919 resultados para mixtures


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Mixture experiments are typical for chemical, food, metallurgical and other industries. The aim of these experiments is to find optimal component proportions that provide desired values of some product performance characteristics.

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Pavement analysis and design for fatigue cracking involves a number of practical problems like material assessment/screening and performance prediction. A mechanics-aided method can answer these questions with satisfactory accuracy in a convenient way when it is appropriately implemented. This paper presents two techniques to implement the pseudo J-integral based Paris’ law to evaluate and predict fatigue cracking in asphalt mixtures and pavements. The first technique, quasi-elastic simulation, provides a rational and appropriate reference modulus for the pseudo analysis (i.e., viscoelastic to elastic conversion) by making use of the widely used material property: dynamic modulus. The physical significance of the quasi-elastic simulation is clarified. Introduction of this technique facilitates the implementation of the fracture mechanics models as well as continuum damage mechanics models to characterize fatigue cracking in asphalt pavements. The second technique about modeling fracture coefficients of the pseudo J-integral based Paris’ law simplifies the prediction of fatigue cracking without performing fatigue tests. The developed prediction models for the fracture coefficients rely on readily available mixture design properties that directly affect the fatigue performance, including the relaxation modulus, air void content, asphalt binder content, and aggregate gradation. Sufficient data are collected to develop such prediction models and the R2 values are around 0.9. The presented case studies serve as examples to illustrate how the pseudo J-integral based Paris’ law predicts fatigue resistance of asphalt mixtures and assesses fatigue performance of asphalt pavements. Future applications include the estimation of fatigue life of asphalt mixtures/pavements through a distinct criterion that defines fatigue failure by its physical significance.

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A lot of mixed vitrified waste exists at DOE sites, which contain valuable metal having great potential for being reused in industry. Of these useful metals, steel constitutes more than 45% of the volume. Using the differential centrifugal separation technology, steel is separated by using remote melting of the mixed waste. The high costs involved are directly proportional to the time involved in separation of the steel from the mixed waste. This is determined by using similitude principles. Having obtained a solidified steel ingot by melting, it is essential to determine the decontaminated portions of the ingot that can be released to industry. Two parameters representing measures of separation are proposed—the Centrifugal Fluid Separation Number and the Thermal Separation Number. Regression correlations are determined to express the estimated time of separation. Experimental analysis of solidified ingots has shown that when the Thermal Separation Number is less than 1700 the steel contains little or no trace of glass. This result can be used to recycle steel back to industry. ^

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This dissertation utilized electrospray ion mobility mass spectrometry (ESI-IMS-MS) to develop methods necessary for the separation of chiral compounds of forensic interest. The compounds separated included ephedrines and pseudoephedrines, that occur as impurities in confiscated amphetamine type substances (ATS) in an effort to determine the origin of these substances. The ESI-IMS-MS technique proved to be faster and more cost effective than traditional chromatographic methods currently used to conduct chiral separations such as gas and liquid chromatography. Both mass spectrometric and computational analysis revealed the separation mechanism of these chiral interactions allowing for further development to separate other chiral compounds by IMS. Successful separation of chiral compounds was achieved utilizing a variety of modifiers injected into the IMS drift tube. It was found that the modifiers themselves did not need to be chiral in nature and that achiral modifiers were sufficient in performing the required separations. The ESI-IMS-MS technique was also used to detect thermally labile compounds which are commonly found in explosive substances. The methods developed provided mass spectrometric identification of the type of ionic species being detected from explosive analytes as well as the appropriate solvent that enhances detection of these analytes in either the negative or positive ion mode. An application of the developed technique was applied to the analysis of a variety of low explosive smokeless powder samples. It was found that the developed ESI-IMS-MS technique not only detected the components of the smokeless powders, but also provided data that allowed the classification of the analyzed smokeless powders by manufacturer or make. ^

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In the present work, the deviations in the solubility of CO2, CH4, and N2 at 30 °c in the mixed gases (CO2/CH4) and (CO2/N2) from the pure gas behavior were studied using the dual-mode model over a wide range of equilibrium composition and pressure values in two glassy polymers. The first of which was PI-DAR which is the polyimide formed by the reaction between 4, 6-diaminoresorcinol dihydrochloride (DAR-Cl) and 2, 2’-bis-(3, 4-dicarboxyphenyl) hexafluoropropane dianhydride (6FDA). The other glassy polymer was TR-DAR which is the corresponding thermally rearranged polymer of PI-DAR. Also, mixed gas sorption experiments for the gas mixture (CO2/CH4) in TR-DAR at 30°c took place in order to assess the degree of accuracy of the dual-mode model in predicting the true mixed gas behavior. The experiments were conducted on a pressure decay apparatus coupled with a gas chromatography column. On the other hand, the solubility of CO2 and CH4 in two rubbery polymers at 30⁰c in the mixed gas (CO2/CH4) was modelled using the Lacombe and Sanchez equation of state at various values of equilibrium composition and pressure. These two rubbery polymers were cross-linked poly (ethylene oxide) (XLPEO) and poly (dimethylsiloxane) (PDMS). Moreover, data about the sorption of CO2 and CH4 in liquid methyl dietahnolamine MDEA that was collected from literature65-67 was used to determine the deviations in the sorption behavior in the mixed gas from that in the pure gases. It was observed that the competition effects between the penetrants were prevailing in the glassy polymers while swelling effects were predominant in the rubbery polymers above a certain value of the fugacity of CO2. Also, it was found that the dual-mode model showed a good prediction of the sorption of CH4 in the mixed gas for small pressure values but in general, it failed to predict the actual sorption of the penetrants in the mixed gas.

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Bayesian methods offer a flexible and convenient probabilistic learning framework to extract interpretable knowledge from complex and structured data. Such methods can characterize dependencies among multiple levels of hidden variables and share statistical strength across heterogeneous sources. In the first part of this dissertation, we develop two dependent variational inference methods for full posterior approximation in non-conjugate Bayesian models through hierarchical mixture- and copula-based variational proposals, respectively. The proposed methods move beyond the widely used factorized approximation to the posterior and provide generic applicability to a broad class of probabilistic models with minimal model-specific derivations. In the second part of this dissertation, we design probabilistic graphical models to accommodate multimodal data, describe dynamical behaviors and account for task heterogeneity. In particular, the sparse latent factor model is able to reveal common low-dimensional structures from high-dimensional data. We demonstrate the effectiveness of the proposed statistical learning methods on both synthetic and real-world data.

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Mixtures of Zellner's g-priors have been studied extensively in linear models and have been shown to have numerous desirable properties for Bayesian variable selection and model averaging. Several extensions of g-priors to Generalized Linear Models (GLMs) have been proposed in the literature; however, the choice of prior distribution of g and resulting properties for inference have received considerably less attention. In this paper, we extend mixtures of g-priors to GLMs by assigning the truncated Compound Confluent Hypergeometric (tCCH) distribution to 1/(1+g) and illustrate how this prior distribution encompasses several special cases of mixtures of g-priors in the literature, such as the Hyper-g, truncated Gamma, Beta-prime, and the Robust prior. Under an integrated Laplace approximation to the likelihood, the posterior distribution of 1/(1+g) is in turn a tCCH distribution, and approximate marginal likelihoods are thus available analytically. We discuss the local geometric properties of the g-prior in GLMs and show that specific choices of the hyper-parameters satisfy the various desiderata for model selection proposed by Bayarri et al, such as asymptotic model selection consistency, information consistency, intrinsic consistency, and measurement invariance. We also illustrate inference using these priors and contrast them to others in the literature via simulation and real examples.

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This thesis deals with the evaporation of non-ideal liquid mixtures using a multicomponent mass transfer approach. It develops the concept of evaporation maps as a convenient way of representing the dynamic composition changes of ternary mixtures during an evaporation process. Evaporation maps represent the residual composition of evaporating ternary non-ideal mixtures over the full range of composition, and are analogous to the commonly-used residue curve maps of simple distillation processes. The evaporation process initially considered in this work involves gas-phase limited evaporation from a liquid or wetted-solid surface, over which a gas flows at known conditions. Evaporation may occur into a pure inert gas, or into one pre-loaded with a known fraction of one of the ternary components. To explore multicomponent masstransfer effects, a model is developed that uses an exact solution to the Maxwell-Stefan equations for mass transfer in the gas film, with a lumped approach applied to the liquid phase. Solutions to the evaporation model take the form of trajectories in temperaturecomposition space, which are then projected onto a ternary diagram to form the map. Novel algorithms are developed for computation of pseudo-azeotropes in the evaporating mixture, and for calculation of the multicomponent wet-bulb temperature at a given liquid composition. A numerical continuation method is used to track the bifurcations which occur in the evaporation maps, where the composition of one component of the pre-loaded gas is the bifurcation parameter. The bifurcation diagrams can in principle be used to determine the required gas composition to produce a specific terminal composition in the liquid. A simple homotopy method is developed to track the locations of the various possible pseudo-azeotropes in the mixture. The stability of pseudo-azeotropes in the gas-phase limited case is examined using a linearized analysis of the governing equations. Algorithms for the calculation of separation boundaries in the evaporation maps are developed using an optimization-based method, as well as a method employing eigenvectors derived from the linearized analysis. The flexure of the wet-bulb temperature surface is explored, and it is shown how evaporation trajectories cross ridges and valleys, so that ridges and valleys of the surface do not coincide with separation boundaries. Finally, the assumption of gas-phase limited mass transfer is relaxed, by employing a model that includes diffusion in the liquid phase. A finite-volume method is used to solve the system of partial differential equations that results. The evaporation trajectories for the distributed model reduce to those of the lumped (gas-phase limited) model as the diffusivity in the liquid increases; under the same gas-phase conditions the permissible terminal compositions of the distributed and lumped models are the same.

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A modified UNIFAC–VISCO group contribution method was developed for the correlation and prediction of viscosity of ionic liquids as a function of temperature at 0.1 MPa. In this original approach, cations and anions were regarded as peculiar molecular groups. The significance of this approach comes from the ability to calculate the viscosity of mixtures of ionic liquids as well as pure ionic liquids. Binary interaction parameters for selected cations and anions were determined by fitting the experimental viscosity data available in literature for selected ionic liquids. The temperature dependence on the viscosity of the cations and anions were fitted to a Vogel–Fulcher–Tamman behavior. Binary interaction parameters and VFT type fitting parameters were then used to determine the viscosity of pure and mixtures of ionic liquids with different combinations of cations and anions to ensure the validity of the prediction method. Consequently, the viscosities of binary ionic liquid mixtures were then calculated by using this prediction method. In this work, the viscosity data of pure ionic liquids and of binary mixtures of ionic liquids are successfully calculated from 293.15 K to 363.15 K at 0.1 MPa. All calculated viscosity data showed excellent agreement with experimental data with a relative absolute average deviation lower than 1.7%.

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Abstract The development of high voltage electrolytes is one of the key aspects for increasing both energy and power density of electrochemical double layer capacitors (EDLCs). The usage of blends of ionic liquids and organic solvents has been considered as a feasible strategy since these electrolytes combine high usable voltages and good transport properties at the same time. In this work, the ionic liquid 1-butyl-1-methylpyrrolidinium bis{(trifluoromethyl)sulfonyl}imide ([Pyrr14][TFSI]) was mixed with two nitrile-based organic solvents, namely butyronitrile and adiponitrile, and the resulting blends were investigated regarding their usage in electrochemical double layer capacitors. Both blends have a high electrochemical stability, which was confirmed by prolonged float tests at 3.2 V, as well as, good transport properties. In fact, the butyronitrile blend reaches a conductivity of 17.14 mS·cm−1 and a viscosity of 2.46 mPa·s at 20 °C, which is better than the state-of-the-art electrolyte (1 mol·dm−3 of tetraethylammonium tetrafluoroborate in propylene carbonate).

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Electrochemical double layer capacitors (EDLCs), also known as supercapacitors, are promising energy storage devices, especially when considering high power applications [1]. EDLCs can be charged and discharged within seconds [1], feature high power (10 kW·kg-1) and an excellent cycle life (>500,000 cycles). All these properties are a result of the energy storage process of EDLCs, which relies on storing energy by charge separation instead of chemical redox reactions, as utilized in battery systems. Upon charging, double layers are forming at the electrode/electrolyte interface consisting of the electrolyte’s ions and electric charges at the electrode surface.In state-of-the-art EDLC systems activated carbons (AC) are used as active materials and tetraethylammonium tetrafluoroborate ([Et4N][BF4]) dissolved in organic solvents like propylene carbonate (PC) or acetonitrile (ACN) are commonly used as the electrolyte [2]. These combinations of materials allow operative voltages up to 2.7 V - 2.8 V and an energy in the order of 5 Wh·kg-1[3]. The energy of EDLCs is dependent on the square of the operative voltage, thus increasing the usable operative voltage has a strong effect on the delivered energy of the device [1]. Due to their high electrochemical stability, ionic liquids (ILs) were thoroughly investigated as electrolytes for EDLCs, as well as, batteries, enabling high operating voltages as high as 3.2 V - 3.5 V for the former [2]. While their unique ionic structure allows the usage of neat ILs as electrolyte in EDLCs, ILs suffer from low conductivity and high viscosity increasing the intrinsic resistance and, as a result, a lower power output of the device. In order to overcome this issue, the usage of blends of ionic liquids and organic solvents has been considered a feasible strategy as they combine high usable voltages, while still retaining good transport properties at the same time.In our recent work the ionic liquid 1-butyl-1-methylpyrrolidinium bis{(trifluoromethyl)sulfonyl}imide ([Pyrr14][TFSI]) was combined with two nitrile-based organic solvents, namely butyronitrile (BTN) and adiponitrile (ADN), and the resulting blends were investing regarding their usage in electrochemical double layer capacitors [4,5]. Firstly, the physicochemical properties were investigated, showing good transport properties for both blends, which are similar to the state-of-the-art combination of [Et4N][BF4] in PC. Secondly, the electrochemical properties for EDLC application were studied in depth revealing a high electrochemical stability with a maximum operative voltage as high as 3.7 V. In full cells these high voltage organic solvent based electrolytes have a good performance in terms of capacitance and an acceptable equivalent series resistance at cut-off voltages of 3.2 and 3.5 V. However, long term stability tests by float testing revealed stability issues when using a maximum voltage of 3.5 V for prolonged time, whereas at 3.2 V no such issues are observed (Fig. 1).Considering the obtained results, the usage of ADN and BTN blends with [Pyrr14][TFSI] in EDLCs appears to be an interesting alternative to state-of-the-art organic solvent based electrolytes, allowing the usage of higher maximum operative voltages while having similar transport properties to 1 mol∙dm-3 [Et4N][BF4] in PC at the same time.

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Carbon dioxide solubility in a set of carboxylate ionic liquids formulated with stoicheiometric amounts of water is found to be significantly higher than for other ionic liquids previously reported. This is due to synergistic chemical and physical absorption. The formulated ionic liquid/water mixtures show greatly enhanced carbon dioxide solubility relative to both anhydrous ionic liquids and aqueous ionic liquid solutions, and are competitive with commercial chemical absorbers, such as activated N-methyldiethanolamine or monoethanolamine.

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Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Dissertation, 2016

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[EN]All the relevant risk factors contributing to breast cancer etiology are not fully known. Exposure to organochlorine pesticides has been linked to an increased incidence of the disease, although not all data have been consistent. Most published studies evaluated the exposure to organochlorines individually, ignoring the potential effects exerted by the mixtures of chemicals.