Characterization of transducers and resonators under high drive levels
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Mass is a major driver for future spacecraft, and missions exposed to high radiation levels present even more challenge. Non-invasive pressure measurement techniques that enable the accurate determination of pressures within a propulsion system will be described and their performance reviewed.
Mass is a major driver for future spacecraft and missions exposed to high radiation levels (i.e. Europa Orbiter) present even more challenge. A variety of non-invasive measurement techniques are in development that enables determination of pressures within a propulsion network.
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Cantilever type piezoelectric harvesters, such as bimorphs, are typically used for vibration induced energy harvesting. However, a major drawback of a piezoelectric bimorph is its brittle nature in harsh environments, resulting in short life-times as well as output power degradation. The emphasis in this work is to design robust, highly efficient piezoelectric harvesters that are capable of generating electrical power in the milliwatt range. Various harvesters have been modeled, designed and prototyped, and the flextensional actuator based harvester, where the metal cantilever is mounted and coupled between two flextensional actuators, was found to be a viable alternative to the cantilever type piezoelectric harvesters. Preliminary tests showed that these devices equipped with 5x5x36 mm two piezoelectric PZT stacks can produce greater than 50 mW of power under air flow induced vibrations.
Nylon-11 nanowires have been fabricated in flexible track-etched polymer templates. Customized fabrication equipment was employed to realize an air-flow and gravity assisted template-wetting synthesis technique. X-ray diffraction analysis suggests that the strength of the piezoelectric phase of the nanowire crystals is directly proportional to the air-flow.
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Within the compressive sensing (CS) framework, one effective way to increase the likelihood of successful signal reconstruction is to employ random processes in the construction of the sensing matrix. This work presents a 3D holey cavity, with diverse frequency modes, to spectrally code, that is, randomize, the ultrasound wave fields. The simulated results show that the use of such a cavity enables imaging simple or complex targets, such as spheres or the letter E, by only a single transceiver—something that is not possible without the use of a coding structure like the cavity. The effect of noise on imaging results and the size of the targets on the first-order Born approximation (BA) are also investigated. Moreover, this study attempts to optimize the cavity, based on a single numerical metric, such as the sum of singular values (SSV) or mutual coherence (MC). Yet, it will be shown that neither of these metrics can consistently compare the norm-one imaging performance between two cavities of different materials or hole sizes. This leaves finding a quantitative metric for these kinds of optimizations an open problem.
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Here we introduce an inverse design framework based on artificial neural networks, genetic algorithms, and tight-binding calculations, capable to optimize the very large configuration space of nanoelectronic devices. Our non-linear optimization procedure operates on trial Hamiltonians through superoperators controlling growth policies of regions of distinct doping. We demonstrate that our algorithm optimizes the doping of graphene-based three-terminal devices for valleytronics applications, monotonously converging to synthesizable devices with high merit functions in a few thousand evaluations (out of similar or equal to ≃ 2 3800 possible configurations). The best-performing device allowed for a terminal-specific separation of valley currents with similar or equal to ≃ 96% (≃ 94%) K(K') valley purity. Importantly, the devices found through our non-linear optimization procedure have both a higher merit function and higher robustness to defects than the ones obtained through geometry optimization.
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