOM can be trained and its performance analysed. For the SOM described in this work, there is a good chance that it will correctly classify the experimental AEs.

Policy-driven self-management for an automotive middleware

This paper describes work towards the deployment of self-managing capabilities into an advanced middleware for automotive systems. The middleware will support a range of futuristic use-cases requiring context-awareness and dynamic system configuration. Several use-cases are described and their specific context-awareness requirements identified. The discussion is accompanied by a justification for the selection of policy-based computing as the autonomics technique to drive the self-management. The specific policy technology to be deployed is described briefly, with a focus on its specific features that are of direct relevance to the middleware project. A selected use-case is explored in depth to illustrate the extent of dynamic behaviour achievable in the proposed middleware architecture, which is composed of several policy-configured services. An early demonstration application which facilitates concept evaluation is presented and a sequence of typical device-discovery events is worked through

Using hypnosis to facilitate direct observation of multiple tics and self-monitoring in a typically developing teenager

A hypnotic induction technique was used to facilitate direct observation of multiple tics in a typically developing teenager in a home setting. A comprehensive habit reversal program then was implemented, including awareness training, competing response training, relaxation training, self-monitoring, social support and contingency management. Duration of relaxation was then self-monitored using a changing criterion design. The procedure eliminated multiple tics and achieved long-term maintenance of treatment gains. Implications for assessing and treating tics are discussed.

Self-cooling of a micro-mirror by radiation pressure

Cooling of mechanical resonators is currently a popular topic in many fields of physics including ultra-high precision measurements, detection of gravitational waves and the study of the transition between classical and quantum behaviour of a mechanical system. Here we report the observation of self-cooling of a micromirror by radiation pressure inside a high-finesse optical cavity. In essence, changes in intensity in a detuned cavity, as caused by the thermal vibration of the mirror, provide the mechanism for entropy flow from the mirror's oscillatory motion to the low-entropy cavity field. The crucial coupling between radiation and mechanical motion was made possible by producing free-standing micromirrors of low mass (m approximately 400 ng), high reflectance (more than 99.6%) and high mechanical quality (Q approximately 10,000). We observe cooling of the mechanical oscillator by a factor of more than 30; that is, from room temperature to below 10 K. In addition to purely photothermal effects we identify radiation pressure as a relevant mechanism responsible for the cooling. In contrast with earlier experiments, our technique does not need any active feedback. We expect that improvements of our method will permit cooling ratios beyond 1,000 and will thus possibly enable cooling all the way down to the quantum mechanical ground state of the micromirror.

A novel shrinkage technique based on the normal inverse Gaussian density model

This paper proposes a novel image denoising technique based on the normal inverse Gaussian (NIG) density model using an extended non-negative sparse coding (NNSC) algorithm proposed by us. This algorithm can converge to feature basis vectors, which behave in the locality and orientation in spatial and frequency domain. Here, we demonstrate that the NIG density provides a very good fitness to the non-negative sparse data. In the denoising process, by exploiting a NIG-based maximum a posteriori estimator (MAP) of an image corrupted by additive Gaussian noise, the noise can be reduced successfully. This shrinkage technique, also referred to as the NNSC shrinkage technique, is self-adaptive to the statistical properties of image data. This denoising method is evaluated by values of the normalized signal to noise rate (SNR). Experimental results show that the NNSC shrinkage approach is indeed efficient and effective in denoising. Otherwise, we also compare the effectiveness of the NNSC shrinkage method with methods of standard sparse coding shrinkage, wavelet-based shrinkage and the Wiener filter. The simulation results show that our method outperforms the three kinds of denoising approaches mentioned above.

Bond and Interfacial Properties of Reinforcement in Self-Compacting Concrete

This paper reports a study carried out to assess the impact of the use of self-compacting concrete (SCC) on bond and interfacial properties around steel reinforcement in practical concrete element. The pull-out tests were carried out to determine bond strength between reinforcing steel bar and concrete, and the depth-sensing nano-indentation technique was used to evaluate the elastic modulus and micro-strength of the interracial transition zone (ITZ) around steel reinforcement. The bond and interracial properties around deformed steel bars in different SCC mixes with strength grades of 35 MPa and 60 MPa (C35, C60) were examined together with those in conventional vibrated reference concrete with the same strength grades. The results showed that the maximum bond strength decreased when the diameter of the steel bar increased from 12 to 20 mm. The normalised bond strengths of the SCC mixes were found to be about 10-40% higher than those of the reference mixes for both bar diameters (12 and 20 mm). The study of the interfacial properties revealed that the elastic modulus and the micro-strength of the ITZ were lower on the bottom side of a horizontal steel bar than on the top side, particularly for the vibrated reference concrete. The difference of ITZ properties between top and bottom side of the horizontal steel bar appeared to be less pronounced for the SCC mixes than for the corresponding reference mixes.

Self-potential signatures associated with an injection experiment at an in situ biological permeable reactive barrier

Strategies available to evaluate the performance of in situ permeable reactive barriers are currently not well developed and often rely on fluid and media sampling directly from the permeable reactive barrier (PRB). Here, we investigate the utility of the self-potential (SP) method as a technique to monitor in situ PRB performance. Our field study was conducted at in situ biological PRB in Portadown, Northern Ireland, UK, which was emplaced to assist in the remediation of groundwater contamination (e.g., hydrocarbons, ammonia) that resulted from the operations and waste disposal practices of a former gasworks. Borehole SP measurements were collected during the injection of contaminant groundwater slugs in an attempt to monitor/detect the response of the microbial activity associated with the breakdown of the added contaminants into the PRB. In addition, an uncontaminated groundwater slug was injected into a different portion of the PRB as a ‘control’ and SP measurements were collected for comparison to the SP response of the contaminant slugs. The results of the SP signals due to the contaminant injections show that the magnitude of the response was relatively small (<10 mV) yet showed a consistent decrease during both contaminant injections. The net decrease in SP recorded during the contaminant injections slowly rebounded to near background values through ~44 hours post-injection. The SP response during the uncontaminated injection showed a slight, albeit negligible (within the margin of error), 1 mV increase in the measured SP signals, in contrast to the contaminant injections. The results of the SP signals recorded from the uncontaminated groundwater injection also persisted through a period of ~47 hours after injection but show a net increase in SP relative to pre-injection values. Based on the difference in SP response between the contaminated and uncontaminated injections, we suggest that the responses are likely to be the result of differences in the chemistry of the injection types (contaminated versus uncontaminated) and in situ groundwater. We argue that the SP signals associated with the contaminated injections are dominated by diffusion (electrochemical) potential, possibly enhanced by a microbial effect. While the results of our investigation show a consistent SP response associated with the contaminant injections that is dominated by diffusional effects, further studies are required in order to better understand the effect of microbial activity on SP signals and the potential utility for the SP method to detect/monitor changes that may be indicative of biological PRB performance.

Self-generated expressions of residual complaints following brain injury

Following brain injury there is often a prolonged period of deteriorating psychological condition, despite neurological stability or improvement. This is presumably consequent to the remission of anosognosia and the realisation of permanently worsened status. This change is hypothesised to be directed partially by the socially mediated processes which play a role in generating self-awareness and which here direct the reconstruction of the self as a permanently injured person. However, before we can understand this process of redevelopment, we need an unbiassed technique to monitor self-awareness. Semi-structured interviews were conducted with 30 individuals with long-standing brain injuries to capture their spontaneous complaints and their level of insight into the implications of their difficulties. The focus was on what the participants said in their own words, and the extent to which self-knowledge of difficulties was spontaneously salient to the participants. Their responses were subjected to content analysis. Most participants were able to say that they had brain injuries and physical difficulties, many mentioned memory and attentional problems and a few made references to a variety of emotional disturbances. Content analysis of data from unbiassed interviews can reveal the extent to which people with brain injuries know about their difficulties. Social constructionist accounts of self-awareness and recovery are supported.