Parametric Coupling in Aluminum Nitride Lamb Wave Devices Through a Nonlinear Elastic Modulus
ORAL
Abstract
Parametric coupling was intensely studied in the 1950s where a time varying circuit parameter (i.e. capacitance or inductance) is used to provide frequency conversion, allowing energy supplied at one frequency to be converted to another. The main advantage of this process is its low noise characteristic and is a promising step forward for low noise radio frequency (RF) devices. However, the realization of small devices relying on a time varying circuit parameter is difficult for lower frequency applications (100MHz – 1GHz) due to the long electromagnetic wavelength. In this research, Aluminum Nitride (AlN) Lamb wave devices are investigated as an option for parametric coupling in acoustic waves, significantly reducing the size of devices in the desired frequency range.
AlN Lamb wave devices are modeled, fabricated, and tested. Results show successful parametric mixing in the devices at both an up converted frequency and down converted frequency. The output power of the mixed signal is linearly dependent on the carrier power until gain compression is reached. A circuit model developed closely matches the experimental data. These devices provide evidence for next generation RF components that are 5 orders in magnitude smaller than the current state of the art.
AlN Lamb wave devices are modeled, fabricated, and tested. Results show successful parametric mixing in the devices at both an up converted frequency and down converted frequency. The output power of the mixed signal is linearly dependent on the carrier power until gain compression is reached. A circuit model developed closely matches the experimental data. These devices provide evidence for next generation RF components that are 5 orders in magnitude smaller than the current state of the art.
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Presenters
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Joseph Schneider
University of California, Los Angeles
Authors
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Joseph Schneider
University of California, Los Angeles
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Ting Lu
University of California, Los Angeles
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Sidhant Tiwari
University of California, Los Angeles
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Xiating Zou
University of California, Los Angeles
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Ajit Mal
University of California, Los Angeles
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Robert Candler
University of California, Los Angeles
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Yuanxun Ethan Wang
University of California, Los Angeles
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Greg P Carman
University of California, Los Angeles