Production and characterization of ZnO nanoparticles and porous particles by ultrasonic spray pyrolysis using a zinc nitrate precursor

ZnO nanoparticles and porous particles were produced by an ultrasonic spray pyrolysis method using a zinc nitrate precursor at various temperatures under air atmosphere. The effects of reaction temperature on the size and morphology of ZnO particles were investigated. The samples were characterized by energy dispersive spectroscopy, X-ray diffraction, transmission electron microscopy, and scanning electron microscopy. ZnO particles were obtained in a hexagonal crystal structure and the crystallite shapes changed from spherical to hexagonal by elevating the reaction temperature. The crystallite size grew by increasing the temperature, in spite of reducing the residence time in the heated zone. ZnO nanoparticles were obtained at the lowest reaction temperature and ZnO porous particles, formed by aggregation of ZnO nanoparticles due to effective sintering, were prepared at higher temperatures. The results showed that the properties of ZnO particles can be controlled by changing the reaction temperature in the ultrasonic spray pyrolysis method.     

Wavelength-scalable hollow optical fibres with large photonic bandgaps for CO2 laser transmission

Conventional solid-core optical fibres require highly transparent materials. Such materials have been difficult to identify owing to the fundamental limitations associated with the propagation of light through solids, such as absorption, scattering and nonlinear effects. Hollow optical fibres offer the potential to minimize the dependence of light transmission on fibre material transparency. Here we report on the design and drawing of a hollow optical fibre lined with an interior omnidirectional dielectric mirror. Confinement of light in the hollow core is provided by the large photonic bandgaps established by the multiple alternating submicrometre-thick layers of a high-refractive-index glass and a low-refractive-index polymer. The fundamental and high-order transmission windows are determined by the layer dimensions and can be scaled from 0.75 to 10.6 micro m in wavelength. Tens of metres of hollow photonic bandgap fibres for transmission of carbon dioxide laser light at 10.6 micro m wavelength were drawn. The transmission losses are found to be less than 1.0 dB m(-1), orders of magnitude lower than those of the intrinsic fibre material, thus demonstrating that low attenuation can be achieved through structural design rather than high-transparency material selection.     

Mechanical properties and microstructure of composites produced by recycling metal chips

In this study, the processing and mechanical properties of porous metal matrix composites (MMCs) composed of spheroidal cast iron chips (GGG40) and bronze chips (CuSn10) and formed by hot isostatic pressing were investigated. Bronze chips (CuSn10) were used as a matrix component, and spheroidal cast iron (GGG40) chips were used as a reinforcement component. The MMCs were produced with different CuSn10 contents (90wt%, 80wt%, 70wt%, and 60wt%). The hot isostatic pressing process was performed under three different pressures and temperatures. The produced MMCs were characterized using density tests, Brinell hardness tests, and compression tests. In addition, the consolidation mechanism was investigated by X-ray diffraction (XRD) analysis and scanning electron microscopy. The test results were compared with those for bulk CuSn10 and bulk GGG40. Mechanical tests results revealed that the metallic chips can be recycled by using hot pressing and that the mechanical properties of the produced MMCs were similar to those of bulk CuSn10. XRD and microscopy studies showed that no intermetallic compounds formed between the metallic chips. The results showed that the CuSn10 and GGG40 chips were consolidated by mechanical interlocking.     

Utilization of waste polyethylene terephthalate as a reducing agent in the reduction of iron ore composite pellets

The increasing consumption of plastics inevitably results in increasing amounts of waste plastics. Because of their long degradation periods, these wastes negatively affect the natural environment. Numerous studies have been conducted to recycle and eliminate waste plastics. The potential for recycling waste plastics in the iron and steel industry has been underestimated; the high C and H contents of plastics may make them suitable as alternative reductants in the reduction process of iron ore. This study aims to substitute plastic wastes for coal in reduction melting process and to investigate their performance during reduction at high temperature. We used a common type of waste plastic, polyethylene terephthalate (PET), because of its high carbon and hydrogen contents. Composite pellets containing PET wastes, coke, and magnetite iron ore were reduced at selected temperatures of 1400 and 1450°C for reduction time from 2 to 10 min to investigate the reduction melting behavior of these pellets. The results showed that an increased temperature and reduction time increased the reduction ratio of the pellets. The optimum experimental conditions for obtaining metallic iron (iron nuggets) were reduction at 1450°C for 10 min using composite pellets containing 60% PET and 40% coke.     

Evaluating predictive performance of value‐at‐risk models in emerging markets: a reality check

We investigate the predictive performance of various classes of value‐at‐risk (VaR) models in several dimensions—unfiltered versus filtered VaR models, parametric versus nonparametric distributions, conventional versus extreme value distributions, and quantile regression versus inverting the conditional distribution function. By using the reality check test of White (2000), we compare the predictive power of alternative VaR models in terms of the empirical coverage probability and the predictive quantile loss for the stock markets of five Asian economies that suffered from the 1997–1998 financial crisis. The results based on these two criteria are largely compatible and indicate some empirical regularities of risk forecasts. The Riskmetrics model behaves reasonably well in tranquil periods, while some extreme value theory (EVT)‐based models do better in the crisis period. Filtering often appears to be useful for some models, particularly for the EVT models, though it could be harmful for some other models. The CaViaR quantile regression models of Engle and Manganelli (2004) have shown some success in predicting the VaR risk measure for various periods, generally more stable than those that invert a distribution function. Overall, the forecasting performance of the VaR models considered varies over the three periods before, during and after the crisis. Copyright © 2006 John Wiley & Sons, Ltd.