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

BPN876: Metal-Organic Frameworks for Chemical Sensing with High Selectivity

Alireza Pourghaderi
Jihoon Chung
Isaac Zakaria
2022

A classic challenge in gas sensing is the tunability of the sensing material for the selective absorption of target gases without interference from unwanted species. Metal-organic frameworks (MOFs), made up of metal-cluster nodes connected by organic linkers, can achieve selective adsorption owing to their high chemical and structural tunability. Their selectivity and flexibility make MOFs attractive for gas sensing, as realized in novel low-power, low-footprint, on-chip devices such as the chemical-sensitive field-effect transistor, previously demonstrated by our group. In this...

BPN743: Highly Responsive pMUTs

Yande Peng
Sedat Pala
Fan Xia
2022

Ultrasonics has been realized as a nondestructive measurement method for a variety of applications, such as medical imaging, healthcare monitoring, structural testing, range finding, and motion sensing. Furthermore, high intensity ultrasound can be used in therapeutic treatments, such as lithotripsy for kidney stone comminution, hyperthermia for cancer therapy, high-intensity focused ultrasound (HIFU) for laparoscopic surgery and transcranial sonothrombolysis for brain stroke treatment. MEMS ultrasonic transducers are known to have several pronounced advantages over the conventional...

BPN735: Walking Silicon Microrobots

Alexander Alvara
2022

This project focuses on developing a new generation of sub-centimeter MEMS-based walking robots. These robots are based on electrostatic actuators driving planar silicon linkages, all fabricated in the device layer of a silicon-on-insulator (SOI) wafer. By using electrostatic actuation, these legs have the advantage of being low power compared to other microrobot leg designs. This is key to granting the robot autonomy through low-power energy harvesting. The ultimate goal will be to join these silicon legs with a CMOS brain, battery power, a high voltage power source, and high...

BPN974: Lidar-Camera Fusion for Autonomous Driving

Philip L. Jacobson
2022

Within the past few decades, the goal of fully-autonomous vehicles has moved from a thought experiment to a potential reality thanks to advances in machine intelligence. One of the key challenges to still be overcome is the building of robotic perception systems which can achieve performance on-par with or surpassing that of humans. Currently, most autonomous driving researchers rely on several different modalities for collecting visual information, namely lidar, radar, and cameras. Although relying on lidar for perception has the drawback of high cost, maturing lidar technology has opened...

Customizing MEMS Designs via Conditional Generative Adversarial Networks

Fanping Sui
Ruiqi Guo
Wei Yue
Kamyar Behrouzi
Liwei Lin
2021

We present a novel systematic MEMS structure design approach based on a “deep conditional generative model”. Utilizing the conditional generative adversarial network (CGAN) on a case study of circular-shaped MEMS resonators, three major advancements have been demonstrated: 1) a high-throughput vectorized MEMS design generation scheme that satisfies the geometric constraints; 2) MEMS structural customization toward tunable, desired physical properties with excellent generation accuracy; and 3) experience-free design space explorations to achieve extreme physical properties, such as...

Designing Weakly Coupled MEMS Resonators with Machine Learning-Based Method

Fanping Sui
Wei Yue
Ruiqi Guo
Kamyar Behrouzi
Liwei Lin
2021

We demonstrate a design scheme for weakly coupled resonators (WCRs) by integrating the supervised learning (SL) with the genetic algorithm (GA). In this work, three distinctive achievements have been accomplished: 1) the precise prediction of coupling characteristics of WCRs with an accuracy of 98.7% via SL; 2) the stepwise evolutionary optimization of WCR geometries while maintaining their geometric connectivity via GA; and 3) the highly efficient generation of WCR designs with a mean coupling factor down to 0.0056, which outperforms 98% of random designs. The coupling behavior analysis...

BPN973: Functionalized-Carbon Reinforced Concrete Towards Low-Carbon Intensity Hydrogen Fuel and Smart Concrete

Stuart McElhany
2022

Global usage of concrete has tripled in the last 40 years, and continues to grow rapidly, placing immense pressure on the environment while requiring its use for safe and effective infrastructure. Concrete accounts for roughly 10% of worldwide CO2 emissions annually. A promising method for directly reducing the CO2 emissions associated with concrete is through replacement of cement, the primary binding material in concrete, with a percentage of carbon, creating so called carbon-incorporated cement composites (CCC). Carbon may be sourced from the waste...

BPN913: Enhanced MOF-Enabled Colorimetric CO2 Sensing Through Dye-Precursor Synthesis

Adrian K. Davey
2022

Carbon dioxide (CO2) has been linked to various human health symptoms indoors, such as nasal and optic irritation. Toward an optimal indoor air sensor, our group has developed two generations of ultralow-power, passive, rapid colorimetric CO2 sensors based on (a) a highly-porous metal-organic framework, ZIF-8; (b) a pH indicator, phenol red (PSP); and (c) a CO2-affinative group, ethylenediamine (ED). The first sensor, PSP-ED/ZIF-8, is composed of pristine ZIF-8 mixed with PSP and ED. The second sensor, ED/PSP:ZIF-8, is produced from directly mixing PSP with the ZIF-8 methanolic precursor...

BSAC's Best: Fall 2020 Oral Presentation Winners Announced

September 24, 2020

BSAC would like to thank all of the researchers who presented their research during BSAC's Fall 2020 Research Review, September 21-23.

BSAC Industrial Members voted for their favorite oral presentations and the results are in. Please join us in congratulating the winners of the Fall 2020 Best of BSAC honors, Mallika Bariya and Daniel Teal!

...

BPN922: Analog Optical Voltage Sensor

Jordan L. Edmunds
Soner Sonmezoglu
2021

Distributed sensors are becoming ubiquitous in manufacturing, automotive, and consumer applications. One extremely common need at the core of many of these sensors is the requirement to sense small voltages (uV-mV scale), amplify, digitize, and then communicate those bits so they can be acted on. We are taking a different approach - by utilizing nonlinear optical materials, we plan to transduce these signals directly into reflected light, removing the need for complex and high-cost sensor-side circuitry. Since the mechanism is purely passive and does not require a continuous power...