Abstract

In this thesis, a novel scanning micromirror is introduced in which a thin layer of lithium niobate (few micrometer thick) is utilized as both as the structural material and the actuating piezoelectric medium. In this novel monolithic design, the conventional composite torsional hinges are avoided. The finite element simulations performed and reported in here indicate that the proposed design offers a superior performance in terms of higher scan angle and linear angle control compared to the existing solutions for the same dimensions. The simulation results predict an optical scan angle of 125.6° at a resonant frequency of 550 Hz using a driving voltage of 10V under an assumed Quality factor (Q=70). An inexpensive miniaturized 3D imager is the key component which ensures safe and reliable driving and enables the mass production of self-driving vehicles of the future. Light detection and ranging (LIDAR) technology– the current standard of 3D imaging- has already proven to be invaluable for development of the concept self-driving cars. However, in its current form, it doesn't meet all the requirements of large scale industrialization. Hence, there has been a growing demand for a miniaturized LIDAR system, which is the broad focus of this thesis. Micro-electro-mechanical-systems (MEMS-) based micromirrors are considered as one of the potential technologies for miniaturization of the LIDAR. The electrostatic, electromagnetic and piezoelectric principles are the commonly used actuation techniques in MEMS. Due to its considerable benefits such as high efficiency, low actuation voltage, miniaturization, and linearity, piezoelectric actuation is the optimum choice for this objective. In this work, it is postulated that thin film single crystalline lithium-niobate is a promising candidate for implementation of the scanning micromirrors not only for its high electromechanical efficiency, but also for the unique piezoelectric properties which enables rotary actuation in a monolithic layer.

Notes

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Graduation Date

2020

Semester

Fall

Advisor

Abdolvand, Reza

Degree

Master of Science in Electrical Engineering (M.S.E.E.)

College

College of Engineering and Computer Science

Department

Electrical and Computer Engineering

Degree Program

Electrical Engineering

Format

application/pdf

Identifier

CFE0008788;DP0025519

URL

https://purls.library.ucf.edu/go/DP0025519

Language

English

Release Date

June 2021

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

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