Physical Sensors & Devices

Research that includes:

  • Silicon MEMS actuators: comb, electro-thermal, and plastic deformation
  • Precision electronic sensing and measurements of capacitive, frequency, and coulombic MEMS variables
  • Structures and architectures for gyroscopes, accelerometers, micro strain gauges for direct application to rigid structures e.g., steel, and levitated MEMS

Automatic Network-Based Multi-Channel Frequency Calibration for Self-Joining Crystal-Free Motes

Titan Yuan
Filip Maksimovic
Tengfei Chang
Kristofer S. J. Pister
2026

Crystal-free transceivers offer a highly integrated, miniaturized, and power-efficient solution for IoT networks. However, without any time and frequency reference, they need to calibrate their freerunning oscillators, especially their RF oscillator, before they are interoperable with other IoT devices. To join wireless sensor networks that implement a time-synchronized channel-hopping (TSCH) protocol based on the IEEE 802.15.4 physical layer, crystal-free radios have to find the correct frequency tuning settings for all sixteen channels in the 2.4GHz ISM band. We propose an automatic,...

BPNX1067: High-Efficiency Impedance Transformers for Microwave-to-Optical Quantum Transducers

Ahmet Oguz Sakin
Nicholas Yama
Tae Gyu Ahn
2026

We are developing high-efficiency microwave impedance transformers for microwave-to-optical quantum transducers. Our goal is to match a standard 50 Ω microwave environment to a novel high-impedance electro-optic (EO) device based on a 20 kΩ thin-film lithium niobate (TFLN) traveling-wave modulator. The high impedance increases the microwave field in the EO device and improves the overall transduction efficiency. We will use a Klopfenstein taper design, as it provides low reflection with a compact length over a broad bandwidth. We target 4–8 GHz operation and near-unity coupling to the 20...

BPNX1073: Cryogenic CMOS-based Control and Readout of Electrons in Paul Traps

Andris Huang
Nikhil Jain
Izze Sacksteder
Baiyi Yu
Hartmut Haeffner
2026

The electron in Paul trap system has been recently proposed as a candidate for qubits in quantum information processing. In such a system, floating electrons are confined in vacuum using oscillating electric fields. Feasibility studies and experimental trapping at room temperature have shown that electrons satisfy all DiVincenzo's criteria, a common standard used to determine whether a system can be a good candidate to perform quantum computation. More importantly, electrons have several advantages in quantum information processing as compared to trapped ions. Electrons are spin-½...

BPNX1069: Programmable Self-Assembly of Microparticles

Umut Can Yener
Declan M. Fitzgerald
Mostafa Sedky
Huicong Deng
2026

Piezoelectric micromachined ultrasonic transducer (PMUT) arrays provide a compact and scalable platform for synthesizing programmable acoustic pressure fields. In this project, we investigate PMUT-enabled programmable microparticle self-assembly in fluidic environments using dynamically controlled ultrasonic standing waves. Unlike conventional cymatics, which relies on fixed vibrational modes of a single acoustic source, individually addressable PMUT elements enable active control of frequency, phase, and amplitude to generate reconfigurable pressure landscapes. By tailoring...

BPNX1068: Corrosion-Resistant Encapsulation for Long-Term Stable Silicon MEMS Resonators

Kyuho Lee
Xintian Liu
Neil Chen
Shiwoo Lee
Kathy Doan
2026

Long-term frequency stability of silicon MEMS resonators is fundamentally limited by surface-driven degradation mechanisms, including corrosion, moisture adsorption, surface oxidation, and defect evolution. These processes progressively alter surface energy, mass, stiffness, and internal stress, leading to frequency drift, Q degradation, and reduced device lifetime. This work presents a corrosion-resistant encapsulation strategy that conformally coats silicon resonator surfaces with a chemically robust, high-hardness barrier layer engineered for long-term environmental stability. The...

BPNX1061: 3D Imaging Using PMUTs

Nikita Lukhanin
Ziv Behar
Ashkay Shivkumar
Divij Muthu
Alice Wu
Ameer Hamzah
Umut Can Yener
Mostafa Sedky
Megan Teng
Tofic Esses
Linda Liu
Suraj Chamakura
Ryan Johnson
Chun-Ming Chen
2026

We have used PMUTs for 3D imaging using air based arrays with a computational imaging scheme. This project advances the ultrasound-based imaging techniques by using the compressed sensing scheme. The goal is to achieve 3D imaging with a low number of transducers and minimum computation for various applications in robotics, wearable electronics, autonomous navigation, and medical diagnostics.

Project is currently funded by: Member Fees

BPNX1057: Micromechanical Resonator Aging Rate Reduction

Neil Chen
Kathy Doan
Shiwoo Lee
Xintian Liu
Kevin H. Zheng
2026

This project aims to demonstrate superior aging-resistance for micromechanical resonators via methods that remove or immobilize defects and other non-idealities towards a lower material energy state. One such method to be explored is localized annealing, whereby fast, high-temperature Joule heating at the micron scale provides a method for tailoring the morphology of a resonator's structural material.

Project is currently funded by: Federal

BPNX1052: Piezoelectric MEMS Programmable Photonic Integrated Circuits

Huicong Deng
Sirui Tang
Yiyang Zhi
Yasuhiro Aida
Masakazu Fukumitsu
Arkadev Roy
Akira Konno
Daniel Klawson
Liwei Lin
2026

Integrated silicon photonic switches are becoming increasingly important for next-generation computing and communication infrastructure, with emerging applications in pluggable optics, co-packaged optics (CPO), and optical switching systems. Our group has previously developed MEMS-based photonic switches that enable large-scale integration, broad optical bandwidth, and low insertion loss. However, conventional electrostatic MEMS actuation typically requires relatively high driving voltages (>30V), limiting compatibility with standard electronic control architectures.

In this...

BPNX1036: Enhanced Gas Sensing with Machine Learning

Yuan Gao
Wei Yue
2026

Accurate, real-time gas detection is crucial for applications from environmental monitoring to industrial processes, yet sensors are limited by low accuracy, slow response, and drift — the same gas reads differently months later. This project develops scalable machine learning for both problems. Encoder–decoder architectures and a decision-fusion model consolidate the strengths of multiple carbon dioxide sensors into a single virtual sensor, achieving a mean absolute percentage error (MAPE) of 2.97% while reducing response and recovery times from approximately 9 minutes to 2 minutes. A...

BPNX1035: Six-Axis Control of Electrostatically Levitated Mass

Yichen Liu
Daniel Lovell
Lawrence Rhee
Jacob Kwon
Damanic Luck
Emily Tan
Alexander Alvara
Hani Gomez
Daniel Teal
2026

This project focuses on the design, fabrication, and development of a six-axis electrostatically levitated mass system. While electrostatic levitation has been previously demonstrated, the emphasis here is on achieving a compact form factor (10 cm × 10 cm), reduced power consumption (0.5 W), and increased levitated mass capacity. The proof mass is suspended using a system of actuation electrodes: four top electrodes provide levitation and control of vertical displacement (z-axis) as well as rotation about the x- and y-axes, while six side electrodes control lateral motion (x- and y-...