7 resultados para Semi-arid area

em Cambridge University Engineering Department Publications Database


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This work describes the deposition, annealing and characterisation of semi-insulating oxygen-doped silicon films at temperatures compatible with polysilicon circuitry on glass. The semi-insulating layers are deposited by the plasma enhanced chemical vapour deposition technique from silane (SiH4), nitrous oxide (N2O) and helium (He) gas mixtures at a temperature of 350 °C. The as-deposited films are then furnace annealed at 600 °C which is the maximum process temperature. Raman analysis shows the as-deposited and annealed films to be completely amorphous. The most important deposition variable is the N2O SiH4 gas ratio. By varying the N2O SiH4 ratio the conductivity of the annealed films can be accurately controlled, for the first time, down to a minimum of ≈10-7Ω-1cm-1 where they exhibit a T -1 4 temperature dependence indicative of a hopping conduction mechanism. Helium dilution of the reactant gases is shown to improve both film uniformity and reproducibility. A model for the microstructure of these semi-insulating amorphous oxygen-doped silicon films is proposed to explain the observed physical and electrical properties. © 1995.

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This work describes the annealing and characterisation of semi-insulating oxygen-doped silicon films deposited by the Plasma Enhanced Chemical Vapour Deposition (PECVD) technique from silane (SiH4), nitrous oxide (N2O) and helium (He) gas mixtures. The maximum process temperature is chosen to be compatible with large area polycrystalline silicon (poly-Si) circuitry on glass. The most important deposition variable is shown to be the N2O SiH4 gas ratio. Helium dilution results in improved film uniformity and reproducibility. Raman analysis shows the 'as-deposited' and annealed films to be completely amorphous. A model for the microstructure of these Semi-Insulating Amorphous Oxygen-doped Silicon (SIAOS) films is proposed to explain the observed physical and electrical properties. © 1995.

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Traffic classification using machine learning continues to be an active research area. The majority of work in this area uses off-the-shelf machine learning tools and treats them as black-box classifiers. This approach turns all the modelling complexity into a feature selection problem. In this paper, we build a problem-specific solution to the traffic classification problem by designing a custom probabilistic graphical model. Graphical models are a modular framework to design classifiers which incorporate domain-specific knowledge. More specifically, our solution introduces semi-supervised learning which means we learn from both labelled and unlabelled traffic flows. We show that our solution performs competitively compared to previous approaches while using less data and simpler features. Copyright © 2010 ACM.

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An improved technique for transferring large area graphene grown by chemical vapor deposition on copper is presented. It is based on mechanical separation of the graphene/copper by H2 bubbles during H2O electrolysis, which only takes a few tens of seconds while leaving the copper cathode intact. A semi-rigid plastic frame in combination with thin polymer layer span on graphene gives a convenient way of handling- and avoiding wrinkles and holes in graphene. Optical and electrical characterizations prove the graphene quality is better than that obtained by traditional wet etching transfer. This technique appears to be highly reproducible and cost efficient. © 2013 American Institute of Physics.