Iterative Analysis Approach using interactive Python-FEM to estimate the residual stresses in PMUTs

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Iterative Analysis Approach using interactive Python-FEM to estimate the residual stresses in PMUTs
Title:
Iterative Analysis Approach using interactive Python-FEM to estimate the residual stresses in PMUTs
Journal Title:
2023 IEEE SENSORS
Keywords:
Publication Date:
28 November 2023
Citation:
Ramegowda, P. C., Choong, D. S. W., Goh, D. J., Jihang, L., Merugu, S., Chang, P., Leotti, A., Giusti, D., Prelini, C., Ghosh, S., Lee, J. E.-Y., Koh, Y. (2023). Iterative Analysis Approach using interactive Python-FEM to estimate the residual stresses in PMUTs. 2023 IEEE SENSORS, 01–04. https://doi.org/10.1109/sensors56945.2023.10325091
Abstract:
Key performance metrics of Piezoelectric Micromachined Ultrasonic Transducers (PMUTs), such as resonance frequency (fr) and electromechanical coupling kt 2, are significantly impacted by the residual stress. In this study, we present an iterative analysis approach that utilizes interactive Python-FEM to estimate residual stress in PMUTs by integrating optical profile data with a finite element model (FEM) employing Newton-Raphson approximation. The proposed approach is validated using a known solution obtained from COMSOL simulation. We successfully applied this approach to estimate residual stress in three PZT PMUT samples fabricated in a Lab-in-Fab (LiF) facility. The estimated residual stresses are -171 MPa, -111 MPa, and -169 MPa indicate a compressive nature and align with the optical profile data. These values fall within the process condition range for the LiF physical vapor deposited (PVD) leadzirconate- titanate (PZT) PMUT process.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the Agency for Science, Technology and Research - Piezo Specialty Lab-in-a-Fab (LIF 1.0)
Grant Reference no. : I1901E0050
Description:
© 2023 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISSN:
1558-1748
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