Justin Kuo Thesis

MEMS GHZ SONAR FOR THROUGH SILICON COMMUNICATIONS AND SENSING APPLICATIONS A Dissertation Presented to the Faculty of the Graduate School of Cornell University In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Justin C. Kuo August 2018 © 2018 Justin C. Kuo MEMS GHZ SONAR FOR THROUGH SILICON COMMUNICATIONS AND SENSING APPLICATIONS Justin C. Kuo, Ph. D. Cornell University 2018 This dissertation presents work on using the GHz sonar transducer, a new type of MEMS (microelectromechanical systems) bulk acoustic wave (BAW) technology, for communications and sensing applications. As these devices are fabricated with aluminum nitride (AlN), a CMOS-compatible piezoelectric thin film material, these devices can be integrated directly with CMOS circuits to allow for new circuit functionalities. The structure and fabrication details of GHz sonar transducers are introduced, followed by a discussion of how to model the devices. There are two primary effects that will be discussed – the electrical to acoustic conversion of the piezoelectric thin film transducers and how diffraction affects wave propagation from the transducers through the silicon substrate. In this work, three new applications enabled by the GHz sonar transducer will be discussed. The first is the GHz ultrasonic through-silicon via (UTSV), a new type of wireless 3D interconnect that enables chip-to-chip communication in multi-chip 3D integrated circuit (3DIC) stacks. The second application is the GHz sonic memory – a delay line memory that uses the UTSV as an ultrasonic delay line and stores digital bits as ultrasonic waves. The novelty of this memory is that it transforms the previously unused silicon substrate into 3D memory elements, as opposed to the traditional method of increasing memory density by stacking 2D memory chips. The third application is the GHz ultrasonic fingerprint sensor, a new CMOS compatible fingerprint sensor. The use of ultrasound allows for numerous advantages over current capacitive and optical fingerprint sensors, including higher penetration through glass and metal layers, as well as enhancing the spoof resistance of the fingerprint sensor by allowing the sensor to image elastic properties of tissue. The 1.3 GHz frequency of the sensor potentially allows for two orders of magnitude higher resolution over existing ultrasonic fingerprint sensors, which typically operate at biomedical ultrasound frequencies of tens of MHz. BIOGRAPHICAL SKETCH Justin Kuo was born in 1990 in Staten Island, New York to Ken (Chen-Chih) and Amy (Yumei) Kuo. He spent his early childhood in Staten Island, the “forgotten borough” of New York City, before moving to Tainan, Taiwan in 2001 for intermediate school. He returned to New York City in 2004 for high school, attending the Science Institute program at Tottenville High School in Staten Island. In 2008, he started college at Cornell University, majoring in Electrical and Computer Engineering. In the summer after his sophomore year, he started working with Prof. Amit Lal on an undergraduate research project on electronic backpacks for flight control of Manduca sexta moths for the Hybrid Insect MEMS program. Other research projects included work on designing control circuits for a MEMS ultrasonic neural probe and wireless controlled mirrors for concentrated solar power. In 2012, he decided he wanted to continue doing research on MEMS and started his PhD at Cornell University in the SonicMEMS Laboratory under the guidance of Prof. Amit Lal. His doctoral research focuses on GHz chip-scale sonar, a novel MEMS technology developed at the SonicMEMS Laboratory at Cornell, and its applications for 3D chip-to-chip communication and fingerprint sensing. v ACKNOWLEDGMENTS The successful completion of my thesis work has only been possible through the help of numerous people. Most important of all, I would like to express my gratitude to my advisor, Prof. Amit Lal, for his guidance and inspiration. In particular, I would like to acknowledge his boundless creativity, which enables his research group to push the boundaries of current research, and his optimism, guided by his excellent intuition, which has proven to be correct over my pragmatic skepticism countless times throughout my graduate work. While the plethora of last minute deadlines, particularly for CMOS tape-outs and conference publications and talks, within his group have caused me great stress and consternation at times, I can say for certain that, by working under Amit’s tutelage, I have learned and accomplished a lot that would not have been possible in any other research group and the personal growth I have obtained through this experience has made me a much better person, researcher, and electrical engineer. I would also like to acknowledge the rest of the members of SonicMEMS – the graduate students and the postdoctoral researchers who have contributed to making the lab an extremely friendly and pleasant working environment and all of whom have taught me many things – Visarute “Earth” Pinrod, Alex Ruyack, June-Ho Hwang, Vinaya Kumar, Benyamin Davaji, Ved Gund, Sachin Nadig, Janet Shen, Steven Tin, Yue Shi, Kwame Amponsah, Hadi Hosseinzadegan, Larry Yuerui Lu, Sarvani Piratla, Siva Pulla, Leanna Pancoast, Di Ni, Tiffany St. Bernard, and Nabil Shalabi. Special thanks goes to the graduate students and postdocs on whom I have worked on the TIC project for making it such a success – Serhan Ardanuc, Po-Cheng Chen, Mamdouh Abdelmejeed, Adarsh Ravi, Jessica Yutong Liu, and especially to Jason Hoople. Without the solid foundation that Jason has built for the GHz AlN silicon sonar, I would not have been able to accomplish as much as I did during my PhD work. I vi would also like to thank the following ECE graduate students for their help in circuit design and MEMS fabrication and testing – Sunwoo Lee, Changhyuk Lee, Suren Jayasuriya, Robert Karmazin, and Tanay Gosavi. In addition, I would like to thank my committee members – Prof. Al Molnar and Prof. Cliff Pollock for their support and assistance throughout my graduate work. I would also like to thank Sue Bulkley, Daniel Richter, Scott Coldren, and Patricia Gonyea for their help on the various administrative tasks I have encountered throughout my time at Cornell. For fabrication of the devices I used in my graduate work, I would like to thank Navab Singh, Jeffrey Soon Bo Woon, Merugu Srinivas, and Sharma Jaibir at A*STAR Institute of Microelectronics (IME), Troy Olsson and Ben Griffiths from Sandia National Laboratories, Ron Polcawich from Army Research Laboratory, and all of the staff at the Cornell Nanoscale Science and Technology Facility (CNF). For funding of the projects I worked on, I would like to thank Dr. Dennis Polla and Dr. Carl McCants, the program managers of the IARPA Trusted Integrated Chips (TIC) program, Dr. Vincent Tang from DARPA who was the program manager for the SonicFFT project, and Dr. Mohamed Abdel-moneum at Intel for the GHz ultrasonic fingerprint reader project. Finally, I would like to thank my family members – my father and mother and my sisters, Tiffany and Jocelyn – for their support over the many years. Without the influence of my father I would have never thought of doing a PhD. vii TABLE OF CONTENTS Chapter 1: Introduction ............................................................................................. 1 1.1 More-Than-Moore .................................................................................. 1 1.2 Hardware Security Motivations for MEMS GHz Chip-Scale Sonar ...... 3 1.3 Surface Micromachined MEMS BAW Devices ..................................... 6 1.4 Principle of Operation for MEMS GHz Chip-Scale Sonar .................... 10 1.5 GHz Ultrasonic Acoustic Microscopy .................................................... 16 1.6 Dissertation Scope .................................................................................. 18 Chapter 2: Transducer Thin Film Layer Stack Modeling ........................................ 20 2.1 Transducer Thin Film Layer Stack and Fabrication ............................... 20 2.2 KLM Modeling of Transducers .............................................................. 25 2.3 Controlled Source Model ....................................................................... 35 2.4 Analytical Equation for Estimating Transducer Acoustic Response ...... 38 Chapter 3: Wave Propagation Modeling and Characterization ................................ 50 3.1 Introduction to Elastic Waves ................................................................ 51 3.2 Green’s Function Method and the Rayleigh Integral ............................. 56 3.3 Radiation from Circular and Rectangular Transducers .......................... 61 3.4 Diffraction Loss and Crosstalk ............................................................... 71 3.5 Experimental Verification of Diffraction Models .................................. 79 Chapter 4: Excitation Waveforms for GHz Sonar Transducers ............................... 90 4.1 Single Tone Excitation with Sinusoidal RF Pulses ................................ 90 4.2 Driving GHz Sonar Transducers with Digital Waveforms .................... 92 Chapter 5: GHz Ultrasonic TSV and Memory ......................................................... 99 5.1 Introduction to 3D Interconnect Technology ......................................... 99 5.2 The Ultrasonic Through Silicon Via (UTSV) ........................................ 102 5.3 History of the Delay Line Memory .......................................................

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