A high frequency, low voltage stackable full bridge module for modular multilevel cascade converter (MMCC) research

A new small full bridge module for MMCC research is presented. Each full bridge converter cell is a single small (65 × 30 mm) multilayer PCB with two low voltage high current (22 V, 40 A) integrated half bridge ICs and the necessary isolated control signals and auxiliary power supply (2500 V isolation). All devices are surface mount, minimising cell height (4 mm) and parasitic inductance. Each converter cell can be physically stacked with PCB connectors propagating the control signals and inter-cell power connections. Many cells can be trivially stacked to create a large multilevel converter leg with isolated auxiliary power and control signals. Any of the MMCC family members is then easily formed. With a change in placement of stacking connector, a parallel connection of bridges is also possible. Operation of a nine level parallel full bridge is demonstrated at 12 V and 384 kHz switching frequency delivering a 30 W 2 kHz sinewave into a resistive load. A number of new applications for this novel module aside from MMCC development are listed.

An evaluation of the neocognitron

We describe a sequence of experiments investigating the strengths and limitations of Fukushima's neocognitron as a handwritten digit classifier. Using the results of these experiments as a foundation, we propose and evaluate improvements to Fukushima's original network in an effort to obtain higher recognition performance. The neocognitron's performance is shown to be strongly dependent on the choice of selectivity parameters and we present two methods to adjust these variables. Performance of the network under the more effective of the two new selectivity adjustment techniques suggests that the network fails to exploit the features that distinguish different classes of input data. To avoid this shortcoming, the network's final layer cells were replaced by a nonlinear classifier (a multilayer perceptron) to create a hybrid architecture. Tests of Fukushima's original system and the novel systems proposed in this paper suggest that it may be difficult for the neocognitron to achieve the performance of existing digit classifiers due to its reliance upon the supervisor's choice of selectivity parameters and training data. These findings pertain to Fukushima's implementation of the system and should not be seen as diminishing the practical significance of the concept of hierarchical feature extraction embodied in the neocognitron. © 1997 IEEE.

Error and variance bounds on sigmoidal neurons with weight and input errors

Bounds on the expectation and variance of errors at the output of a multilayer feedforward neural network with perturbed weights and inputs are derived. It is assumed that errors in weights and inputs to the network are statistically independent and small. The bounds obtained are applicable to both digital and analogue network implementations and are shown to be of practical value.

Suppressed thermal conductivity of bilayer graphene with vacancy-initiated linkages

Through larger-scale molecular dynamics simulations, we investigated the impacts from vacancy-initiated linkages on the thermal conductivity of bilayer graphene sheets (of size L × W = 24.5 nm × 3.7 nm). Three different interlayer linkages, including divacancy bridging, “spiro” interstitial bridging and Frenkel pair defects, are considered. It is found that the presence of interlayer linkages induces a significant degradation in the thermal conductivity of the bilayer graphene sheet. The degradation is strongly dependent on the interlayer linkage type, concentration and location. More importantly, the linkages that contain vacancies lead to more severe suppression of the thermal conductivity, in agreement with theoretical predictions that vacancies induce strong phonon scattering. Our finding provides useful guidelines for the application of multilayer graphene sheets in practical thermal management.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

Effect of covalent functionalisation on thermal transport across graphene-polymer interfaces

This paper is concerned with the interfacial thermal resistance for polymer composites reinforced by various covalently functionalised graphene. By using molecular dynamics simulations, the obtained results show that the covalent functionalisation in graphene plays a significant role in reducing the graphene-paraffin interfacial thermal resistance. This reduction is dependent on the coverage and type of functional groups. Among the various functional groups, butyl is found to be the most effective in reducing the interfacial thermal resistance, followed by methyl, phenyl and formyl. The other functional groups under consideration such as carboxyl, hydroxyl and amines are found to produce negligible reduction in the interfacial thermal resistance. For multilayer graphene with a layer number up to four, the interfacial thermal resistance is insensitive to the layer number. The effects of the different functional groups and the layer number on the interfacial thermal resistance are also elaborated using the vibrational density of states of the graphene and the paraffin matrix. The present findings provide useful guidelines in the application of functionalised graphene for practical thermal management.

New microscale vertically oriented organic photovoltaics cells

We initially look at the changing energy environment and how that can have a dramatic change on the potential of alternative energies, in particular those of organic photovoltaicvs (OPV) cells. In looking at OPV's we also address the aspects of where we are with the current art and why we may not be getting the best from our materials. In doing so, we propose the idea of changing how we build organic photovoltaics by addressing the best method to contain light within the devices. Our initial effort is in addressing how these microscale optical concentrators work in the form of optical fibers in terms of absorption. We have derived a mathematical method which takes account of the input angle of light to achieve optimum absorption. However, in doing so we also address the complex issue how the changing refractive indices in a multilayer device can alter how we input the light. We have found that by knowing the materials refractive index our model takes into account the incident plane, meridonal plane, cross sectional are and path length to ensure optical angular input. Secondly, we also address the practicalities of making such vertical structures the greater issue of changing light intensity incident on a solar cell and how that aspects alters how we view the performance of organic solar cells.

Graphene with patterned fluorination: Morphology modulation and implications

Recent years have witnessed a large volume of works on the modification of graphene; however, an understanding of the associated morphology or mechanical properties changes is still lacking, which is vital for its engineering implementation. By taking the C4F fluorination as an example, we find that the morphology of both graphene sheet (GS) and graphene nanoribbon (GNR) can be effectively tailored by fluorination patterning via molecular dynamics simulations. The fluorine atom produces out-of-plane forces which trigger several intriguing morphology changes to monolayer graphene, including zigzag, folded, ruffle, nanoscroll, and chain structures. Notably, for multilayer GNR, the delamination and climbing phenomena of the surface layer are observed. Further studies show that the fluorination pattern can also be utilized to modulate the mechanical properties of graphene, e.g., about 40% increase of the effective yield strain is observed for the examined GNR with fluorination patterns. This study not only demonstrates the significant impacts on the morphology of graphene from fluorination but also suggests an effective avenue to tailor the morphology and thus mechanical properties of GS and GNR.

Borax Mediated Layer-by-Layer Self-Assembly of Neutral Poly(vinyl alcohol) and Chitosan

We report a multilayer film of poly(vinyl alcohol) (PVA)-borate complex and chitosan by using a layer-by-layer approach. PVA is an uncharged polymer, but hydroxyl functional groups of PVA can be crosslinked by using borax as a cross-linking agent. As a result electrostatic charges and intra- and interchain cross-links are introduced in the PVA chain and provide physically cross-linked networks. The PVA-borate was then deposited on a flat Substrate as well as on colloidal particles with chitosan as an oppositely charged polyelectrolyte. Quartz crystal microbalance. scanning electron microscopy, and atomic force microscopy were used to follow the growth of thin film oil flat substrate. Analogous experiments were performed on melamine formaldehyde colloidal particles (3-3.5 mu m) to quantify the process for the preparation of hollow rnicrocapsules. Removal of the core in 0.1 N HCI results in hollow microcapsules. Characterization of microcapsules by transmission electron microscopy revealed formation of stable microcapsules. Further, self-assembly of PVA-borate/chitosan was loaded with the anticancer drug doxorubicin, and release rates were determined at different pH Values to highlight the drug delivery potential of this system.

Layer-by-layer self-assembly of modified hyaluronic acid/chitosan based on hydrogen bonding

The fabrication of hydrogen bonded polymer self-assembly for drug delivery has been accomplished via layer-by-layer sequential assembly from aqueous solution. In this study, the self-assembly was constructed based on hydrogen bonding between DNA base (adenine and thymine) pairs substituted on the backbone of chitosan and hyaluronic acid. Chitosan was modified with adenine, whereas hyaluronic acid was modified with thymine. Subsequently, these two polymers were sequentially absorbed on flat substrate by taking advantage of interactions of DNA base pairs via hydrogen bonding. Interlayer hydrogen bonding of these two polymers produces stable multilayer film without using any cross-linking agent. Thin film formation on quartz substrate has been monitored with UV-vis spectra and an AFM study. Formation of multilayer hydrogen-bonded thin film has been further confirmed with SEM. Encapsulation and release behavior of the therapeutic drug from the multilayer thin film at different conditions has been illustrated using UV-vis spectra. Cell viability of modified polymers using MTT assay confirmed no cytotoxic effect.

Electron Spectroscopic Studies of Oxygen and Carbon Dioxide Adsorbed on Metal Surfaces

Adsorption of oxygen on Ni, Cu, Pd, Ag, and Au surfaces has been investigated by employing UV and X-ray photoelectron spectrscopy as well as electron energy loss spectroscopy (EELS). Molecularly chemisorbed (singlet) oxygen is found on Ni, Cu, Ag, and Au surfaces showing features such as stabilization of the rB* orbital, destabilization of the .nu orbital, higher O(1s) binding energy than the atomic species, and a band 2-3 eV below the Fermi level due to metal d-O(2p)u* interaction. 0-0 and metal-oxygen stretching frequencies have been observed in EELS. Physical adsorption of O2 is found to occur on Pd and Ni surfaces, only at high exposures in the latter case. Physical adsorption and multilayer condensation of CO, on metal surfaces are distinguished by characteristic relaxation shifts in UPS as well as O(1s) binding energies. Adsorption of CO on a Ni surface covered with presorbed atomic oxygen gives rise to C02.

Encapsulation and release of rifampicin using poly(vinyl pyrrolidone)-poly (methacrylic acid) polyelectrolyte capsules

Poly(vinyl pyrrolidone) and poly(methacrylic acid) multilayer capsules based on hydrogen bonding have been prepared by the layer-by-layer approach and used to encapsulate and release rifampicin, an antituberculosis drug. Removal of silica core using a buffer of ammonium fluoride and hydrofluoric acid at about pH 3 was found to produce better capsules than hydrofluoric acid alone. An eight-layered capsule had a wall thickness of 20 rim. Maximum encapsulation was found to be about 86 mu g at 40 degrees C with 1 +/- 0.2 x 10(6) capsules. Release studies showed a burst kind of release and maximum release was obtained above pH 7 where the capsules disintegrate rapidly thereby releasing the drug in a short period. Interactions studies with Mycobacterium smegmatis showed that the capsules were cytocompatible and the released drug functioned with the same efficacy as the free drug.

Using multi-label classification for acoustic pattern detection and assisting bird species surveys

Acoustics is a rich source of environmental information that can reflect the ecological dynamics. To deal with the escalating acoustic data, a variety of automated classification techniques have been used for acoustic patterns or scene recognition, including urban soundscapes such as streets and restaurants; and natural soundscapes such as raining and thundering. It is common to classify acoustic patterns under the assumption that a single type of soundscapes present in an audio clip. This assumption is reasonable for some carefully selected audios. However, only few experiments have been focused on classifying simultaneous acoustic patterns in long-duration recordings. This paper proposes a binary relevance based multi-label classification approach to recognise simultaneous acoustic patterns in one-minute audio clips. By utilising acoustic indices as global features and multilayer perceptron as a base classifier, we achieve good classification performance on in-the-field data. Compared with single-label classification, multi-label classification approach provides more detailed information about the distributions of various acoustic patterns in long-duration recordings. These results will merit further biodiversity investigations, such as bird species surveys.

Improved photovoltaic performance of dye-sensitized solar cells with modified self-assembling highly ordered mesoporous TiO 2 photoanodes

Strategies for improving the photovoltaic performance of dye-sensitized solar cells (DSSCs) are proposed by modifying highly transparent and highly ordered multilayer mesoporous TiO 2 photoanodes through nitrogen-doping and top-coating with a light-scattering layer. The mesoporous TiO 2 photoanodes were fabricated by an evaporation-induced self-assembly method. In regard to the modification methods, the light-scattering layer as a top-coating was proved to be superior to nitrogen-doping in enhancing not only the power conversion efficiency but also the fill factor of DSSCs. The optimized bifunctional photoanode consisted of a 30-layer mesoporous TiO 2 thin film (4.15 μm) and a Degussa P25 light-scattering top-layer (4 μm), which gives rise to a ∼200% higher cell efficiency than for unmodified cells and a fill factor of 0.72. These advantages are attributed to its higher dye adsorption, better light scattering, and faster photon-electron transport. Such a photoanode configuration provides an efficient way to enhance the energy conversion efficiency of DSSCs.

Structural, ferroelectric and optical properties of Bi2VO5.5 thin films deposited on platinized silicon {(100) Pt/TiO2/SiO2/Si} substrates

Bismuth vanadate (Bi2VO5.5, BVO) thin films have been deposited by a pulsed laser ablation technique on platinized silicon substrates. The surface morphology of the BVO thin films has been studied by atomic force microscopy (AFM). The optical properties of the BVO thin films were investigated using spectroscopic ellipsometric measurements in the 300–820 nm wavelength range. The refractive index (n), extinction coefficient (k) and thickness of the BVO thin films have been obtained by fitting the ellipsometric experimental data in a four-phase model (air/BVOrough/BVO/Pt). The values of the optical constants n and k that were determined through multilayer analysis at 600 nm were 2.31 and 0.056, respectively. For fitting the ellipsometric data and to interpret the optical constants, the unknown dielectric function of the BVO films was constructed using a Lorentz model. The roughness of the films was modeled in the Brugmann effective medium approximation and the results were compared with the AFM observations.