41 resultados para semi conducting polymers, electroluminescence, photovoltaics

em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain


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Both the intermolecular interaction energies and the geometries for M ̄ thiophene, M ̄ pyrrole, M n+ ̄ thiophene, and M n+ ̄ pyrrole ͑with M = Li, Na, K, Ca, and Mg; and M n+ = Li+ , Na+ , K+ , Ca2+, and Mg2+͒ have been estimated using four commonly used density functional theory ͑DFT͒ methods: B3LYP, B3PW91, PBE, and MPW1PW91. Results have been compared to those provided by HF, MP2, and MP4 conventional ab initio methods. The PBE and MPW1PW91 are the only DFT methods able to provide a reasonable description of the M ̄ complexes. Regarding M n+ ̄ ␲ complexes, the four DFT methods have been proven to be adequate in the prediction of these electrostatically stabilized systems, even though they tend to overestimate the interaction energies.

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We consider linear optimization over a nonempty convex semi-algebraic feasible region F. Semidefinite programming is an example. If F is compact, then for almost every linear objective there is a unique optimal solution, lying on a unique \active" manifold, around which F is \partly smooth", and the second-order sufficient conditions hold. Perturbing the objective results in smooth variation of the optimal solution. The active manifold consists, locally, of these perturbed optimal solutions; it is independent of the representation of F, and is eventually identified by a variety of iterative algorithms such as proximal and projected gradient schemes. These results extend to unbounded sets F.

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In this paper, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non-homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.

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Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

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L’objectiu d’aquest PFC és desenvolupar una eina d’edició de façanes procedural apartir d’una imatge d’una façana real. L’aplicació generarà les regles procedurals de lafaçana a partir de dades adquirides del model que es vol representar, com unafotografia. L’usuari de l’aplicació generarà de forma semi-automàtica i interactiva lesregles de subdivisió i repetició, especificant també la inserció de elementsarquitectònics (portes, finestres), que podran ser instanciats a partir d’una llibreria. Uncop generades, les regles s’escriuran en el format del sistema BuildingEngine perintegrar-se completament dins el procés de modelatge urbà.Aquest projecte es desenvoluparà en Matlab

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In this paper we define the formal and tempered Deligne cohomology groups, that are obtained by applying the Deligne complex functor to the complexes of formal differential forms and tempered currents respectively. We then prove the existence of a duality between them, a vanishing theorem for the former and a semipurity property for the latter. The motivation of these results comes from the study of covariant arithmetic Chow groups. The semipurity property of tempered Deligne cohomology implies, in particular, that several definitions of covariant arithmetic Chow groups agree for projective arithmetic varieties.

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In this work, we demonstrate that conductive atomic force microscopy (C-AFM) is a very powerful tool to investigate, at the nanoscale, metal-oxide-semiconductor structures with silicon nanocrystals (Si-nc) embedded in the gate oxide as memory devices. The high lateral resolution of this technique allows us to study extremely small areas ( ~ 300nm2) and, therefore, the electrical properties of a reduced number of Si-nc. C-AFM experiments have demonstrated that Si-nc enhance the gate oxide electrical conduction due to trap-assisted tunneling. On the other hand, Si-nc can act as trapping centers. The amount of charge stored in Si-nc has been estimated through the change induced in the barrier height measured from the I-V characteristics. The results show that only ~ 20% of the Si-nc are charged, demonstrating that the electrical behavior at the nanoscale is consistent with the macroscopic characterization.

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High optical power density of 0.5 mW/cm2, external quantum efficiency of 0.1%, and population inversion of 7% are reported from Tb+-implanted silicon-rich silicon nitride/oxide light emitting devices. Electrical and electroluminescence mechanisms in these devices were investigated. The excitation cross section for the 543 nm Tb3+ emission was estimated under electrical pumping, resulting in a value of 8.2 × 10−14 cm2, which is one order of magnitude larger than one reported for Tb3+:SiO2 light emitting devices. These results demonstrate the potentiality of Tb+-implanted silicon nitride material for the development of integrated light sources compatible with Si technology.

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Within a drift-diffusion model we investigate the role of the self-consistent electric field in determining the impedance field of a macroscopic Ohmic (linear) resistor made by a compensated semi-insulating semiconductor at arbitrary values of the applied voltage. The presence of long-range Coulomb correlations is found to be responsible for a reshaping of the spatial profile of the impedance field. This reshaping gives a null contribution to the macroscopic impedance but modifies essentially the transition from thermal to shot noise of a macroscopic linear resistor. Theoretical calculations explain a set of noise experiments carried out in semi-insulating CdZnTe detectors.