928 resultados para Electric field simulations


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This work reports the development of field-effect transistors (FETs), whose channel is based on zinc oxide (ZnO) nanoparticles (NPs). Using screen-printing as the primary deposition technique, different inks were developed, where the semiconducting ink is based on a ZnO NPs dispersion in ethyl cellulose (EC). These inks were used to print electrolyte-gated transistors (EGTs) in a staggered-top gate structure on glass substrates, using a lithium-based polymeric electrolyte. In another approach, FETs with a staggered-bottom gate structure on paper were developed using a sol-gel method to functionalize the paper’s surface with ZnO NPs, using zinc acetate dihydrate (ZnC4H6O4·2H2O) and sodium hydroxide (NaOH) as precursors. In this case, the paper itself was used as dielectric. The various layers of the two devices were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier Transform Infrared spectroscopy (FTIR), thermogravimetric and differential scanning calorimetric analyses (TG-DSC). Electrochemical impedance spectroscopy (EIS) was used in order to evaluate the electric double-layer (EDL) formation, in the case of the EGTs. The ZnO NPs EGTs present electrical modulation for annealing temperatures equal or superior to 300 ºC and in terms of electrical properties they showed On/Off ratios in the order of 103, saturation mobilities (μSat) of 1.49x10-1 cm2(Vs)-1 and transconductance (gm) of 10-5 S. On the other hand, the ZnO NPs FETs on paper exhibited On/Off ratios in the order of 102, μSat of 4.83x10- 3 cm2(Vs)-1and gm around 10-8 S.

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Electric Vehicles (EVs) are increasingly used nowadays, and different powertrain solutions can be adopted. This paper describes the control system of an axial flux Permanent Magnet Synchronous Motor (PMSM) for EVs powertrain. It is described the implemented Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique. Also, the mathematical model of the PMSM is presented. Both, simulation and experimental, results with different types of mechanical load are presented. The experimental results were obtained using a laboratory test bench. The obtained results are discussed.

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This paper presents the conversion process of a traditional Internal Combustion Engine vehicle into an Electric Vehicle. The main constitutive elements of the Electric Vehicle are presented. The developed powertrain uses a three-phase inverter with Field Oriented Control and space vector modulation. The developed on-board batteries charging system can operate in Grid-to-Vehicle and Vehicle-to-Grid modes. The implemented prototypes were tested, and experimental results are presented. The assembly of these prototypes in the vehicle was made in accordance with the Portuguese legislation about vehicles conversion, and the main adopted solutions are presented.

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Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

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Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

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The simultaneous recording of scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can provide unique insights into the dynamics of human brain function, and the increased functional sensitivity offered by ultra-high field fMRI opens exciting perspectives for the future of this multimodal approach. However, simultaneous recordings are susceptible to various types of artifacts, many of which scale with magnetic field strength and can seriously compromise both EEG and fMRI data quality in recordings above 3T. The aim of the present study was to implement and characterize an optimized setup for simultaneous EEG-fMRI in humans at 7T. The effects of EEG cable length and geometry for signal transmission between the cap and amplifiers were assessed in a phantom model, with specific attention to noise contributions from the MR scanner coldheads. Cable shortening (down to 12cm from cap to amplifiers) and bundling effectively reduced environment noise by up to 84% in average power and 91% in inter-channel power variability. Subject safety was assessed and confirmed via numerical simulations of RF power distribution and temperature measurements on a phantom model, building on the limited existing literature at ultra-high field. MRI data degradation effects due to the EEG system were characterized via B0 and B1(+) field mapping on a human volunteer, demonstrating important, although not prohibitive, B1 disruption effects. With the optimized setup, simultaneous EEG-fMRI acquisitions were performed on 5 healthy volunteers undergoing two visual paradigms: an eyes-open/eyes-closed task, and a visual evoked potential (VEP) paradigm using reversing-checkerboard stimulation. EEG data exhibited clear occipital alpha modulation and average VEPs, respectively, with concomitant BOLD signal changes. On a single-trial level, alpha power variations could be observed with relative confidence on all trials; VEP detection was more limited, although statistically significant responses could be detected in more than 50% of trials for every subject. Overall, we conclude that the proposed setup is well suited for simultaneous EEG-fMRI at 7T.

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La meva incorporació al grup de recerca del Prof. McCammon (University of California San Diego) en qualitat d’investigador post doctoral amb una beca Beatriu de Pinós, va tenir lloc el passat 1 de desembre de 2010; on vaig dur a terme les meves tasques de recerca fins al darrer 1 d’abril de 2012. El Prof. McCammon és un referent mundial en l’aplicació de simulacions de dinàmica molecular (MD) en sistemes biològics d’interès humà. La contribució més important del Prof. McCammon en la simulació de sistemes biològics és el desenvolupament del mètode de dinàmiques moleculars accelerades (AMD). Les simulacions MD convencionals, les quals estan limitades a l’escala de temps del nanosegon (~10-9s), no son adients per l’estudi de sistemes biològics rellevants a escales de temps mes llargues (μs, ms...). AMD permet explorar fenòmens moleculars poc freqüents però que son clau per l’enteniment de molts sistemes biològics; fenòmens que no podrien ser observats d’un altre manera. Durant la meva estada a la “University of California San Diego”, vaig treballar en diferent aplicacions de les simulacions AMD, incloent fotoquímica i disseny de fàrmacs per ordinador. Concretament, primer vaig desenvolupar amb èxit una combinació dels mètodes AMD i simulacions Car-Parrinello per millorar l’exploració de camins de desactivació (interseccions còniques) en reaccions químiques fotoactivades. En segon lloc, vaig aplicar tècniques estadístiques (Replica Exchange) amb AMD en la descripció d’interaccions proteïna-lligand. Finalment, vaig dur a terme un estudi de disseny de fàrmacs per ordinador en la proteïna-G Rho (involucrada en el desenvolupament de càncer humà) combinant anàlisis estructurals i simulacions AMD. Els projectes en els quals he participat han estat publicats (o estan encara en procés de revisió) en diferents revistes científiques, i han estat presentats en diferents congressos internacionals. La memòria inclosa a continuació conté més detalls de cada projecte esmentat.

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There is increasing evidence to suggest that the presence of mesoscopic heterogeneities constitutes the predominant attenuation mechanism at seismic frequencies. As a consequence, centimeter-scale perturbations of the subsurface physical properties should be taken into account for seismic modeling whenever detailed and accurate responses of the target structures are desired. This is, however, computationally prohibitive since extremely small grid spacings would be necessary. A convenient way to circumvent this problem is to use an upscaling procedure to replace the heterogeneous porous media by equivalent visco-elastic solids. In this work, we solve Biot's equations of motion to perform numerical simulations of seismic wave propagation through porous media containing mesoscopic heterogeneities. We then use an upscaling procedure to replace the heterogeneous poro-elastic regions by homogeneous equivalent visco-elastic solids and repeat the simulations using visco-elastic equations of motion. We find that, despite the equivalent attenuation behavior of the heterogeneous poro-elastic medium and the equivalent visco-elastic solid, the seismograms may differ due to diverging boundary conditions at fluid-solid interfaces, where there exist additional options for the poro-elastic case. In particular, we observe that the seismograms agree for closed-pore boundary conditions, but differ significantly for open-pore boundary conditions. This is an interesting result, which has potentially important implications for wave-equation-based algorithms in exploration geophysics involving fluid-solid interfaces, such as, for example, wave field decomposition.

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In this work we analyze how patchy distributions of CO2 and brine within sand reservoirs may lead to significant attenuation and velocity dispersion effects, which in turn may have a profound impact on surface seismic data. The ultimate goal of this paper is to contribute to the understanding of these processes within the framework of the seismic monitoring of CO2 sequestration, a key strategy to mitigate global warming. We first carry out a Monte Carlo analysis to study the statistical behavior of attenuation and velocity dispersion of compressional waves traveling through rocks with properties similar to those at the Utsira Sand, Sleipner field, containing quasi-fractal patchy distributions of CO2 and brine. These results show that the mean patch size and CO2 saturation play key roles in the observed wave-induced fluid flow effects. The latter can be remarkably important when CO2 concentrations are low and mean patch sizes are relatively large. To analyze these effects on the corresponding surface seismic data, we perform numerical simulations of wave propagation considering reservoir models and CO2 accumulation patterns similar to the CO2 injection site in the Sleipner field. These numerical experiments suggest that wave-induced fluid flow effects may produce changes in the reservoir's seismic response, modifying significantly the main seismic attributes usually employed in the characterization of these environments. Consequently, the determination of the nature of the fluid distributions as well as the proper modeling of the seismic data constitute important aspects that should not be ignored in the seismic monitoring of CO2 sequestration problems.

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We have investigated edge modes of different multipolarity sustained by quantum antidots at zero magnetic field. The ground state of the antidot is described within a local-density-functional formalism. Two sum rules, which are exact within this formalism, have been derived and used to evaluate the energy of edge collective modes as a function of the surface density and the size of the antidot.

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We present a study of a phase-separation process induced by the presence of spatially correlated multiplicative noise. We develop a mean-field approach suitable for conserved-order-parameter systems and use it to obtain the phase diagram of the model. Mean-field results are compared with numerical simulations of the complete model in two dimensions. Additionally, a comparison between the noise-driven dynamics of conserved and nonconserved systems is made at the level of the mean-field approximation.

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We present a mean field model that describes the effect of multiplicative noise in spatially extended systems. The model can be solved analytically. For the case of the phi4 potential it predicts that the phase transition is shifted. This conclusion is supported by numerical simulations of this model in two dimensions.

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We analyze the heat transfer between two nanoparticles separated by a distance lying in the near-field domain in which energy interchange is due to the Coulomb interactions. The thermal conductance is computed by assuming that the particles have charge distributions characterized by fluctuating multipole moments in equilibrium with heat baths at two different temperatures. This quantity follows from the fluctuation-dissipation theorem for the fluctuations of the multipolar moments. We compare the behavior of the conductance as a function of the distance between the particles with the result obtained by means of molecular dynamics simulations. The formalism proposed enables us to provide a comprehensive explanation of the marked growth of the conductance when decreasing the distance between the nanoparticles.

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We study numerically the out-of-equilibrium dynamics of the hypercubic cell spin glass in high dimensionalities. We obtain evidence of aging effects qualitatively similar both to experiments and to simulations of low-dimensional models. This suggests that the Sherrington-Kirkpatrick model as well as other mean-field finite connectivity lattices can be used to study these effects analytically.

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We study the electric dipole polarizability α D in 208 Pb based on the predictions of a large and representative set of relativistic and nonrelativistic nuclear mean-field models. We adopt the droplet model as a guide to better understand the correlations between α D and other isovector observables. Insights from the droplet model suggest that the product of α D and the nuclear symmetry energy at saturation density J is much better correlated with the neutron skin thickness r np of 208 Pb than the polarizability alone. Correlations of α D J with r np and with the symmetry energy slope parameter L suggest that α D J is a strong isovector indicator. Hence, we explore the possibility of constraining the isovector sector of the nuclear energy density functional by comparing our theoretical predictions against measurements of both α D and the parity-violating asymmetry in 208 Pb. We find that the recent experimental determination of α D in 208 Pb in combination with the range for the symmetry energy at saturation density J = [31 ± (2) est] MeV suggests r np (208 Pb) = 0 . 165 ± (0 . 009) expt ± (0 . 013) theor ± (0.021) est fm and L = 43 ± (6) expt ± (8) theor ± (12) est MeV