Gas-phase production of gold-decorated silica nanoparticles.

Gold-decorated silica nanoparticles were synthesized in a two-step process in which silica nanoparticles were produced by chemical vapor synthesis using tetraethylorthosilicate (TEOS) and subsequently decorated using two different gas-phase evaporative techniques. Both evaporative processes resulted in gold decoration of the silica particles. This study compares the mechanisms of particle decoration for a production method in which the gas and particles remain cool to a method in which the entire aerosol is heated. Results of transmission electron microscopy and visible spectroscopy studies indicate that both methods produce particles with similar morphologies and nearly identical absorption spectra, with peak absorption at 500-550 nm. A study of the thermal stability of the particles using heated-TEM indicates that the gold decoration on the particle surface remains stable at temperatures below 900 °C, above which the gold decoration begins to both evaporate and coalesce.

Gas-phase production of multifunctional composite nanoparticles by photoinduced chemical vapor deposition

As these results indicate, photo-CVD coating is a robust process that allows for the creation of core-shell nanoparticles. In the present work we demonstrated that photo-CVD can effectively coat Fe2O3 particles with silica for purposes of biological applications. TDMA results combined with TEM images indicate that all particles are effectively coated and that particle coating thicknesses can be tuned to desired thickness depending on the application. In addition, the ability to vary coating properties and to coat high concentrations of particles makes this technique of interest for industrial production where uniform properties are needed for large quantities of particles [2]. Copyright © 2010 by ASME.

MCBoost: Multiple classifier boosting for perceptual co-clustering of images and visual features

We present a new co-clustering problem of images and visual features. The problem involves a set of non-object images in addition to a set of object images and features to be co-clustered. Co-clustering is performed in a way that maximises discrimination of object images from non-object images, thus emphasizing discriminative features. This provides a way of obtaining perceptual joint-clusters of object images and features. We tackle the problem by simultaneously boosting multiple strong classifiers which compete for images by their expertise. Each boosting classifier is an aggregation of weak-learners, i.e. simple visual features. The obtained classifiers are useful for object detection tasks which exhibit multimodalities, e.g. multi-category and multi-view object detection tasks. Experiments on a set of pedestrian images and a face data set demonstrate that the method yields intuitive image clusters with associated features and is much superior to conventional boosting classifiers in object detection tasks.

Synthesis of 10 nm Ag nanoparticle polymer composite pastes for low temperature production of high conductivity films

The conversion of silver nanoparticle (NP) paste films into highly conductive films at low sintering temperature is an important requirement for the developing areas of additive fabrication and printed electronics. Ag NPs with a diameter of ∼10 nm were prepared via an improved chemical process to produce viscous paste with a high wt%. The paste consisted of as-prepared Ag NP and an organic vehicle of ethylcellulose that was deposited on glass and Si substrates using a contact lithographic technique. The morphology and conductivity of the imprinted paste film were measured as a function of sintering temperature, sintering time and the percentage ratio of Ag NP and ethylcellulose. The morphology and conductivity were examined using scanning electron microscopy (SEM) and a two-point probe electrical conductivity measurement. The results show that the imprinted films were efficiently converted into conducting states when exposed to sintering temperature in the range of 200-240 °C, this temperature is lower than the previously reported values for Ag paste. © 2010 Elsevier B.V. All rights reserved.

FPGA, physics-based modeling of IGBT and pin diode for hardware co-simulation of complex power electronic converters and systems

This paper presents the steps and the challenges for implementing analytical, physics-based models for the insulated gate bipolar transistor (IGBT) and the PIN diode in hardware and more specifically in field programmable gate arrays (FPGAs). The models can be utilised in hardware co-simulation of complex power electronic converters and entire power systems in order to reduce the simulation time without compromising the accuracy of results. Such a co-simulation allows reliable prediction of the system's performance as well as accurate investigation of the power devices' behaviour during operation. Ultimately, this will allow application-specific optimisation of the devices' structure, circuit topologies as well as enhancement of the control and/or protection schemes.