Investigation into IGBT dV/dt during turn-off and its temperature dependence

In many power converter applications, particularly those with high variable loads, such as traction and wind power, condition monitoring of the power semiconductor devices in the converter is considered desirable. Monitoring the device junction temperature in such converters is an essential part of this process. In this paper, a method for measuring the insulated gate bipolar transistor (IGBT) junction temperature using the collector voltage dV/dt at turn-OFF is outlined. A theoretical closed-form expression for the dV/dt at turn-OFF is derived, closely agreeing with experimental measurements. The role of dV/dt in dynamic avalanche in high-voltage IGBTs is also discussed. Finally, the implications of the temperature dependence of the dV/dt are discussed, including implementation of such a temperature measurement technique. © 2006 IEEE.

Photo-assisted hydrosilylation of silicon nanoparticles: Dependence of particle size on grafting chemistry

Silicon nanoparticles between 2.5 nm and 30 nm in diameter were functionalized by means of photoassisted hydrosilylation reactions in the aerosol phase with terminal alkenes of varying chain length. Using infrared spectroscopy and nuclear magnetic resonance, the chemical composition of the alkyl layer was determined for each combination of particle size and alkyl chain length. The spectroscopic techniques were used to determine that smaller particles functionalized with short chains in the aerosol phase tend to attach to the interior (β) alkenyl carbon atom, whereas particles >10 nm in diameter exhibit attachment primarily with the exterior (α) alkenyl carbon atom, regardless of chain length. © 2011 American Chemical Society.

Faecal pellets in deep marine soft clay crusts: Implications for hot-oil pipeline design

In recent years, the presence of crusts within near surface sediments found in deep water locations off the west coast of Angola has been of interest to hot-oil pipeline designers. The origin for these crusts is considered to be of biological origin, based on the observation of thousands of faecal pellets in natural crust core samples. This paper presents the results of laboratory tests undertaken on natural and faecal pellet-only samples. These tests investigate the role faecal pellets play in modifying the gemechanical behaviour of clayey sediments. It is found that faecal pellets are able to significantly alter both the strength and the average grain-size of natural sediments, and therefore, influence the permeability and stiffness. Hot-oil pipelines self-embed into and subsequent shear on crusts containing faecal pellets. Being able to predict the time required for installed pipelines to consolidate the underlying sediment and thus, how soon after pipe-laying, the interface strength will develop is of great interest to pipeline designers. It is concluded from wet-sieving samples before and after oedometer tests, that the process of pipe laying is unlikely to destroy pellets. They will therefore, be a major constituent of the sediment subject to soil-pipeline shearing behaviour during axial pipe-walking and lateral buckling. Based on the presented results, a discussion highlighting the key implications for pipeline design is therefore provided. Copyright © 2011 by ASME.

Concentration dependence of the Er3+ visible and infrared luminescence in Y2-x Erx O3 thin films on Si

Y2-x Erx O3 thin films, with x varying between 0 and 0.72, have been successfully grown on crystalline silicon (c-Si) substrates by radio-frequency magnetron cosputtering of Y2 O 3 and Er2 O3 targets. As-deposited films are polycrystalline, showing the body-centered cubic structure of Y2 O3, and show only a slight lattice parameter contraction when x is increased, owing to the insertion of Er ions. All the films exhibit intense Er-related optical emission at room temperature both in the visible and infrared regions. By studying the optical properties for different excitation conditions and for different Er contents, all the mechanisms (i.e., cross relaxations, up-conversions, and energy transfers to impurities) responsible for the photoluminescence (PL) emission have been identified, and the existence of two different well-defined Er concentration regimes has been demonstrated. In the low concentration regime (x up to 0.05, Er-doped regime), the visible PL emission reaches its highest intensity, owing to the influence of up-conversions, thus giving the possibility of using Y2-x Er x O3 films as an up-converting layer in the rear of silicon solar cells. However, most of the excited Er ions populate the first two excited levels 4I11/2 and 4I13/2, and above a certain excitation flux a population inversion condition between the former and the latter is achieved, opening the route for the realization of amplifiers at 2.75 μm. Instead, in the high concentration regime (Er-compound regime), an increase in the nonradiative decay rates is observed, owing to the occurrence of cross relaxations or energy transfers to impurities. As a consequence, the PL emission at 1.54 μm becomes the most intense, thus determining possible applications for Y2-x Erx O 3 as an infrared emitting material. © 2009 American Institute of Physics.

Gaussian Process Vine Copulas for Multivariate Dependence

Copulas allow to learn marginal distributions separately from the multivariate dependence structure (copula) that links them together into a density function. Vine factorizations ease the learning of high-dimensional copulas by constructing a hierarchy of conditional bivariate copulas. However, to simplify inference, it is common to assume that each of these conditional bivariate copulas is independent from its conditioning variables. In this paper, we relax this assumption by discovering the latent functions that specify the shape of a conditional copula given its conditioning variables We learn these functions by following a Bayesian approach based on sparse Gaussian processes with expectation propagation for scalable, approximate inference. Experiments on real-world datasets show that, when modeling all conditional dependencies, we obtain better estimates of the underlying copula of the data.