7 resultados para TRANSPARENT

em CORA - Cork Open Research Archive - University College Cork - Ireland


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Thin layers of indium tin oxide are widely used as transparent coatings and electrodes in solar energy cells, flat-panel displays, antireflection coatings, radiation protection and lithium-ion battery materials, because they have the characteristics of low resistivity, strong absorption at ultraviolet wavelengths, high transmission in the visible, high reflectivity in the far-infrared and strong attenuation in the microwave region. However, there is often a trade-off between electrical conductivity and transparency at visible wavelengths for indium tin oxide and other transparent conducting oxides. Here, we report the growth of layers of indium tin oxide nanowires that show optimum electronic and photonic properties and demonstrate their use as fully transparent top contacts in the visible to near-infrared region for light-emitting devices.

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Unique bimodal distributions of single crystal epitaxially grown In2O3 nanodots on silicon are shown to have excellent IR transparency greater than 87% at IR wavelengths up to 4 μm without sacrificing transparency in the visible region. These broadband antireflective nanodot dispersions are grown using a two-step metal deposition and oxidation by molecular beam epitaxy, and backscattered diffraction confirms a dominant (111) surface orientation. We detail the growth of a bimodal size distribution that facilitates good surface coverage (80%) while allowing a significant reduction in In2O3 refractive index. This unique dispersion offers excellent surface coverage and three-dimensional volumetric expansion compared to a thin film, and a step reduction in refractive index compared to bulk active materials or randomly porous composites, to more closely match the refractive index of an electrolyte, improving transparency. The (111) surface orientation of the nanodots, when fully ripened, allows minimum lattice mismatch strain between the In2O3 and the Si surface. This helps to circumvent potential interfacial weakening caused by volume contraction due to electrochemical reduction to lithium, or expansion during lithiation. Cycling under potentiodynamic conditions shows that the transparent anode of nanodots reversibly alloys lithium with good Coulombic efficiency, buffered by co-insertion into the silicon substrate. These properties could potentially lead to further development of similarly controlled dispersions of a range of other active materials to give transparent battery electrodes or materials capable of non-destructive in situ spectroscopic characterization during charging and discharging.

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Metal oxide thin films are important for modern electronic devices ranging from thin film transistors to photovoltaics and functional optical coatings. Solution processed techniques allow for thin films to be rapidly deposited over a range of surfaces without the extensive processing of comparative vapour or physical deposition methods. The production of thin films of vanadium oxide prepared through dip-coating was developed enabling a greater understanding of the thin film formation. Mechanisms of depositing improved large area uniform coverage on a number of technologically relevant substrates were examined. The fundamental mechanism for polymer-assisted deposition in improving thin film surface smoothness and long range order has been delivered. Different methods were employed for adapting the alkoxide based dip-coating technique to produce a variety of amorphous and crystalline vanadium oxide based thin films. Using a wide range of material, spectroscopic and optical measurement techniques the morphology, structure and optoelectronic properties of the thin films were studied. The formation of pinholes on the surface of the thin films, due to dewetting and spinodal effects, was inhibited using the polymer assisted deposition technique. Uniform thin films with sub 50 nm thicknesses were deposited on a variety of substrates controlled through alterations to the solvent-alkoxide dilution ratios and employing polymer assisted deposition techniques. The effects of polymer assisted deposition altered the crystallized VO thin films from a granular surface structure to a polycrystalline structure composed of high density small in-plane grains. The formation of transparent VO based thin film through Si and Na substrate mediated diffusion highlighted new methods for material formation and doping.

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Transparent thin films can now be site-selectively patterned and positioned on surface using mask-defined electrodeposition of one oxide and overcoating with a different solution-processed oxide, followed by thermal annealing. Annealing allows an interdiffusion process to create a new oxide that is entirely transparent. A primary electrodeposited oxide can be patterned and the secondary oxide coated over the entire substrate to form high color contrast coplanar thin film tertiary oxide. The authors also detail the phase formation and chemical state of the oxide and how the nature of the electrodeposited layer and the overlayer influence the optical clearing of the patterned oxide film.

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We review recent advances in all-optical OFDM technologies and discuss the performance of a field trial of a 2 Tbit/s Coherent WDM over 124 km with distributed Raman amplification. The results indicate that careful optimisation of the Raman pumps is essential. We also consider how all-optical OFDM systems perform favourably against energy consumption when compared with alternative coherent detection schemes. We argue that, in an energy constrained high-capacity transmission system, direct detected all-optical OFDM with 'ideal' Raman amplification is an attractive candidate for metro area datacentre interconnects with ~100 km fibre spans, with an overall energy requirement at least three times lower than coherent detection techniques.

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The aging population in many countries brings into focus rising healthcare costs and pressure on conventional healthcare services. Pervasive healthcare has emerged as a viable solution capable of providing a technology-driven approach to alleviate such problems by allowing healthcare to move from the hospital-centred care to self-care, mobile care, and at-home care. The state-of-the-art studies in this field, however, lack a systematic approach for providing comprehensive pervasive healthcare solutions from data collection to data interpretation and from data analysis to data delivery. In this thesis we introduce a Context-aware Real-time Assistant (CARA) architecture that integrates novel approaches with state-of-the-art technology solutions to provide a full-scale pervasive healthcare solution with the emphasis on context awareness to help maintaining the well-being of elderly people. CARA collects information about and around the individual in a home environment, and enables accurately recognition and continuously monitoring activities of daily living. It employs an innovative reasoning engine to provide accurate real-time interpretation of the context and current situation assessment. Being mindful of the use of the system for sensitive personal applications, CARA includes several mechanisms to make the sophisticated intelligent components as transparent and accountable as possible, it also includes a novel cloud-based component for more effective data analysis. To deliver the automated real-time services, CARA supports interactive video and medical sensor based remote consultation. Our proposal has been validated in three application domains that are rich in pervasive contexts and real-time scenarios: (i) Mobile-based Activity Recognition, (ii) Intelligent Healthcare Decision Support Systems and (iii) Home-based Remote Monitoring Systems.

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It is estimated that the quantity of digital data being transferred, processed or stored at any one time currently stands at 4.4 zettabytes (4.4 × 2 70 bytes) and this figure is expected to have grown by a factor of 10 to 44 zettabytes by 2020. Exploiting this data is, and will remain, a significant challenge. At present there is the capacity to store 33% of digital data in existence at any one time; by 2020 this capacity is expected to fall to 15%. These statistics suggest that, in the era of Big Data, the identification of important, exploitable data will need to be done in a timely manner. Systems for the monitoring and analysis of data, e.g. stock markets, smart grids and sensor networks, can be made up of massive numbers of individual components. These components can be geographically distributed yet may interact with one another via continuous data streams, which in turn may affect the state of the sender or receiver. This introduces a dynamic causality, which further complicates the overall system by introducing a temporal constraint that is difficult to accommodate. Practical approaches to realising the system described above have led to a multiplicity of analysis techniques, each of which concentrates on specific characteristics of the system being analysed and treats these characteristics as the dominant component affecting the results being sought. The multiplicity of analysis techniques introduces another layer of heterogeneity, that is heterogeneity of approach, partitioning the field to the extent that results from one domain are difficult to exploit in another. The question is asked can a generic solution for the monitoring and analysis of data that: accommodates temporal constraints; bridges the gap between expert knowledge and raw data; and enables data to be effectively interpreted and exploited in a transparent manner, be identified? The approach proposed in this dissertation acquires, analyses and processes data in a manner that is free of the constraints of any particular analysis technique, while at the same time facilitating these techniques where appropriate. Constraints are applied by defining a workflow based on the production, interpretation and consumption of data. This supports the application of different analysis techniques on the same raw data without the danger of incorporating hidden bias that may exist. To illustrate and to realise this approach a software platform has been created that allows for the transparent analysis of data, combining analysis techniques with a maintainable record of provenance so that independent third party analysis can be applied to verify any derived conclusions. In order to demonstrate these concepts, a complex real world example involving the near real-time capturing and analysis of neurophysiological data from a neonatal intensive care unit (NICU) was chosen. A system was engineered to gather raw data, analyse that data using different analysis techniques, uncover information, incorporate that information into the system and curate the evolution of the discovered knowledge. The application domain was chosen for three reasons: firstly because it is complex and no comprehensive solution exists; secondly, it requires tight interaction with domain experts, thus requiring the handling of subjective knowledge and inference; and thirdly, given the dearth of neurophysiologists, there is a real world need to provide a solution for this domain