110 resultados para Solvent extraction.


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Selectivity of the particular solvent to separate a mixture is essential for the optimal design of a separation process. Supercritical carbon dioxide (SCCO2) is widely used as a solvent in the extraction, purification and separation of specialty chemicals. The effect of the temperature and pressure on selectivity is complicated and varies from system to system. The effect of temperature and pressure on selectivity of SCCO2 for different solid mixtures available in literature was analyzed. In this work, we have developed two model equations to correlate the selectivity in terms of temperature and pressure. The model equations have correlated the selectivity of SCCO2 satisfactorily for 18 solid mixtures with an average absolute relative deviation (AARD) of around 5%. (C) 2012 Elsevier B.V. All rights reserved.

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The fluorescence quenching studies of carboxamide namely (E)-N-(3-Chlorophenyl)-2-(3,4,5-trimethoxybenzylideneamino)-4,5,6,7 tetrahydrobenzob]thiophene-3-carboxamide ENCTTTC] by aniline and carbon tetrachloride in six different solvents namely toluene, cyclohexane, n-hexane, n-heptane, n-decane and n-pentane have been carried out at room temperature with a view to understand the quenching mechanisms. The Stern-Volmer (S-V) plots have been found to be nonlinear with a positive deviation for all the solvents studied. In order to interpret these results we have invoked the ground state complex formation and sphere of action static quenching models. Using these models various quenching rate parameters have been determined. The magnitudes of these parameters suggest that sphere of action static quenching model agrees well with the experimental results. Hence the positive deviation is attributed to the static and dynamic quenching. Further, with the use of Finite Sink approximation model, it was possible to check these bimolecular reactions as diffusion-limited and to estimate independently distance parameter R' and mutual diffusion coefficient D. Finally an effort has been made to correlate the values of R' and D with the values of the encounter distance R and the mutual coefficient D determined using the Edward's empirical relation and Stokes Einstein relation. (C) 2011 Elsevier B.V. All rights reserved.

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We present an analytical field-effect method to extract the density of subgap states (subgap DOS) in amorphous semiconductor thin-film transistors (TFTs), using a closed-form relationship between surface potential and gate voltage. By accounting the interface states in the subthreshold characteristics, the subgap DOS is retrieved, leading to a reasonably accurate description of field-effect mobility and its gate voltage dependence. The method proposed here is very useful not only in extracting device performance but also in physically based compact TFT modeling for circuit simulation.

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We describe a hybrid synthetic protocol, the solvated metal atom dispersion (SMAD) method, for the synthesis and stabilization of monodisperse amorphous cobalt nanoparticles. By employing an optimized ratio of a weakly coordinating solvent and a capping agent monodisperse colloidal cobalt nanoparticles (2 +/- 0.5 nm) have been prepared by the SMAD method. However, the as-prepared samples were found to be oxidatively unstable which was elucidated by their magnetic studies. Oxidative stability in our case was achieved via a pyrolysis process that led to the decomposition of the organic solvent and the capping agent resulting in the formation of carbon encapsulated cobalt nanoparticles which was confirmed by Raman spectroscopy. Controlled annealing at different temperatures led to the phase transformation of metallic cobalt from the hcp to fcc phase. The magnetic behaviour varies with the phase and the particle size; especially, the coercivity of nanoparticles exhibited strong dependence on the phase transformation of cobalt. The high saturation magnetization close to that of the bulk value was achieved in the case of the annealed samples. In addition to detailed structural and morphological characterization, the results of thermal and magnetic studies are also presented.

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Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

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We analyze the spectral zero-crossing rate (SZCR) properties of transient signals and show that SZCR contains accurate localization information about the transient. For a train of pulses containing transient events, the SZCR computed on a sliding window basis is useful in locating the impulse locations accurately. We present the properties of SZCR on standard stylized signal models and then show how it may be used to estimate the epochs in speech signals. We also present comparisons with some state-of-the-art techniques that are based on the group-delay function. Experiments on real speech show that the proposed SZCR technique is better than other group-delay-based epoch detectors. In the presence of noise, a comparison with the zero-frequency filtering technique (ZFF) and Dynamic programming projected Phase-Slope Algorithm (DYPSA) showed that performance of the SZCR technique is better than DYPSA and inferior to that of ZFF. For highpass-filtered speech, where ZFF performance suffers drastically, the identification rates of SZCR are better than those of DYPSA.

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The effect of molecular shape and position of hydrogen bonding functionality in the solid state structural self-assembly was investigated using diaminotriazine substituted diphenyl ether based positional isomers (1-5). The molecular shape was modulated by changing diaminotriazine position that produced channel supramolecular structures in 1, 3 and 5. There exists a direct correlation between the molecular shape and three dimensional structures; more linear molecules resulted in close-packing whereas molecules with a labyrinthine topology formed a channel structure. Supramolecular aspects pertaining to the influence of solvent of crystallization in structure formation and reversible structural transformation in solid state were also explored. 1-5 exhibited tunable solid state fluorescence (lambda(max) = 437-496 nm) depending on the diaminotriazine substitutional position and 3 showed solvent-dependent solid state fluorescence. The present study describes the generation of a supramolecular channel structure with functional properties such as tunable fluorescence by varying the position of hydrogen bond functionality and solvent of crystallization.

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Identifying symmetry in scalar fields is a recent area of research in scientific visualization and computer graphics communities. Symmetry detection techniques based on abstract representations of the scalar field use only limited geometric information in their analysis. Hence they may not be suited for applications that study the geometric properties of the regions in the domain. On the other hand, methods that accumulate local evidence of symmetry through a voting procedure have been successfully used for detecting geometric symmetry in shapes. We extend such a technique to scalar fields and use it to detect geometrically symmetric regions in synthetic as well as real-world datasets. Identifying symmetry in the scalar field can significantly improve visualization and interactive exploration of the data. We demonstrate different applications of the symmetry detection method to scientific visualization: query-based exploration of scalar fields, linked selection in symmetric regions for interactive visualization, and classification of geometrically symmetric regions and its application to anomaly detection.

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Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

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Two heterometallic coordination polymers (CPs) have been prepared using (NiL)-L-II](2)Co-II (where H2L = N,N'-bis(salicylidene)-1,3-propanediamine) as nodes and dicyanamido spacers by varying the solvent for synthesis. Structural characterizations revealed that methanol assisted the formation of a two-dimensional (4,4) connected rhombic grid network of (NiL)(2)Co(NCNCN)2](infinity) (1a) whereas relatively less polar acetonitrile afforded a different superstructure {(NiL)(2)Co(NCNCN)(2)]center dot CH3CN}(infinity) (1b) with a two-dimensional (4,4) connected square grid network. The presence of acetonitrile molecules in the structure of 1b seems to change the spatial orientation of the terminal metalloligands NiL] from pseudo-eclipsed in 1a to staggered-like in 1b around the central Co(II). These structural changes in the nodes together with the conformationally flexible dicyanamido spacers, which are cis coordinated to the Co(II) in both trinuclear units, led to the differences in the final 2D network. Variable-temperature magnetic susceptibility measurements revealed that this supramolecular isomerism led to a drastic transition from spin-frustrated antiferromagnetism for 1a to a dominant ferromagnetic behaviour for 1b. The geometrical differences in Ni2Co coordination clusters (CCs) which are scalene triangular in 1a but nearly linear in 1b, are held responsible for the changes of the magnetic properties. The DFT calculations of exchange interactions between metal centres provide a clear evidence of the role played by the fundamental geometrical factors on the nature and magnitude of the magnetic coupling in these pseudo-polymorphic CPs.

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This paper presents classification, representation and extraction of deformation features in sheet-metal parts. The thickness is constant for these shape features and hence these are also referred to as constant thickness features. The deformation feature is represented as a set of faces with a characteristic arrangement among the faces. Deformation of the base-sheet or forming of material creates Bends and Walls with respect to a base-sheet or a reference plane. These are referred to as Basic Deformation Features (BDFs). Compound deformation features having two or more BDFs are defined as characteristic combinations of Bends and Walls and represented as a graph called Basic Deformation Features Graph (BDFG). The graph, therefore, represents a compound deformation feature uniquely. The characteristic arrangement of the faces and type of bends belonging to the feature decide the type and nature of the deformation feature. Algorithms have been developed to extract and identify deformation features from a CAD model of sheet-metal parts. The proposed algorithm does not require folding and unfolding of the part as intermediate steps to recognize deformation features. Representations of typical features are illustrated and results of extracting these deformation features from typical sheet metal parts are presented and discussed. (C) 2013 Elsevier Ltd. All rights reserved.

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Porous activated-carbons with a large surface-area have been the most common materials for electrical-double-layer capacitors (EDLCs). These carbons having a wide pore distribution ranges from micropores to macropores in conjunction with a random pore connection that facilitates the high specific-capacitance values. Pore distribution plays a central role in controlling the capacitance value of EDLCs, since electrolyte distribution inside the active material mainly depends on the pore distribution. This has a direct influence on the distribution of resistance and capacitance values within the electrode. As a result, preparation of electrodes remains a vital issue in realising high-performance EDLCs. Generally, carbon materials along with some binders are dispersed into a solvent and coated onto the current collectors. This study examines the role of binder solvents used for the carbon-ink preparation on the microstructure of the electrodes and the consequent performance of the EDLCs. It is observed that the physical properties of the binder solvent namely its dielectric constant, viscosity and boiling point have important role in determining the pore-size distribution as well as the microstructure of electrodes which influence their specific capacitance values.

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Epoch is defined as the instant of significant excitation within a pitch period of voiced speech. Epoch extraction continues to attract the interest of researchers because of its significance in speech analysis. Existing high performance epoch extraction algorithms require either dynamic programming techniques or a priori information of the average pitch period. An algorithm without such requirements is proposed based on integrated linear prediction residual (ILPR) which resembles the voice source signal. Half wave rectified and negated ILPR (or Hilbert transform of ILPR) is used as the pre-processed signal. A new non-linear temporal measure named the plosion index (PI) has been proposed for detecting `transients' in speech signal. An extension of PI, called the dynamic plosion index (DPI) is applied on pre-processed signal to estimate the epochs. The proposed DPI algorithm is validated using six large databases which provide simultaneous EGG recordings. Creaky and singing voice samples are also analyzed. The algorithm has been tested for its robustness in the presence of additive white and babble noise and on simulated telephone quality speech. The performance of the DPI algorithm is found to be comparable or better than five state-of-the-art techniques for the experiments considered.

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We carry out a series of long atomistic molecular dynamics simulations to study the unfolding of a small protein, chicken villin headpiece (HP-36), in water-ethanol (EtOH) binary mixture. The prime objective of this work is to explore the sensitivity of protein unfolding dynamics toward increasing concentration of the cosolvent and unravel essential features of intermediates formed in search of a dynamical pathway toward unfolding. In water ethanol binary mixtures, HP-36 is found to unfold partially, under ambient conditions, that otherwise requires temperature as high as similar to 600 K to denature in pure aqueous solvent. However, an interesting course of pathway is observed to be followed in the process, guided by the formation of unique intermediates. The first step of unfolding is essentially the separation of the cluster formed by three hydrophobic (phenylalanine) residues, namely, Phe-7, Phe-11, and Phe-18, which constitute the hydrophobic core, thereby initiating melting of helix-2 of the protein. The initial steps are similar to temperature-induced unfolding as well as chemical unfolding using DMSO as cosolvent. Subsequent unfolding steps follow a unique path. As water-ethanol shows composition-dependent anomalies, so do the details of unfolding dynamics. With an increase in cosolvent concentration, different partially unfolded intermediates are found to be formed. This is reflected in a remarkable nonmonotonic composition dependence of several order parameters, including fraction of native contacts and protein-solvent interaction energy. The emergence of such partially unfolded states can be attributed to the preferential solvation of the hydrophobic residues by the ethyl groups of ethanol. We further quantify the local dynamics of unfolding by using a Marcus-type theory.

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Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS. The results show that correlation between actual and estimated proportion is higher by an average of 0.25 for the artificial datasets compared to a situation where variability is not considered. With IKONOS, Landsat ETM+ and MODIS data, the average correlation increased by 0.15 for 2 and 3 classes and by 0.19 for 4 classes, when compared to single endmember per class. (C) 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.