47 resultados para Polymers - Industrial applications

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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The potential to use Ionic Liquids (ILs) as novel solvents or fluids for a diverse range of applications has become increasingly rent as researchers in academia and try respond to challenges from atmospheric emissions and disposal of many common solvents by evaluating novel reaction media. The intrinsic non-volatile nature of ILs provides an opportunity to reduce, or even completely eliminate, hazardous and toxic emissions to the atmosphere, thus providing the promise for significant environmental benefits. In synthesis and catalysis, ILs have been used as solvents (or solvents and catalysts), with the greatest current effort on using the ILs as alternatives to VOCs. In contrast, electrochemical studies hove utills'ed the fact that ILs are liquid rather than solids to provide liquid electrolytes without needing to odd an additional solvent. is overview appraiso an appraisal of potential to use ILs in industrial applications, illustrating some areas where practical uses are being developed, and how, throuqh understanding ionic liquids in a conceptuo level, new opportunities ore continuing to evolve.

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Architecture Description Languages (ADLs) have emerged in recent years as a tool for providing high-level descriptions of software systems in terms of their architectural elements and the relationships among them. Most of the current ADLs exhibit limitations which prevent their widespread use in industrial applications. In this paper, we discuss these limitations and introduce ALI, an ADL that has been developed to address such limitations. The ALI language provides a rich and flexible syntax for describing component interfaces, architectural patterns, and meta-information. Multiple graphical architectural views can then be derived from ALI's textual notation.

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Pulsed beams of energetic x-rays and neutrons from intense laser interactions with solid foils are promising for applications where bright, small emission area sources, capable of multi-modal delivery are ideal. Possible end users of laser-driven multi-modal sources are those requiring advanced non-destructive inspection techniques in industry sectors of high value commerce such as aerospace, nuclear and advanced manufacturing. We report on experimental work that demonstrates multi-modal operation of high power laser-solid interactions for neutron and x-ray beam generation. Measurements and Monte Carlo radiation transport simulations show that neutron yield is increased by a factor ∼2 when a 1 mm copper foil is placed behind a 2 mm lithium foil, compared to using a 2 cm block of lithium only. We explore x-ray generation with a 10 picosecond drive pulse in order to tailor the spectral content for radiography with medium density alloy metals. The impact of using >1 ps pulse duration on laser-accelerated electron beam generation and transport is discussed alongside the optimisation of subsequent bremsstrahlung emission in thin, high atomic number target foils. X-ray spectra are deconvolved from spectrometer measurements and simulation data generated using the GEANT4 Monte Carlo code. We also demonstrate the unique capability of laser-driven x-rays in being able to deliver single pulse high spatial resolution projection imaging of thick metallic objects. Active detector radiographic imaging of industrially relevant sample objects with a 10 ps drive pulse is presented for the first time, demonstrating that features of 200 μm size are resolved when projected at high magnification.

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Gas temperature is of major importance in plasma based surface treatment, since the surface processes are strongly temperature sensitive. The spatial distribution of reactive species responsible for surface modification is also influenced by the gas temperature. Industrial applications of RF plasma reactors require a high degree of homogeneity of the plasma in contact with the substrate. Reliable measurements of spatially resolved gas temperatures are, therefore, of great importance. The gas temperature can be obtained, e.g. by optical emission spectroscopy (OES). Common methods of OES to obtain gas temperatures from analysis of rotational distributions in excited states do not include the population dynamics influenced by cascading processes from higher electronic states. A model was developed to evaluate this effect on the apparent rotational temperature that is observed. Phase resolved OES confirmed the validity of this model. It was found that cascading leads to higher apparent temperatures, but the deviation (~25 K) is relatively small and can be ignored in most cases. This analysis is applied to investigate axially and radially resolved temperature profiles in an inductively coupled hydrogen RF discharge.

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Gas temperature is of major importance in plasma based surface treatment, since the surface processes are strongly temperature sensitive. The spatial distribution of reactive species responsible for surface modification is also influenced by the gas temperature. Industrial applications of RF plasma reactors require a high degree of homogeneity of the plasma in contact with the substrate. Reliable measurements of spatially resolved gas temperatures are, therefore, of great importance. The gas temperature can be obtained, e.g. by optical emission spectroscopy (OES). Common methods of OES to obtain gas temperatures from analysis of rotational distributions in excited states do not include the population dynamics influenced by cascading processes from higher electronic states. A model was developed to evaluate this effect on the apparent rotational temperature that is observed. Phase resolved OES confirmed the validity of this model. It was found that cascading leads to higher apparent temperatures, but the deviation (similar or equal to 25 K) is relatively small and can be ignored in most cases. This analysis is applied to investigate axially and radially resolved temperature profiles in an inductively coupled hydrogen RF discharge.

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The ionic nature of ionic liquids (ILs) results in a unique combination of intrinsic properties that produces increasing interest in the research of these fluids as environmentally friendly "neoteric" solvents. One of the main research fields is their exploitation as solvents for liquid-liquid extractions, but although ILs cannot vaporize leading to air pollution, they present non-negligible miscibility with water that may be the cause of some environmental aquatic risks. It is thus important to know the mutual solubilities between ILs and water before their industrial applications. In this work, the mutual solubilities of hydrophobic yet hygroscopic imidazolium-, pyridinium-, pyrrolidinium-, and piperidinium-based ILs in combination with the anions bis(trifluoromethylsulfonyl)imide, hexafluorophosphate, and tricyanomethane with water were measured between 288.15 and 318.15 K. The effect of the ILs structural combinations, as well as the influence of several factors, namely cation side alkyl chain length, the number of cation substitutions, the cation family, and the anion identity in these mutual solubilities are analyzed and discussed. The hydrophobicity of the anions increases in the order [C(CN)3] <[PF6] <[Tf2N] while the hydrophobicity of the cations increases from [Cnmim] <[Cnmpy] [Cnmpyr] <[Cnmpip] and with the alkyl chain length increase. From experimental measurements of the temperature dependence of ionic liquid solubilities in water, the thermodynamic molar functions of solution, such as Gibbs energy, enthalpy, and entropy at infinite dilution were determined, showing that the solubility of these ILs in water is entropically driven and that the anion solvation at the IL-rich phase controls their solubilities in water. The COSMO-RS, a predictive method based on unimolecular quantum chemistry calculations, was also evaluated for the description of the water-IL binary systems studied, where it showed to be capable of providing an acceptable qualitative agreement with the experimental data.

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Ionic liquids (ILs) have recently garnered increased attention because of their potential environmental benefits as "green" replacements over conventional volatile organic solvents. While ILs cannot significantly volatilize and contribute to air pollution, even the most hydrophobic ones present some miscibility with water posing environmental risks to the aquatic ecosystems. Thus, the knowledge of ILs toxicity and their water solubility must be assessed before an accurate judgment of their environmental benefits and prior to their industrial applications. In this work, the mutual solubilities for [C2-C8mim][Tf2N] (n-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide) and water between 288.15 and 318.15 K at atmospheric pressure were measured. Although these are among the most hydrophobic ionic liquids known, the solubility of water in these compounds is surprisingly large, ranging from 0.17 to 0.36 in mole fraction, while the solubility of these ILs in water is much lower ranging from 3.2 × 10-5 to 1.1 × 10-3 in mole fraction, in the temperature and pressure conditions studied. From the experimental data, the molar thermodynamic functions of solution and solvation such as Gibbs energy, enthalpy, and entropy at infinite dilution were estimated, showing that the solubility of these ILs in water is entropically driven. The predictive capability of COSMO-RS, a model based on unimolecular quantum chemistry calculations, was evaluated for the description of the binary systems investigated providing an acceptable agreement between the model predictions and the experimental data both with the temperature dependence and with the ILs structural variations.

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The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

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This paper provides an overview of the current field in wireless networks for monitoring and control. Alternative wireless technologies are introduced, together with current typical industrial applications. The focus then shifts to wireless Ethernet and the specialised requirements for wireless networked control systems (WNCS) are discussed. This is followed by a brief look at some current WNCS research, including reduced communication control.