The proposed research is aimed at advancing resonant microelectromechancal (MEMS) mass sensors such as those used for detecting specific chemical or biological agents. Two investigative themes are proposed: (1) mass sensors utilizing array-type detection single-input-single-output device configurations which is simpler than existing array-based approaches and would allow designer to minimize on-chip electronics, and (2) mass detection using parametrically resonance sensors. Methods will be developed for assessing sensor metrics for performance comparison with traditional resonance-based mass sensors. Nano scaled material modeling and assembly for synthesis and performance enhancement will be investigated. The development and simple single-input-simple-output design would allow minimization of on-chip electronics and enable packaging of the resonators in vacuum and enhancement of overall system performance and sensitivity.
This collaborative multi-disciplinary research between a theorist and experimentalist will advance the graduate education programs across the departmental and institutional boundaries, and address outreach at the junior high and high school levels through art, the internet, and interactive activities, all of which are enhanced by computational components.
The overarching goal of this collaborative project was to develop methods for improving the performance of micro-scale sensors that make use of mechanical vibration. These micro-electro-mechanical-system (MEMS) sensors have applications in inertial sensing, often used in guidance and navigation, and for the detection of chemical and biological agents. Such sensors rely on the measurement of highly sensitive changes in the vibration characteristics of the sensor device that occur due to variations in its environment. Fabrication technologies allow for the design of very small sensor devices of this type, which are appealing for a number of reasons, including, power usage, weight, and ease of integration with electronics. However, their small size also presents challenges, since the device signals are similarly small and more easily corrupted by noise and other factors. This project used fundamental physics and modern computational tools to model and design novel devices, and state-of-the-art fabrication and testing methods to build and evaluate micro-sensors designed to overcome many of these challenges, thereby offering improved performance of MEMS sensors. The collaborative project supported an ongoing partnership between research groups at Michigan State University (MSU), who specialize in the modeling, design, and analysis of MEMS devices, and the University of California-Santa Barbara (UCSB), whose expertise is in the design, fabrication, and testing of these systems. Student training was an important component of the project, contributing to its broader impacts. One PhD student at each institution completed their degrees during the project. These students worked closely together and each developed broad-based fundamental and practical knowledge relevant to MEMS design. One student is now employed at a MEMS company, while the other is continuing in academia, working as a postdoc at Carnegie Mellon University. In addition, two undergraduate students were involved in the project at MSU, supported by a Research Experience for Undergraduates (REU) supplement to the grant; these students graduated and are enrolled in PhD programs, one at the University of Notre Dame and the other at Carnegie Mellon University. Outreach was another important component contributing to the broader impacts of the project. Both the MSU and UCSB teams played a lead role in summer outreach programs throughout the duration of the project. These programs are aimed at talented middle and high school students, about 25% of whom are from groups underrepresented in engineering. These programs are designed to excite students about their prospects in engineering and MEMS applications were presented as example of cutting-edge technology where engineering is playing a vital role. The technical focus of the project was on the development of methods for improving the signal-to-noise performance and the robustness of MEMS sensors, that is, their ability to operate accurately in changing environmental conditions. Specific achievements included: the development of mathematical models that systematically account for parametric amplification, noise, and other relevant effects on device response; analysis of these models to predict system response and the manner in which it depends on device parameters; experimental demonstration of the use of parametric amplification to enhance the effective signal-to-noise ratio in multi-mode resonant sensors capable of detecting multiple agents using a single device output; development of methods for real-time control of micro-sensors and their application to a tunneling accelerometer; design and testing of a parametrically resonant angular rate (gyro) sensor that uses nonlinear response features to achieve robustness and a significantly higher signal-to-noise ratio when compared to traditional angular rate sensors; and development of methods for estimating device instabilities in the presence of noise, a fundamental study with relevance to a wide range of systems that utilize instability thresholds for sensing. In addition, the UCSB group has close connections with several MEMS industries and is actively seeking partners to develop fabrication and transduction methods that will help translate the results of this research into commercially viable products.
