Liwei Lin (Advisor)

The geometric designs of MEMS devices can profoundly impact their physical properties and eventual performances. However, it is challenging for researchers to rationally consider a large number of possible designs, as it would be very time- and resource-consuming to study all these cases using numerical simulation. In this paper, we report the use of deep learning techniques to accelerate the MEMS design cycle by quickly and accurately predicting the physical properties of numerous design candidates with vastly different geometric features. Design candidates are represented in a...

This paper presents an improved lumped element model for clamped, circular-shape, piezoelectric micromachined ultrasonic transducers (pMUTs). A small signal equivalent circuit is developed to include electrical, mechanical, and acoustic domains, which are analyzed separately and combined with the associated couplings. For the first time, a two-term mode shape approach is adapted to reveal intrinsic and extrinsic properties of a pMUT, such as equivalent circuit parameters, input impedance, velocity, displacement, bandwidth, quality factor, directivity, and the on-axis pressure in the...

Traditional Chinese medicine(TCM) has existed for more than two thousand years and one of the important diagnostic methods is the pulse diagnosis. It generally takes decades of training for a practitioner to master this skill as pulse acquisition and diagnosis require long-term experiences and are very subjective. The project aims to use the combination of advanced sensor technology and artificial intelligence to emulate the TCM practice for health monitoring. A flexible piezoelectric film is designed to record the wrist pulse data. A group of representative pulse features has been...