251 resultados para decomposition techniques


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A method for the explicit determination of the polar decomposition (and the related problem of finding tensor square roots) when the underlying vector space dimension n is arbitrary (but finite), is proposed. The method uses the spectral resolution, and avoids the determination of eigenvectors when the tensor is invertible. For any given dimension n, an appropriately constructed van der Monde matrix is shown to play a key role in the construction of each of the component matrices (and their inverses) in the polar decomposition.

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The catalytic oxidation and decomposition of NH3 have been carried out over combustion synthesized Al2O3 and CeO2 supported Pt, Pd and Ag catalysts using temperature programmed reaction (TPR) technique in a packed bed tubular reactor. Metals are ionically dispersed over CeO2 and fine metal particles are found on Al2O3. NH3 oxidation occurs over 1% Pt/Al2O3, 1% Pd/Al2O3 and 1% Ag/Al2O3 at 175, 270 and 350 C respectively producing N-2, NO, N2O and H2O, whereas 1% Pt/CeO2, 1% Pd/CeO2 and 1% Ag/CeO2 give N-2 along with NO, N2O and H2O at 200, 225 and 250degreesC respectively. N-2 predominates over other nitrogen-containing products during the reaction on all catalysts. At less O-2 concentration, N-2 and H2O are the only products obtained during NH3 Oxidation. NH3 decomposition over all the catalysts occurs above 450degreesC.

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The structure and chemical environment of Cu in Cu/CeO2 catalysts synthesized by the solution combustion method have been investigated by X-ray diffraction (XRD), transmission electron microscopy (TEM), electron paramagnetic resonance (EPR) spectroscopy, X-ray photoelectron spectroscopy (XPS), cyclic voltammetry (CV), and extended X-ray fine structure (EXAFS) spectroscopy. High-resolution XRD studies of 3 and 5 atom % Cu/CeO2 do not show CuO lines in their respective patterns. The structure could be refined for the composition Ce1-xCuxO2-delta (x = 0.03 and 0.05; delta similar to 0.13 and 0.16) in the fluorite structure with 5-8% oxide ion vacancy. High-resolution TEM did not show CuO particles in 5 atom % Cu/CeO2. EPR as well as XPS studies confirm the presence of Cu2+ species in the CeO2 matrix. Redox potentials of Cu species in the CeO2 matrix are lower than those in CuO. EXAFS investigations of these catalysts show an average coordination number of 3 around the Cu2+ ion in the first shell at a distance of 1.96 Angstrom, indicating the O2- ion vacancy around the Cu2+ ion. The Cu-O bond length also decreases compared to that in CuO. The second and third shell around the Cu2+ ion in the catalysts are attributed to -Cu2+-O2--Cu2+ - at 2.92 Angstrom and -Cu2+-O2--Ce4+- at the distance of 3.15 Angstrom, respectively. The present results provide direct evidence for the formation of a Ce1-xCuxO2-delta type of solid solution phase having -square-Cu2+-O-Ce4+- kind of linkages.

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Visualization of fluids has wide applications in science, engineering and entertainment. Various methodologies Of visualizing fluids have evolved which emphasize on capturing different aspects of the fluids accurately. In this survey the existing methods for realistic visualization of fluids are reviewed. The approaches are classified based on the key concept they rely on for fluid modeling. This classification allows for easy selection of the method to be adopted for visualization given an application. It also enables identification of alternative techniques for fluid modeling.

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This is the first report on the analysis of random block polysulfide copolymers containing different amounts of repeating units in the copolymer backbone, which has been studied by direct pyrolysis mass spectrometry (DPMS) and by pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). The homopolymers such as poly(ethylene sulfide) (PES), poly(styrene sulfide) (PSS), and two random copolymers, viz., poly(ethylene sulfide(x)-co-styrene sulfide(y)) [copolymer I (x = y = 0.5) and copolymer II (x = 0.74, y = 0.26)] were investigated by both DPMS and Py-GC/MS (except copolymer II) techniques. In the case of copolymer I, the thermal degradation products of SE1, SE2, S-2, and S2E (S = styrene sulfide, E = ethylene sulfide) were detected in DPMS, whereas the formation of SE1 and SE2 were observed by Py-GC/MS technique. However, for copolymer II, SE3 was also found along with SE1, SE2, S-2, and S2E in DPMS. The formation of additional product (SE3) observed in copolymer II could be due to an increase in the block length formed during copolymerization. Further, a comparative study on thermal degradation of PES, poly(ethylene disulfide) (PEDS), and poly(ethylene tetrasulfide) (PETS) were investigated by Py-GC/MS. The pyrolysis products detected by both DPMS and Py-GC/MS indicates that the thermal decomposition of these polymers yield cyclic sulfides through an intramolecular exchange or by backbiting processes. The linear products with thiol and vinyl groups were also observed by Py-GC/MS along with the cyclic products via carbon hydrogen transfer reaction.

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The equilibrium decomposition temperatures of Cu2Ln2O5 (Ln = Tb, Dy, Ho, Er, Tm, Yb, and Lu) compounds have been measured using a combined DTA-TGA apparatus under a flowing Ar + O2 gas mixture, in which the partial pressure of oxygen was controlled at 5.0 × 103 Pa. The Cu2Ln2O5 compounds yield Ln2O3 and Cu2O on decomposition. The decomposition temperature increases monotonically with the atomic number of the lanthanide element. This suggests that the stability of the Cu2Ln2O5 compounds with respect to the component binary oxides increases with decreasing radius of the Ln3+ ion.

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Nickel orthosilicate (Ni2SiO4) has been found to decompose into its component binary oxides in oxygen potential gradients at 1373 K. Nickel oxide was formed at the high oxygen potential boundary, while silica was detected at the low oxygen potential side. Significant porosity and fissures were observed near the Ni2SiO4/SiO2 interface and the SiO2 layer. The critical oxygen partial pressure ratio required for decomposition varied from 1.63 to 2.15 as the oxygen pressures were altered from 1.01 ⊠ 105 to 2.7X 10−4 Pa, well above the dissociation pressure of Ni2SiO4. Platinum markers placed at the boundaries of the Ni2SiO4 sample indicated growth of NiO at the higher oxygen potential boundary, without any apparent transport of material to the low oxygen potential side. However, significant movement of the bulk Ni2SiO4 crystal with respect to the marker was not observed. The decomposition of the silicate occurs due to the unequal rates of transport of Ni and Si. The critical oxygen partial pressure ratio required for decomposition is related both to the thermodynamic stability of Ni2SiO4 with respect to component oxides and the ratio of diffusivities of nickel and silicon. Kinetic decomposition of multicomponent oxides, first discovered by Schmalzried, Laqua, and co-workers [H. Schmalzried, W. Laqua, and P. L. Lin, Z. Natur Forsch. Teil A 34, 192 (1979); H. Schmalzried and W. Laqua, Oxid. Met. 15, 339 (1981); W. Laqua and H. Schmalzried, Chemical Metallurgy—A Tribute to Carl Wagner (Metallurgical Society of the AIME, New York, 1981), p. 29] has important consequences for their use at high temperatures and in geochemistry.

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Nanostructured materials have attracted considerable interest in recent years due to their properties which differ strongly from their bulk phase and potential applications in nanoscale electronic and optoelectronic devices. Metal oxide nanostructures can be synthesized by variety of different synthesis techniques developed in recent years such as thermal decomposition, sol-gel technique, chemical coprecipitation, hydrothermal process, solvothermal process, spray pyrolysis, polyol process etc. All the above processes go through a tedious synthesis procedure followed by prolonged heat treatment at elevated temperature and are time consuming. In the present work we describe a rapid microwave irradiation-assisted chemical synthesis technique for the growth of nanoparticles, nanorods, and nanotubes of a variety of metal oxides in the presence of an appropriate surfactant, without the use of any templates The method is simple, inexpensive, and helps one to prepare nanostructures in a very simple way, and in a very short time, measured in minutes. The synthesis procedure employs high quality metalorganic complexes (typically -diketonates) featuring a direct metal-to-oxygen bond in its molecular structure. The complex is dissolved in a suitable solvent, often with a surfactant added, and the solution then subjected to microwave irradiation in a domestic microwave oven operating at 2.45 GHz frequency with power varying from 160-800 W, from a few seconds to a few minutes, leading to the formation of corresponding metal oxides. This method has been used successfully to synthesize nanostructures of a variety of binary and ternary metal oxides such as ZnO, CdO, Fe2O3, CuO, Ga2O3, Gd2O3, ZnFe2O4, etc. There is an observed variation in the morphology of the nanostructures with the change of different parameters such as microwave power, irradiation time, appropriate solvent, surfactant type and concentration. Cationic, anionic, nonionic and polymeric surfactants have been used to generate a variety of nanostructures. Even so, to remove the surfactant, there is either no need of heat treatment or a very brief exposure to heat suffices, to yield highly pure and crystalline oxide materials as prepared. By adducting the metal complexes, the shape of the nanostructures can be controlled further. In this manner, very well formed, single-crystalline, hexagonal nanorods and nanotubes of ZnO have been formed. Adducting the zinc complex leads to the formation of tapered ZnO nanorods with a very fine tip, suitable for electron emission applications. Particle size and their monodispersity can be controlled by a suitable choice of a precursor complex, the surfactant, and its concentration. The resulting metal oxide nanostructures have been characterized by X-ray diffraction, field emission scanning electron microscopy, transmission electron microscopy, FTIR spectroscopy, photoluminescence, and electron emission measurements.

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Carbon nanotubes produced by the treatment of Mg1−xMxAl2O4 (M = Fe, Co, or Ni; x = 0.1, 0.2, 0.3, or 0.4) spinels with an H2–CH4 mixture at 1070 °C have been investigated systematically. The grains of the oxide-metal composite particles are uniformly covered by a weblike network of carbon nanotube bundles, several tens of micrometers long, made up of single-wall nanotubes with a diameter close to 4 nm. Only the smallest metal particles (<5 nm) are involved in the formation of the nanotubes. A macroscopic characterization method involving surface area measurements and chemical analysis has been developed in order to compare the different nanotube specimens. An increase in the transition metal content of the catalyst yields more carbon nanotubes (up to a metal content of 10.0 wt% or x = 0.3), but causes a decrease in carbon quality. The best compromise is to use 6.7 wt% of metal (x = 0.2) in the catalyst. Co gives superior results with respect to both the quantity and quality of the nanotubes. In the case of Fe, the quality is notably hampered by the formation of Fe3C particles.

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This paper introduces a scheme for classification of online handwritten characters based on polynomial regression of the sampled points of the sub-strokes in a character. The segmentation is done based on the velocity profile of the written character and this requires a smoothening of the velocity profile. We propose a novel scheme for smoothening the velocity profile curve and identification of the critical points to segment the character. We also porpose another method for segmentation based on the human eye perception. We then extract two sets of features for recognition of handwritten characters. Each sub-stroke is a simple curve, a part of the character, and is represented by the distance measure of each point from the first point. This forms the first set of feature vector for each character. The second feature vector are the coeficients obtained from the B-splines fitted to the control knots obtained from the segmentation algorithm. The feature vector is fed to the SVM classifier and it indicates an efficiency of 68% using the polynomial regression technique and 74% using the spline fitting method.