407 resultados para ELECTRICAL TRANSPORT
Resumo:
Electronic and ionic conductivities of silver selenide crystal (Ag$_2+\delta$ Se) have been measured over a range of stoichiometry through the $\alpha - \beta$ transition by using solid state electrochemical techniques. In the high temperature $\beta$-phase Ag$_2$Se shows metallic behaviour of electronic conductivity for high values of $\delta$; with decrease in $\delta$, the conductivity of the material exhibits a transition. The magnitude of change in electronic conductivity at the $\alpha - \beta$ transition is also determined by stoichiometry. Ionic conductivity of the $\beta$-phase does not vary significantly with stochiometry. Ionic conductivity of the $\beta$-does not vary significantly with stoichiometry. A model to explain the observed transport properties has been suggested.
Resumo:
Two families of low correlation QAM sequences are presented here. In a CDMA setting, these sequences have the ability to transport a large amount of data as well as enable variable-rate signaling on the reverse link. The first family Á2SQ - B2− is constructed by interleaving 2 selected QAM sequences. This family is defined over M 2-QAM, where M = 2 m , m ≥ 2. Over 16-QAM, the normalized maximum correlation [`(q)]maxmax is bounded above by <~1.17 ÖNUnknown control sequence '\lesssim' , where N is the period of the sequences in the family. This upper bound on [`(q)]maxmax is the lowest among all known sequence families over 16-QAM.The second family Á4SQ4 is constructed by interleaving 4 selected QAM sequences. This family is defined over M 2-QAM, where M = 2 m , m ≥ 3, i.e., 64-QAM and beyond. The [`(q)]maxmax for sequences in this family over 64-QAM is upper bounded by <~1.60 ÖNUnknown control sequence '\lesssim' . For large M, [`(q)]max <~1.64 ÖNUnknown control sequence '\lesssim' . These upper bounds on [`(q)]maxmax are the lowest among all known sequence families over M 2-QAM, M = 2 m , m ≥ 3.
Resumo:
A low correlation interleaved QAM sequence family is presented here. In a CDMA setting, these sequences have the ability to transport a large amount of data as well as enable variable-rate signaling on the reverse link. The new interleaved selected family INQ has period N, normalized maximum correlation parameter thetasmacrmax bounded above by lsim a radicN, where a ranges from 1.17 in the 16-QAM case to 1.99 for large M2-QAM, where M = 2m, m ges 2. Each user is enabled to transfer m + 1 bits of data per period of the spreading sequence. These constructions have the lowest known value of maximum correlation of any sequence family with the same alphabet.
Resumo:
Cobalt and iron nanoparticles are doped in carbon nanotube (CNT)/polymer matrix composites and studied for strain and magnetic field sensing properties. Characterization of these samples is done for various volume fractions of each constituent (Co and Fe nanoparticles and CNTs) and also for cases when only either of the metallic components is present. The relation between the magnetic field and polarization-induced strain are exploited. The electronic bandgap change in the CNTs is obtained by a simplified tight-binding formulation in terms of strain and magnetic field. A nonlinear constitutive model of glassy polymer is employed to account for (1) electric bias field dependent softening/hardening (2) CNT orientations as a statistical ensemble and (3) CNT volume fraction. An effective medium theory is then employed where the CNTs and nanoparticles are treated as inclusions. The intensity of the applied magnetic field is read indirectly as the change in resistance of the sample. Very small magnetic fields can be detected using this technique since the resistance is highly sensitive to strain. Its sensitivity due to the CNT volume fraction is also discussed. The advantage of this sensor lies in the fact that it can be molded into desirable shape and can be used in fabrication of embedded sensors where the material can detect external magnetic fields on its own. Besides, the stress-controlled hysteresis of the sample can be used in designing memory devices. These composites have potential for use in magnetic encoders, which are made of a magnetic field sensor and a barcode.
Resumo:
Ionic polymer-metal composites (IPMC), piezoelectric polymer composites and nematic elastomer composites are materials, which exhibit characteristics of both sensors and actuators. Large deformation and curvature are observed in these systems when electric potential is applied. Effects of geometric non-linearity due to the chargeinduced motion in these materials are poorly understood. In this paper, a coupled model for understanding the behavior of an ionic polymer beam undergoing large deformation and large curvature is presented. Maxwell's equations and charge transport equations are considered which couple the distribution of the ion concentration and the pressure gradient along length of a cantilever beam with interdigital electrodes. A nonlinear constitutive model is derived accounting for the visco-elasto-plastic behavior of these polymers and based on the hypothesis that the presence of electrical charge stretches/contracts bonds, which give rise to electrical field dependent softening/hardening. Polymer chain orientation in statistical sense plays a role on such softening or hardening. Elementary beam kinematics with large curvature is considered. A model for understanding the deformation due to electrostatic repulsion between asymmetrical charge distributions across the cross-sections is presented. Experimental evidence that Silver(Ag) nanoparticle coated IPMCs can be used for energy harvesting is reported. An IPMC strip is vibrated in different environments and the electric power against a resistive load is measured. The electrical power generated was observed to vary with the environment with maximum power being generated when the strip is in wet state. IPMC based energy harvesting systems have potential applications in tidal wave energy harvesting, residual environmental energy harvesting to power MEMS and NEMS devices.
Resumo:
The transport processes of the dissolved chemicals in stratified or layered soils have been studied for several decades. In case of the solute transport through stratified layers, interface condition plays an important role in determining appropriate transport parameters. First‐ type and third‐ type interface conditions are generally used in the literature. A first‐type interface condition will result in a continuous concentration profile across the interface at the expense of solute mass balance. On the other hand, a discontinuity in concentration develops when a third‐ type interface condition is used. To overcome this problem, a combined first‐ and third‐ type condition at the interface has been widely employed which yields second‐ type condition. This results in a similar break‐through curve irrespective of the layering order, which is non‐physical. In this work, an interface condition is proposed which satisfies the mass balance implicitly and brings the distinction between the breakthrough curves for different layering sequence corroborating with the experimental observations. This is in disagreement with the earlier work by H. M. Selim and co‐workers but, well agreement with the hypothetical result by Bosma and van der Zee; and Van der Zee.
Resumo:
Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.
Resumo:
Molecular diffusion plays a dominant role in transport of contaminants through fine-grained soils with low hydraulic conductivity. Attenuation processes occur while contaminants travel through the soils. Effective diffusion coefficient (De) is expected to take into consideration various attenuation processes. Effective diffusion coefficient has been considered to develop a general approach for modelling of contaminant transport in soils.The effective diffusion coefficient of sodium in presence of sulphate has been obtained using the column test.The reliability of De, has been checked by comparing theoretical breakthrough curves of sodium ion in soils obtained using advection diffusion equation with the experimental curve.
Resumo:
Sugars perform two vital functions in plants: as compatible solutes protecting the cell against osmotic stress and as mobile source of immediate and long-term energy requirement for growth and development. The two sugars that occur commonly in nature are sucrose and trehalose. Sucrose comprises one glucose and one fructose molecule; trehalose comprises two glucose molecules. Trehalose occurs in significant amounts in insects and fungi which greatly outnumber the plants. Surprisingly, in plants trehalose has been found in barely detectable amounts, if at all, raising the question `why did nature select sucrose instead of trehalose as the mobile energy source and as storage sugar for the plants'? Modelling revealed that when attached to the ribbon-shaped beta-1,4 glucan a trehalose molecule is shaped like a hook. This suggests that the beta-1,4 glucan chains with attached trehalose will fail to align to form inter-chain hydrogen bonds and coalesce into a cellulose microfibril, as a result of which in trehalose-accumulating plant cells, the cell wall will tend to become leaky. Thus in plants an evolutionary selection was made in favour of sucrose as the mobile energy source. Genetic engineering of plant cells for combating abiotic stresses through microbial trehalose-producing genes is fraught with risk of damage to plant cell walls.