We demonstrate an ultra-high-bandwidth Mach-Zehnder electro-optic modulator (EOM), based on foundry-fabricated silicon (Si) photonics, made using conventional lithography and wafer-scale fabrication, oxide-bonded at 200C to a lithium niobate (LN) thin film. Our design integrates silicon photonics light input/output and optical components, such as directional couplers and low-radius bends. No etching or patterning of the thin film LN is required. This hybrid Si-LN MZM achieves beyond 106 GHz 3-dB electrical modulation bandwidth, the highest of any silicon photonic or lithium niobate (phase) modulator.
Piezoelectric energy microgenerators are devices that generate continuously electricity when they are subjected to varying mechanical strain due to e.g. ambient vibrations. This paper presents the mathematical analysis, modelling and validation of a miniaturized piezoelectric energy harvester based on ambient random vibrations. Aluminium nitride as piezoelectric material is arranged between two electrodes. The device design includes a silicon cantilever on which AlN film is deposited and which features a seismic mass at the end of the cantilever. EulerBernoulli energy approach and Hamilton's principle are applied for device modeling and analysis of the operation of the device at various acceleration values. The model shows good agreement with the experimental findings, thus giving confidence into model. Both mechanical and electrical characteristics are considered and compared with the experimental data, and good agreement is obtained. The developed analytical model can be applied for the design of piezoelectric microgenerators with enhanced performance.
List of symbolsL Length of cantilever beam (m) B Width of cantilever beam (m) H Thickness of structural layer (m) T Thickness of piezoelectric layer (m) V Voltage across piezoelectric element (m) Z Coordinate parallel to beam thickness (m) X Coordinate parallel to beam length or axial coordinate (m) T k Kinetic energy (J) U Internal energy (J) W e Electrical work (J) W External work (J) q s Density of structural layer (kg m -3 ) q p Density of piezoelectric layer (kg m -3 ) U Displacement (M) S Applied strain (None) T Developed stress (Pa) EElectric field (V m -1 ) DElectric displacement (C m -2 ) dV s Differential volume of structural layer (m 3 ) dV p
Piezoelectric energy microgenerators are devices that continuously generate electricity when they are subjected to varying mechanical strain due to vibrations. They can generate electrical power up to 100 µW which can be used to drive various sensing and actuating MEMS devices. Today, piezoelectric energy harvesters are considered autonomous and reliable energy sources to actuate low power microdevices such as wireless sensor networks, indoor-outdoor monitoring, facility management and biomedical applications. The advantages of piezoelectric energy harvesters including high power density, moderate output power and CMOS compatible fabrication in particular with aluminum nitride (AlN) have fuelled and motivated researchers to develop MEMS based energy harvesters. Recently, the use of AlN as a piezoelectric material has increased fabrication compatibility, enabling the realization of smart integrated systems on chip which include sensors, actuators and energy storage. Piezoelectric MEMS energy microgenerator is used to capture and transform the available ambient mechanical vibrations into usable electric energy via resonant coupling in the thin film piezoelectric material. Analysis and modeling of piezoelectric energy generators are very important aspects for improved performance. Aluminum nitride as the piezoelectric material is sandwiched between two electrodes. The device design includes a silicon cantilever on which the AlN film is deposited and which features a seismic mass at the end of the cantilever. Beam theory and lumped modeling with circuit elements are applied for modeling and analysis of the device operation at various acceleration values. The model shows good agreement with the experimental findings, thus giving confidence in the model.
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