Tapered Beams in MEMS: A Symbolic Modeling Framework with Applications to Energy Harvesting

This book addresses important aspects of MEMS designs that are well established in engineering practice but rarely discussed in the standard textbooks. One such aspect is the ubiquitous use of tapered beams in the sensing and actuation elements of MEMS designs. As explained in this book, the tapered beam has distinct advantages over the standard rectangular beam but these advantages are often left unarticulated due to the blind trust in the finite-element models of MEMS devices. In this monograph, the authors take a fundamental, physics-based approach to the modeling of tapered beams in MEMS that is based on a rigorous perturbation analysis of the traditional Euler-Bernoulli beam. The authors demonstrate how perturbation methods combined with symbolic modeling and the tools of computer algebra enable the development of semi-analytical models for tapered-beam MEMS elements. They pay particular attention to the application of these novel models to piezoelectric MEMS energy harvesters with tapered-beam elements, including the development of lumped-parameter circuit models that can be readily used for fast electro-mechanical simulations. Another important aspect of MEMS designs that is extensively addressed in the book is the uncertainty quantification (UQ) of tapered-beam MEMS elements using both Monte Carlo and polynomial chaos expansion methods. These UQ methods are applied to the design of variation-aware piezoelectric energy harvesters. With consistent focus on MEMS devices with tapered beam elements, this up-to-date monograph

Table of Contents:
Introduction.- Piezoelectric MEMS Energy Harvesting: Introduction to Reliability and Uncertainty Quantification.- Review of Euler-Bernoulli Rectangular Beam Theory.- Tapered-Beam Piezoelectric MEMS Energy Harvesters.- Modal Analysis of Tapered-Beam Piezoelectric MEMS Energy Harvesters.- Lumped-Parameter Modeling of Tapered-Beam Piezoelectric MEMS Energy Harvesters.- Symbolic Modeling Framework of Tapered-Beam Piezoelectric MEMS Energy Harvesters.- Uncertainty Quantification of Tapered-Beam Piezoelectric MEMS Energy Harvesters Using Monte Carlo Methods.- Uncertainty Quantification of Tapered-Beam Piezoelectric MEMS Energy Harvesters Using Polynomial Chaos Expansion.- Variation-Aware Design of Reliable Piezoelectric MEMS Energy Harvesters.- Other Applications of Tapered Beams in MEMS and Opto-MEMS.

About the Author :
Wajih U. Syed serves as algorithms lead at Masimo Corporation in Irvine, CA , where he has been developing solutions for clinical monitoring, disease tracking, and early warning systems in healthcare since January 2019. Previously, he worked as a Post-Doctoral Fellow at Khalifa University from 2017 to 2018, contributing to the design and characterization of MEMS devices, including space-grade gyroscopes.  His research interests span mathematical modeling of multi-physics systems, MEMS modeling and design, and the development of medical instrumentation and AI-powered disease prediction solutions. He earned his Ph.D. from Khalifa University in June 2017. Ibrahim (Abe) M. Elfadel has been full Professor at Khalifa University, Abu Dhabi, United Arab Emirates, where he has been affiliated with various academic departments and  research centers since 2011. Prior to his current position, he was with IBM, Yorktown Heights, NY, for 15 years as Research Staff Member and Senior Scientist involved in the research, development, and deployment of VLSI CAD tools and methodologies for IBM's high-end microprocessors. Between 2012 and 2019, he led three Abu Dhabi-based, industrially funded research centers dedicated to IoT, 3D Integration, and MEMS. Dr. Elfadel is the recipient of six Invention Achievement Awards, one Outstanding Technical Achievement Award, and one Research Division Award, all from IBM, for his contributions to VLSI CAD. His other awards include the D. O. Pederson Best Paper Award from the IEEE Transactions on Computer-Aided Design (2014), the SRC Board of Directors Special Award for “pioneering semiconductor research in Abu Dhabi” (2018), the IFIP Service Award (2022), and the Khalifa University Service Excellence Award (2023).  Dr. Elfadel is the author of more than 170 refereed publications and the inventor of more than 50 issued US patents. His most recent book  is: “Secure, Low-power IoT Communication Using Edge-Coded Signaling,” Springer, 2022, co-authored with Dr. Shahzad Muzaffar from IMEC. Dr. Elfadel is an Associate Editor of the IEEE Transactions on Circuits and Systems for Artificial Intelligence and the IEEE Transactions on VLSI.  He is also the founding Editor in Chief of the SpringerNature series: “Synthesis Lectures on Circuits and Systems for Artificial Intelligence.” Dr. Elfadel has served on the technical program committees of several flagship conferences, including DAC, ICCAD, ASPDAC, DATE, ISCAS, AICAS, BioCAS, VLSI-SoC, ICCD, ICECS, and MWSCAS. He was the General Co-chair of VLSI-SoC 2017, and the Technical Program Co-chair of VLSI-SoC 2023 and AICAS 2023. He is the Technical Program Co-chair of BioCAS 2024 and  the Technical Program Chair of CloudCom2024. Dr. Elfadel received his PhD from MIT in 1993.