324 resultados para Chemical deposition
Resumo:
Gold is often considered as an inert material but it has been unequivocally demonstrated that it possesses unique electronic, optical, catalytic and electrocatalytic properties when in a nanostructured form.[1] For the latter the electrochemical behaviour of gold in aqueous media has been widely studied on a plethora of gold samples, including bulk polycrystalline and single-crystal electrodes, nanoparticles, evaporated films as well as electrodeposited nanostructures, particles and thin films.[1b, 2] It is now well-established that the electrochemical behaviour of gold is not as simple as an extended double-layer charging region followed by a monolayer oxide-formation/-removal process. In fact the so-called double-layer region of gold is significantly more complicated and has been investigated with a variety of electrochemical and surface science techniques. Burke and others[3] have demonstrated that significant processes due to the oxidation of low lattice stabilised atoms or clusters of atoms occur in this region at thermally and electrochemically treated electrodes which were confirmed later by Bond[4] to be Faradaic in nature via large-amplitude Fourier transformed ac voltammetric experiments. Supporting evidence for the oxidation of gold in the double-layer region was provided by Bard,[5] who used a surface interrogation mode of scanning electrochemical microscopy to quantify the extent of this process that forms incipient oxides on the surface. These were estimated to be as high as 20% of a monolayer. This correlated with contact electrode resistance measurements,[6] capacitance measurements[7] and also electroreflection techniques...
Resumo:
Globally, obesity and diabetes (particularly type 2 diabetes) represents a major challenge to world health. Despite decades of intense research efforts, the genetic basis involved in diabetes pathogenesis & conditions associated with obesity are still poorly understood. Recent advances have led to exciting new developments implicating epigenetics as an important mechanism underpinning diabetes and obesity related disease. One epigenetic mechanism known as the "histone code" describes the idea that specific patterns of post-translational modifications to histones act like a molecular "code" recognised and used by non-histone proteins to regulate specific chromatin functions. One modification which has received significant attention is that of histone acetylation. The enzymes which regulate this modification are described as lysine acetyltransferases or KATs and histone deacetylases or HDACs. Due to their conserved catalytic domain HDACs have been actively targeted as a therapeutic target. Some of the known inhibitors of HDACs (HDACi) have also been shown to act as "chemical chaperones" to alleviate diabetic symptoms. In this review, we discuss the available evidence concerning the roles of HDACs in regulating chaperone function and how this may have implications in the management of diabetes. © 2009 Bentham Science Publishers Ltd.
Resumo:
This thesis reports a comprehensive study on the physical and chemical properties of airborne particles in Brisbane, especially around schools. The sources and potential toxicity of the particles were identified, enabling an assessment of the contributing factors to children's exposure at school. The results from this thesis give a quantitative estimate of the range of airborne particles that children are exposed to at urban schools with different traffic conditions.
Resumo:
Taguchi method is for the first time applied to optimize the synthesis of graphene films by copper-catalyzed decomposition of ethanol. In order to find the most appropriate experimental conditions for the realization of thin high-grade films, six experiments suitably designed and performed. The influence of temperature (1000–1070 °C) and synthesis duration (1–30 min) and hydrogen flow (0–100 sccm) on the number of graphene layers and defect density in the graphitic lattice was ranked by monitoring the intensity of the 2D- and D-bands relative to the G-band in the Raman spectra. After critical examination and adjusting of the conditions predicted to give optimal results, a continuous film consisting of 2–4 nearly defect-free graphene layers was obtained.
Resumo:
Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.
Resumo:
Significance: Chronic wounds represent a major burden on global healthcare systems and reduce the quality of life of those affected. Significant advances have been made in our understanding of the biochemistry of wound healing progression. However, knowledge regarding the specific molecular processes influencing chronic wound formation and persistence remains limited. Recent Advances: Generally, healing of acute wounds begins with hemostasis and the deposition of a plasma-derived provisional matrix into the wound. The deposition of plasma matrix proteins is known to occur around the microvasculature of the lower limb as a result of venous insufficiency. This appears to alter limb cutaneous tissue physiology and consequently drives the tissue into a ‘preconditioned’ state that negatively influences the response to wounding. Critical Issues: Processes, such as oxygen and nutrient suppression, edema, inflammatory cell trapping/extravasation, diffuse inflammation, and tissue necrosis are thought to contribute to the advent of a chronic wound. Healing of the wound then becomes difficult in the context of an internally injured limb. Thus, interventions and therapies for promoting healing of the limb is a growing area of interest. For venous ulcers, treatment using compression bandaging encourages venous return and improves healing processes within the limb, critically however, once treatment concludes ulcers often reoccur. Future Directions: Improved understanding of the composition and role of pericapillary matrix deposits in facilitating internal limb injury and subsequent development of chronic wounds will be critical for informing and enhancing current best practice therapies and preventative action in the wound care field.
Resumo:
Australia is a high-potential country for geothermal power with reserves currently estimated in the tens of millions of petajoules, enough to power the nation for at least 1000 years at current usage. However, these resources are mainly located in isolated arid regions where water is scarce. Therefore, wet cooling systems for geothermal plants in Australia are the least attractive solution and thus air-cooled heat exchangers are preferred. In order to increase the efficiency of such heat exchangers, metal foams have been used. One issue raised by this solution is the fouling caused by dust deposition. In this case, the heat transfer characteristics of the metal foam heat exchanger can dramatically deteriorate. Exploring the particle deposition property in the metal foam exchanger becomes crucial. This paper is a numerical investigation aimed to address this issue. Two dimensional (2D) numerical simulations of a standard one-row tube bundle wrapped with metal foam in cross-flow are performed and highlight preferential particle deposition areas.
Resumo:
Australia is a high potential country for geothermal power with reserves currently estimated in the tens of millions of petajoules, enough to power the nation for at least 1000 years at current usage.However, these resources are mainly located in isolated arid regions where water is scarce. Therefore, wet cooling systems for geothermal plants in Australia are the least attractive solution and thus air-cooled heat exchangers are preferred. In order to increase the efficiency of such heat exchangers, metal foams have been used. One issue raised by this solution is the fouling caused by dust deposition. In this case, the heat transfer characteristics of the metal foam heat exchanger can dramatically deteriorate. Exploring the particle deposition property in the metal foam exchanger becomes crucial. This paper is a numerical investigation aimed to address this issue. Two-dimensional(2D numerical simulations of a standard one-row tube bundle wrapped with metal foam in cross-flow are performed and highlight preferential particle deposition areas.
Resumo:
Floods through inundated urban environments constitute a hazard to the population and infrastructure. A series of field measurements were performed in an inundated section of the City of Brisbane (Australia) during a major flood in January 2011. Using an acoustic Doppler velocimeter (ADV), detailed velocity and suspended sediment concentration measurements were conducted about the peak of the flood. The results are discussed with a focus on the safety of individuals in floodwaters and the sediment deposition during the flood recession. The force of the floodwaters in Gardens Point Road was deemed unsafe for individual evacuation. A comparison with past laboratory results suggested that previous recommendations could be inappropriate and unsafe in real flood flows.
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An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.
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Nanomaterials are prone to influence by chemical adsorption because of their large surface to volume ratios. This enables sensitive detection of adsorbed chemical species which, in turn, can tune the property of the host material. Recent studies discovered that single and multi-layer molybdenum disulfide (MoS2) films are ultra-sensitive to several important environmental molecules. Here we report new findings from ab inito calculations that reveal substantially enhanced adsorption of NO and NH3 on strained monolayer MoS2 with significant impact on the properties of the adsorbates and the MoS2 layer. The magnetic moment of adsorbed NO can be tuned between 0 and 1 μB; strain also induces an electronic phase transition between half-metal and metal. Adsorption of NH3 weakens the MoS2 layer considerably, which explains the large discrepancy between the experimentally measured strength and breaking strain of MoS2 films and previous theoretical predictions. On the other hand, adsorption of NO2, CO, and CO2 is insensitive to the strain condition in the MoS2 layer. This contrasting behavior allows sensitive strain engineering of selective chemical adsorption on MoS2 with effective tuning of mechanical, electronic, and magnetic properties. These results suggest new design strategies for constructing MoS2-based ultrahigh-sensitivity nanoscale sensors and electromechanical devices.
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This paper uses examples from the history and practices of multi-national and large companies in the oil, chemical and asbestos industries to examine their legal and illegal despoiling and destruction of the environment and impact on human and non-human life. The discussion draws on the literature on green criminology and state-corporate crime and considers measures and arrangements that might mitigate or prevent such damaging acts. This paper is part of ongoing work on green criminology and crimes of the economy. It places these actions and crimes in the context of a global neo-liberal economic system and considers and critiques the distorting impact of the GDP model of ‘economic health’ and its consequences for the environment.
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Chemically synthesized AgTCNQ exists in two forms that differ in their morphologies (needles and microcrystals) and colors (red and blue). It is now shown that both forms exhibit essentially indistinguishable X-ray diffraction, spectroscopic, and thermochemical data, implying that they are not separate phases, as implied in some literature. Electrochemical reduction of TCNQ((MeCN)) in the presence of Ag+((MeCN)) generates both red and blue AgTCNQ. On glassy carbon, platinum, or indium tin oxide electrodes and at relatively positive deposition potentials, slow growth of high aspect ratio, red needle AgTCNQ crystals occurs. After longer times and at more negative deposition potentials, blue microcrystalline AgTCNQ thin films are favored. Blue AgTCNQ is postulated to be generated via reduction of a Ag+\[(TCNQ(center dot-))(TCNQ)]((MeCN)) intermediate. At even more negative potentials, Ag-(metal) formation inhibits further growth of AgTCNQ. On a gold electrode, Ag-(metal)) deposition occurs at more positive potentials than on the other electrode materials examined. However, surface plasmon resonance data indicate (hat a small potential region is available between the stripping of Ag-(metal)) and the oxidation of TCNQ(center dot-)(MeCN) back to TCNQ(MeCN) where AgTCNQ may form. AgTCNQ in both the red and blue forms also can be prepared electrochemically on a TCNQ((s)) modified electrode in -0.1 M AgNO3(aq) where deposition of Ag(m,,,I) onto the TCNQ((s)) crystals allows a charge transfer process to occur. However, the morphology formed in this solid-solid phase transformation is more difficult to control.
Resumo:
Biodiesel, produced from renewable feedstock represents a more sustainable source of energy and will therefore play a significant role in providing the energy requirements for transportation in the near future. Chemically, all biodiesels are fatty acid methyl esters (FAME), produced from raw vegetable oil and animal fat. However, clear differences in chemical structure are apparent from one feedstock to the next in terms of chain length, degree of unsaturation, number of double bonds and double bond configuration-which all determine the fuel properties of biodiesel. In this study, prediction models were developed to estimate kinematic viscosity of biodiesel using an Artificial Neural Network (ANN) modelling technique. While developing the model, 27 parameters based on chemical composition commonly found in biodiesel were used as the input variables and kinematic viscosity of biodiesel was used as output variable. Necessary data to develop and simulate the network were collected from more than 120 published peer reviewed papers. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture and learning algorithm were optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the coefficient of determination (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found high predictive accuracy of the ANN in predicting fuel properties of biodiesel and has demonstrated the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties. Therefore the model developed in this study can be a useful tool to accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.
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The deposition of biological material (biofouling) onto polymeric contact lenses is thought to be a major contributor to lens discomfort and hence discontinuation of wear. We describe a method to characterize lipid deposits directly from worn contact lenses utilizing liquid extraction surface analysis coupled to tandem mass spectrometry (LESA-MS/MS). This technique effected facile and reproducible extraction of lipids from the contact lens surfaces and identified lipid molecular species representing all major classes present in human tear film. Our data show that LESA-MS/MS is a rapid and comprehensive technique for the characterization of lipid-related biofouling on polymer surfaces.