342 resultados para optimal composition

em Indian Institute of Science - Bangalore - Índia


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A systematic study of the Tl0.5Pb0.5Sr2Gd2−xCexCu2O9−δ system has revealed the existence of a pure phase in the compositional. range 0.0≤x≤0.6 crystalizzing in the 1222 structure. It has an intersheet distance of approximately 6 Å, a value much higher than those found in other cuprates with double CuO2 sheets interleaved by a single fluorite layer. Superconductivity has been observed in the range 0.1≤x≤0.4 with a Tc of 45 K and a superconductive volume fraction up to 20% for the optimal composition. An interesting variation of the superconducting properties of the above system with the composition, i.e. cerium content, has also been noticed. A possible dependence of superconductivity on the coupling between CuO2 sheets in the layered cuprates has been pointed out to bring out a correlation between structure and properties.

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An optimal composition of La0.67Cd0.33MnO3 was synthesized by ceramic route. The compound crystallized in a rhombohedral structure with lattice parameters a = 5.473(4) Å and α = 60°37′. Resistivity measurement showed an insulator-to-metal transition coupled with a ferromagnetic transition of around 255 K. Epitaxial thin films were fabricated on the LaAlO3 (100) substrate by a pulsed laser deposition technique. The psuedocubic lattice parameter a of the film is 3.873(4) Å. The insulator-to-metal transition of the film was observed at 250 K which is comparable with the bulk value. The film was ferromagnetic below this temperature. Magnetoresistance defined as ΔR/R0 = (RH−R0)/R0 was over −86% near the insulator-to-metal transition temperature of 240 K at 6 T magnetic field and over-30% at relatively low fields of 1 T. No magnetoresistance was observed at low temperatures in the film unlike in the polycrystalline sample, where about a 40% decrease in resistance was observed on applying 6 T magnetic field due to the spin dependent scattering at the grain boundaries.

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The superconducting transition temperatures in Bi2Ca1−xLnxSr2Cu2O8+δ, TlCa1−xLnxSr2Cu2O6+δ, and Tl0.8Ca1−xLnxBa2Cu23O6+δ (Ln=Y or rare earth) vary with composition and show a maximum at a specific value of x or δ. This observation suggests that an optimal carrier concentration is required to attain maximum Tc in such cuprates which seem to be two‐band systems

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We examine the effect of subdividing the potential barrier along the reaction coordinate on Kramers' escape rate for a model potential. Using the known supersymmetric potential approach, we show the existence of an optimal number of subdivisions that maximizes the rate.

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Sr2FeMoO6 oxides exhibit a half-metallic ferromagnetic (HM-FM) ground state and peculiar magnetic and magnetotransport properties, which are interesting for applications in the emerging field of spintronics and attractive for fundamental research in the field of heavily correlated electron systems. Sr2FeWO6 is an insulator with an antiferromagnetic (I-AFM) ground state. The solid solutions Sr2FeMoxW1-xO6 also have peculiar properties-W doping enhances chemical order which allows stabilization of the HM-FM state; as the W content exceeds a certain value a metal to insulator transition (MIT) occurs. The role of W in determining the physical properties of Sr2FeMoxW1-xO6 systems has been a matter of intense investigation. This work deals with the problem of the structural and electronic changes related to the MIT from a local perspective by means of x-ray absorption spectroscopy (XAS). This technique allows one to probe in detail the local structure and electronic modifications around selected absorber ions (W, Mo, Fe and Sr in our case). The results of XAS analysis in the whole composition range (0 <= x <= 1), in the near edge (XANES) and extended (EXAFS) regions, demonstrate an abrupt change of the local structure around the Fe and Mo sites at the critical composition, x(c). This change represents the microstructural counterpart associated with the MIT. Conversely, the local structure and electronic configuration of W ions remain unaltered in the whole composition range, suggesting indirect participation of W in the MIT.

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The composition-controlled metal-insulator transition in the perovskite systems LaNi1-xMxO3 (M = Cr, Mn, Fe, and Co) has been investigated by transport measurements over the temperature range 12-300 K. These systems, which have critical electron densities (nc) in the range (1-2) -1020 electrons cm-3, exhibit sharp metal-insulator transitions at the base temperature. The corresponding minimum metallic conductivity (Ï-min), separating the localized and itinerant electronic regimes, is of the order of 102 ohm-1 cm-1. Particular attention is paid to the idea of Ï-min scaling with nc, and our present results are compared with earlier studies of the metal-insulator transition in low (e.g., Ge:Sb) and high (e.g., metal-ammonia, supercritical Hg) electron-density systems. A link is established between the transport and magnetic properties of the title systems at the metal-insulator transition.

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We have prepared, characterized and investigated a new PEG-2000 based solid polymer electrolyte (PEG) x NH4I. Ionic conductivity measurements have been made as a function of salt concentration as well as temperature in the range 265–330 K. Selected compositions of the electrolyte were exposed to a beam of 8 MeV electrons to an accumulated dose of 10 kGy to study the effect on ionic conductivity. The electrolyte samples were also quenched at liquid nitrogen temperature and conductivity measurements were made. The ionic conductivity at room temperature exhibits a characteristic double peak for the composition x = 20 and 70. Both electron beam irradiation and quenching at low temperature have resulted in an increase in conductivity by 1–2 orders of magnitude. The enhancement of conductivity upon irradiation and quenching is interpreted as due to an increase in amorphous region and decrease in crystallinity of the electrolyte. DSC and proton NMR measurements also support this conclusion.

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The problem of optimal scheduling of the generation of a hydro-thermal power system that is faced with a shortage of energy is studied. The deterministic version of the problem is first analyzed, and the results are then extended to cases where the loads and the hydro inflows are random variables.

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This paper deals with the optimal load flow problem in a fixed-head hydrothermal electric power system. Equality constraints on the volume of water available for active power generation at the hydro plants as well as inequality constraints on the reactive power generation at the voltage controlled buses are imposed. Conditions for optimal load flow are derived and a successive approximation algorithm for solving the optimal generation schedule is developed. Computer implementation of the algorithm is discussed, and the results obtained from the computer solution of test systems are presented.

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Surface composition and depth profile studies of hemiplated thin film CdS:CuzS solar cells have been carried out using x-ray photoelectron spectroscopy (XPS) and Auger electron spectroscopy (AES) techniques. These studies indicate that the junction is fairly diffused in the as-prepared cell. However, heat treatment of the cell at 210°C in air relatively sharpens the junction and improves the cell performance. Using the Cu(2p3p)/S(2p) ratio as well as the Cu(LVV)/(LMM) Auger intensity ratio, it can be inferred that the nominal valency of copper in the layers above the junction is Cut and it is essentially in the CUSS form. Copper signals are observed from layers deep down in the cell. These seem to appear mostly from the grain boundary region. From the observed concentration of Cd, Cu and S in these deeper layers and the Cu(LVV)/(LMM) ratio it appears that the signals from copper essentially originate partly from copper in CuS and partly from Cu2t trapped in the lattice. It is significant to note that the nominal valence state of copper changes rather abruptly from Cut to Cuz+ across the junction.

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Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.

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We consider the problem of estimating the optimal parameter trajectory over a finite time interval in a parameterized stochastic differential equation (SDE), and propose a simulation-based algorithm for this purpose. Towards this end, we consider a discretization of the SDE over finite time instants and reformulate the problem as one of finding an optimal parameter at each of these instants. A stochastic approximation algorithm based on the smoothed functional technique is adapted to this setting for finding the optimal parameter trajectory. A proof of convergence of the algorithm is presented and results of numerical experiments over two different settings are shown. The algorithm is seen to exhibit good performance. We also present extensions of our framework to the case of finding optimal parameterized feedback policies for controlled SDE and present numerical results in this scenario as well.

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In this paper, we consider the bi-criteria single machine scheduling problem of n jobs with a learning effect. The two objectives considered are the total completion time (TC) and total absolute differences in completion times (TADC). The objective is to find a sequence that performs well with respect to both the objectives: the total completion time and the total absolute differences in completion times. In an earlier study, a method of solving bi-criteria transportation problem is presented. In this paper, we use the methodology of solvin bi-criteria transportation problem, to our bi-criteria single machine scheduling problem with a learning effect, and obtain the set of optimal sequences,. Numerical examples are presented for illustrating the applicability and ease of understanding.

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In a letter RauA proposed a new method for designing statefeedback controllers using eigenvalue sensitivity matrices. However, there appears to be a conceptual mistake in the procedure, or else it is unduly restricted in its applicability. In particular the equation — BR~lBTK = A/.I, in which K is a positive-definite symmetric matrix.

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Cooperative relay communication in a fading channel environment under the orthogonal amplify-and-forward (OAF), nonorthogonal and orthogonal selection decode-and-forward (NSDF and OSDF) protocols is considered here. The diversity-multiplexing gain tradeoff (DMT) of the three protocols is determined and DMT-optimal distributed space-time (ST) code constructions are provided. The codes constructed are sphere decodable and in some instances incur minimum possible delay. Included in our results is the perhaps surprising finding that the orthogonal and the nonorthogonal amplify-and-forward (NAF) protocols have identical DMT when the time durations of the broadcast and cooperative phases are optimally chosen to suit the respective protocol. Moreover our code construction for the OAF protocol incurs less delay. Two variants of the NSDF protocol are considered: fixed-NSDF and variable-NSDF protocol. In the variable-NSDF protocol, the fraction of time occupied by the broadcast phase is allowed to vary with multiplexing gain. The variable-NSDF protocol is shown to improve on the DMT of the best previously known static protocol when the number of relays is greater than two. Also included is a DMT optimal code construction for the NAF protocol.