158 resultados para Electrical bias


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We have investigated a resonant refractive nonlinearity in a semiconductor waveguide by measuring intensity dependent phase shifts and bias-dependent recovery times. The measurements were performed on an optimized 750-μm-long AR coated buried heterostructure MQW p-i-n waveguide with a bandedge at 1.48 μm. Figure 1 shows the experimental arrangement. The mode-locked color center laser was tuned to 50 meV beyond the bandedge and 8 ps pulses with peak incident power up to 57 W were coupled into the waveguide. Some residual bandtail absorption remains at this wavelength and this is sufficient to cause carriers to be photogenerated and these give rise to a refractive nonlinearity, predominantly by plasma and bandfilling effects. A Fabry-Perot interferometer is used to measure the spectrum of the light which exits the waveguide. The nonlinearity within the guide causes self phase modulation (SPM) of the light and a study of the spectrum allows information to be recovered on the magnitude and recovery time of the nonlinear phase shift with a reasonable degree of accuracy. SPM spectra were recorded for a variety of pulse energies coupled into he unbiased waveguide. Figure 2 shows the resultant phase shift measured from the SPM spectra as a function of pulse energy. The relationship is a linear one, indicating that no saturation of the nonlinearity occurs for coupled pulse energies up to 230 pJ. A π phase shift, the minimum necessary for an all-optical switch, is obtained for a coupled pulse energy of 57 pJ while the maximum phase shift, 4 π, was measured for 230 pJ. The SPM spectra were highly asymmetric with pulse energy shifted to higher frequencies. Such spectra are characteristic of a slow, negative nonlinearity. This relatively slow speed is expected for the unbiased guide as the recovery time will be of the order of the recombination time of the photogenerated electrons, about 1 ns for InGaAsP material. In order to reduce the recovery time of the nonlinearity, it is necessary to remove the photogenerated carriers from the waveguide by a process other than recombination. One such technique is to apply a reverse bias to the waveguide in order to sweep the carriers out. Figure 3 shows the effect on the recovery time of the nonlinearity of applying reverse bias to the waveguide for 230 pJ coupled power. The recovery time was reduced from one much longer than the length of the pulse, estimated to be about 1 ns, at zero bias to 18 ± 3 ps for a bias voltage greater than -4 V. This compares with a value of 24 ps obtained in a bulk waveguide.

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AC loss can be a significant problem for any applications that utilize or produce an AC current or magnetic field, such as an electric machine. The authors are currently investigating the electromagnetic properties of high temperature superconductors with a particular focus on the AC loss in coils made from YBCO superconductors. In this paper, a 2D finite element model based on the H formulation is introduced. The model is then used to calculate the transport AC loss using both a bulk approximation and modeling the individual turns in a racetrack-shaped coil. The coil model is based on the superconducting stator coils used in the University of Cambridge EPEC Superconductivity Group's superconducting permanent magnet synchronous motor design. The transport AC loss of a stator coil is measured using an electrical method based on inductive compensation using a variable mutual inductance. The simulated results are compared with the experimental results, verifying the validity of the model, and ways to improve the accuracy of the model are discussed. © 2010 IEEE.

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In this paper, we present experimental results describing enhanced readout of the vibratory response of a doubly clamped zinc oxide (ZnO) nanowire employing a purely electrical actuation and detection scheme. The measured response suggests that the piezoelectric and semiconducting properties of ZnO effectively enhance the motional current for electromechanical transduction. For a doubly clamped ZnO nanowire resonator with radius ~10 nm and length ~1.91 µm, a resonant frequency around 21.4 MHz is observed with a quality factor (Q) of ~358 in vacuum. A comparison with the Q obtained in air (~242) shows that these nano-scale devices may be operated in fluid as viscous damping is less significant at these length scales. Additionally, the suspended nanowire bridges show field effect transistor (FET) characteristics when the underlying silicon substrate is used as a gate electrode or using a lithographically patterned in-plane gate electrode. Moreover, the Young's modulus of ZnO nanowires is extracted from a static bending test performed on a nanowire cantilever using an AFM and the value is compared to that obtained from resonant frequency measurements of electrically addressed clamped–clamped beam nanowire resonators.

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Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when . certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervised neural network models can cope easily with roving conditions. What makes humans so inferior compared to these models? As experimental and conceptual work has shown, human perceptual learning is neither supervised nor unsupervised but reward-based learning. Reward-based learning suffers from the so-called unsupervised bias, i.e., to prevent synaptic " drift" , the . average reward has to be exactly estimated. However, this is impossible when two or more stimulus types with different rewards are presented during training (and the reward is estimated by a running average). For this reason, we propose no learning occurs in roving conditions. However, roving hinders perceptual learning only for combinations of similar stimulus types but not for dissimilar ones. In this latter case, we propose that a critic can estimate the reward for each stimulus type separately. One implication of our analysis is that the critic cannot be located in the visual system. © 2011 Elsevier Ltd.