7 resultados para self-enhancement

em Universidad Politécnica de Madrid


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A new method for measuring the linewidth enhancement factor (α-parameter) of semiconductor lasers is proposed and discussed. The method itself provides an estimation of the measurement error, thus self-validating the entire procedure. The α-parameter is obtained from the temporal profile and the instantaneous frequency (chirp) of the pulses generated by gain switching. The time resolved chirp is measured with a polarization based optical differentiator. The accuracy of the obtained values of the α-parameter is estimated from the comparison between the directly measured pulse spectrum and the spectrum reconstructed from the chirp and the temporal profile of the pulse. The method is applied to a VCSEL and to a DFB laser emitting around 1550 nm at different temperatures, obtaining a measurement error lower than ± 8%.

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This doctoral thesis explores some of the possibilities that near-field optics can bring to photovoltaics, and in particular to quantum-dot intermediate band solar cells (QD-IBSCs). Our main focus is the analytical optimization of the electric field distribution produced in the vicinity of single scattering particles, in order to produce the highest possible absorption enhancement in the photovoltaic medium in their surroundings. Near-field scattering structures have also been fabricated in laboratory, allowing the application of the previously studied theoretical concepts to real devices. We start by looking into the electrostatic scattering regime, which is only applicable to sub-wavelength sized particles. In this regime it was found that metallic nano-spheroids can produce absorption enhancements of about two orders of magnitude on the material in their vicinity, due to their strong plasmonic resonance. The frequency of such resonance can be tuned with the shape of the particles, allowing us to match it with the optimal transition energies of the intermediate band material. Since these metallic nanoparticles (MNPs) are to be inserted inside the cell photovoltaic medium, they should be coated by a thin insulating layer to prevent electron-hole recombination at their surface. This analysis is then generalized, using an analytical separation-of-variables method implemented in Mathematica7.0, to compute scattering by spheroids of any size and material. This code allowed the study of the scattering properties of wavelengthsized particles (mesoscopic regime), and it was verified that in this regime dielectric spheroids perform better than metallic. The light intensity scattered from such dielectric spheroids can have more than two orders of magnitude than the incident intensity, and the focal region in front of the particle can be shaped in several ways by changing the particle geometry and/or material. Experimental work was also performed in this PhD to implement in practice the concepts studied in the analysis of sub-wavelength MNPs. A wet-coating method was developed to self-assemble regular arrays of colloidal MNPs on the surface of several materials, such as silicon wafers, amorphous silicon films, gallium arsenide and glass. A series of thermal and chemical tests have been performed showing what treatments the nanoparticles can withstand for their embedment in a photovoltaic medium. MNPs arrays are then inserted in an amorphous silicon medium to study the effect of their plasmonic near-field enhancement on the absorption spectrum of the material. The self-assembled arrays of MNPs constructed in these experiments inspired a new strategy for fabricating IBSCs using colloidal quantum dots (CQDs). Such CQDs can be deposited in self-assembled monolayers, using procedures similar to those developed for the patterning of colloidal MNPs. The use of CQDs to form the intermediate band presents several important practical and physical advantages relative to the conventional dots epitaxially grown by the Stranski-Krastanov method. Besides, this provides a fast and inexpensive method for patterning binary arrays of QDs and MNPs, envisioned in the theoretical part of this thesis, in which the MNPs act as antennas focusing the light in the QDs and therefore boosting their absorption

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A good and early fault detection and isolation system along with efficient alarm management and fine sensor validation systems are very important in today¿s complex process plants, specially in terms of safety enhancement and costs reduction. This paper presents a methodology for fault characterization. This is a self-learning approach developed in two phases. An initial, learning phase, where the simulation of process units, without and with different faults, will let the system (in an automated way) to detect the key variables that characterize the faults. This will be used in a second (on line) phase, where these key variables will be monitored in order to diagnose possible faults. Using this scheme the faults will be diagnosed and isolated in an early stage where the fault still has not turned into a failure.

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Enhancement-mode (E-mode) high electron mobility transistors (HEMTs) based on a standard AlGaN/GaN heterostructure have been fabricated using two different methods: 19F implantation and fluorine-based plasma treatment. The need of a thermal annealing after both treatments has been proven in order to restore the ID and gm levels. DC characterization at high temperature has demonstrated that ID and gm decrease reversibly due to the reduction of the electron mobility and the drift velocity. Pulsed measurements (state period and variable pulse width) have been performed to study the self-heating effects.

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Concepts of lateral ordering of epitaxial semiconductor quantum dots (QDs) are for the first time transferred to hybrid nanostructures for active plasmonics. We review our recent research on the self-alignment of epitaxial nanocrystals of In and Ag on ordered one-dimensional In(Ga)As QD arrays and isolated QDs by molecular beam epitaxy. By changing the growth conditions the size and density of the metal nanocrystals are easily controlled and the surface plasmon resonance wavelength is tuned over a wide range in order to match the emission wavelength of the QDs. Photoluminescence measurements reveal large enhancement of the emitted light intensity due to plasmon enhanced emission and absorption down to the single QD level.

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A colloidal deposition technique is presented to construct long-range ordered hybrid arrays of self-assembled quantum dots and metal nanoparticles. Quantum dots are promising for novel opto-electronic devices but, in most cases, their optical transitions of interest lack sufficient light absorption to provide a significant impact in their implementation. A potential solution is to couple the dots with localized plasmons in metal nanoparticles. The extreme confinement of light in the near-field produced by the nanoparticles can potentially boost the absorption in the quantum dots by up to two orders of magnitude. In this work, light extinction measurements are employed to probe the plasmon resonance of spherical gold nanoparticles in lead sulfide colloidal quantum dots and amorphous silicon thin-films. Mie theory computations are used to analyze the experimental results and determine the absorption enhancement that can be generated by the highly intense near-field produced in the vicinity of the gold nanoparticles at their surface plasmon resonance. The results presented here are of interest for the development of plasmon-enhanced colloidal nanostructured photovoltaic materials, such as colloidal quantum dot intermediate-band solar cells.

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Providing security to the emerging field of ambient intelligence will be difficult if we rely only on existing techniques, given their dynamic and heterogeneous nature. Moreover, security demands of these systems are expected to grow, as many applications will require accurate context modeling. In this work we propose an enhancement to the reputation systems traditionally deployed for securing these systems. Different anomaly detectors are combined using the immunological paradigm to optimize reputation system performance in response to evolving security requirements. As an example, the experiments show how a combination of detectors based on unsupervised techniques (self-organizing maps and genetic algorithms) can help to significantly reduce the global response time of the reputation system. The proposed solution offers many benefits: scalability, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, and high ability in detecting and confining attacks. For these reasons, we believe that our solution is capable of coping with the dynamism of ambient intelligence systems and the growing requirements of security demands.