292 resultados para transport-measurements


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We study the current produced in a Tomonaga-Luttinger liquid by an applied bias and by weak, pointlike impurity potentials which are oscillating in time. We use bosonization to perturbatively calculate the current up to second order in the impurity potentials. In the regime of small bias and low pumping frequency, both the dc and ac components of the current have power-law dependences on the bias and pumping frequencies with an exponent 2K-1 for spinless electrons, where K is the interaction parameter. For K < 1/2, the current grows large for special values of the bias. For noninteracting electrons with K=1, our results agree with those obtained using Floquet scattering theory for Dirac fermions. We also discuss the cases of extended impurities and of spin-1/2 electrons.

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A method for determining the electron/hole transport length scale of model semiconducting polymer systems by scanning a narrow-light probe beam over the nonoverlapping anode/cathode region in asymmetric sandwich device structures is presented (see figure). Electron versus hole collection efficacy, and disorder and spatial anisotropy in the electrical transport parameters can be estimated.

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Randomness in the source condition other than the heterogeneity in the system parameters can also be a major source of uncertainty in the concentration field. Hence, a more general form of the problem formulation is necessary to consider randomness in both source condition and system parameters. When the source varies with time, the unsteady problem, can be solved using the unit response function. In the case of random system parameters, the response function becomes a random function and depends on the randomness in the system parameters. In the present study, the source is modelled as a random discrete process with either a fixed interval or a random interval (the Poisson process). In this study, an attempt is made to assess the relative effects of various types of source uncertainties on the probabilistic behaviour of the concentration in a porous medium while the system parameters are also modelled as random fields. Analytical expressions of mean and covariance of concentration due to random discrete source are derived in terms of mean and covariance of unit response function. The probabilistic behaviour of the random response function is obtained by using a perturbation-based stochastic finite element method (SFEM), which performs well for mild heterogeneity. The proposed method is applied for analysing both the 1-D as well as the 3-D solute transport problems. The results obtained with SFEM are compared with the Monte Carlo simulation for 1-D problems.

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We have studied magneto-transport and optical properties of Ga1-xMnxSb crystals (x = 0.01, 0.02, 0.03 and 0.04) grown by horizontal Bridgman method. Negative magnetoresistance and anomalous Hall effect have been observed below 10K. Temperature dependence of magnetization measurement shows a magnetic ordering below 10K which could arise from Ga1-xMnxSb alloy formation. Also, saturation in magnetization observed even at room temperature suggests the existence of ferromagnetic MnSb clusters. Reduction in band gap is observed with increasing Mn concentration in the crystals. Temperature dependence of band gap follows Bose-Einstein's model.

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Carbon nanofibers of 50–500 nm diameter and several micrometer length were synthesized by high-temperature pyrolysis of dihydro-2,5-furandione (C4H4O3) in the temperature range of 600–980 °C. The formation of both graphitic and non-graphitic structured carbon fibers was observed in high-resolution transmission electron microscope. The Raman spectra of the samples showed the presence of both the D and G bands of varying intensity and sharpness. The low-temperature electrical transport studies on the samples have shown interesting metal–insulator transitions. The films showed variable range hopping conduction in the insulating regime and power law behavior in the critical regime at low temperatures.

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In the present work, a numerical study is performed to predict the effect of process parameters on transport phenomena during solidification of aluminium alloy A356 in the presence of electromagnetic stirring. A set of single-phase governing equations of mass, momentum, energy and species conservation is used to represent the solidification process and the associated fluid flow, heat and mass transfer. In the model, the electromagnetic forces are incorporated using an analytical solution of Maxwell equation in the momentum conservation equations and the slurry rheology during solidification is represented using an experimentally determined variable viscosity function. Finally, the set of governing equations is solved for various process conditions using a pressure based finite volume technique, along with an enthalpy based phase change algorithm. In present work, the effect of stirring intensity and cooling rate are considered. It is found that increasing stirring intensity results in increase of slurry velocity and corresponding increase in the fraction of solid in the slurry. In addition, the increasing stirring intensity results uniform distribution of species and fraction of solid in the slurry. It is also found from the simulation that the distribution of solid fraction and species is dependent on cooling rate conditions. At low cooling rate, the fragmentation of dendrites from the solid/liquid interface is more.

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Magmas, a conserved mammalian protein essential for eukaryotic development, is overexpressed in prostate carcinomas and cells exposed to granulocyte-macrophage colony-stimulating factor (GM-CSF). Reduced Magmas expression resulted in decreased proliferative rates in cultured cells. However, the cellular function of Magmas is still elusive. In this report, we have showed that human Magmas is an ortholog of Saccharomyces cerevisiae Pam16 having similar functions and is critical for protein translocation across mitochondrial inner membrane. Human Magmas shows a complete growth complementation of delta pam16 yeast cells at all temperatures. On the basis of our analysis, we report that Magmas localizes into mitochondria and is peripherally associated with inner mitochondrial membrane in yeast and humans. Magmas forms a stable subcomplex with J-protein Pam18 or DnaJC19 through its C-terminal region and is tethered to TIM23 complex of yeast and humans. Importantly, amino acid alterations in Magmas leads to reduced stability of the subcomplex with Pam18 that results in temperature sensitivity and in vivo protein translocation defects in yeast cells. These observations highlight the central role of Magmas in protein import and mitochondria biogenesis. In humans, absence of a functional DnaJC19 leads to dilated cardiac myophathic syndrome (DCM), a genetic disorder with characteristic features of cardiac myophathy and neurodegeneration. We propose that the mutations resulting in decreased stability of functional Magmas:DnaJC19 subcomplex at human TIM23 channel leads to impaired protein import and cellular respiration in DCM patients. Together, we propose a model showing how Magmas:DnaJC19 subcomplex is associated with TIM23 complex and thus regulates mitochondrial import process.

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La0.5Li0.5TiO3 perovskite was synthesized by various wet chemical methods. By adopting low temperature methods of preparation lithium loss from the material is prevented. La0.5Li0.5TiO3 (LLTO) was formed with cubic symmetry at 1473 K. LLTO was formed at relatively lower temperature by using hydrothermal preparation method. PVA gel-decomposition route yield tetragonal LLTO on annealing the dried gel at 1473 K. By using gel-carbonate route LiTi2O4 minor phase was found to remain even after heat-treatment at 1473 K. The hydroxylation of LLTO was done in deionized water as well as in dilute acetic acid medium. By hydroxylation process incorporation of hydroxyls and leaching out of Li+ was observed from the material. The Li+ concentration of these compositions was examined by AAS. The electrical conductivities of these compositions were measured by dc and ac impedance techniques at elevated temperatures. The activation energies of electrical conduction for these compositions were estimated from the experimental results. The measured activation energy of Li+ conduction is 0.34 eV. Unhydroxylated samples exhibit only Li+ conduction, whereas, the hydroxylated LLTO show proton conductivity at 298-550 K in addition to Li+ conductivity. The effect of Zr or Ce substitution in place of Ti were attempted. La0.5Li0.5ZrO3 Perovskite was not formed; instead pyrochlore phase (La2Zr2O7) along with monoclinic ZrO2 phases was observed above 1173 K; below 1173 K cubic ZrO2 is stable. (La0.5Li0.5)(2)CeO4 solid solution was formed in the case of Ce substitution at Ti sublattice on heat-treatment up to 1673 K. (c) 2005 Springer Science + Business Media, Inc.

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Suitable pin-to-hole interference can significantly increase the fatigue life of a pin joint. In practical design, the initial stresses due to interference are high and they are proportional to the effective interference. In experimental studies on such joints, difficulties have been experienced in estimating the interference accurately from physical measurements of pin and hole diameters. A simple photoelastic method has been developed to determine the effective interference to a high degree of accuracy. This paper presents the method and reports illustrative data from a successful application thereof.

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Results of measurements at a high frequency on reverse bias capacitance of copper-doped germanium junctions are reported. Phenomenal increase in capacitance is found in the breakdown region, particularly at low temperatures.

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The rate of absorption of amino acids from mixtures has been studied in the silkworm midgut by using an in vitro perfusion technique. The rates differ for individual amino acids. A characteristic absorption pattern is observed which is independent of the amino acid composition of the mixture used. The metabolic inhibitors dinitrophenol and cyanide have no effect on the amino acid transport from mixtures. Based on these results an energy-independent, carrier-mediated transport is postulated.

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We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

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We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.