Document Type
Article
Publication Date
2023
Keywords
Motion Sensor, Triboelectric generator, MEMS, Accelerometer, Inertial Measurement
Abstract
Two solutions for improving MEMS triboelectric vibration sensors performance in contact-separation mode are reported experimen- tally and analytically. Triboelectric sensors have mostly been studied in the mesoscale. The gap variation between the electrodes induces a potential difference that represents the external vibration. Miniaturizing the device limits the sensor output because of the limited gap. This work offers a warped MEMS diaphragm constrained on its edges. The dome-shaped structure provides one order of magnitude larger displacement after contact-separation than standard designs resulting in one order of magnitude greater volt- age and signal-to-noise-ratio. Secondly, micro triboelectric sensors do not operate unless the external vibration is sufficiently forceful to initiate contact between layers. The proposed constraints on the edge of the diaphragm provide friction during periodic motion and generate charges. The combination of the warped diaphragm and boundary constraints instead of serpentine springs increases the charge density and voltage generation. The mechanical properties and electrical output are thoroughly investigated including nonlinearity, sensitivity, and signal-to-noise ratio. Sensitivity of 250 mV/g and signal-to-noise-ratio of 32 dB is provided by the pre- sented device at resonance which is very promising for event-driven motion sensors because it does not require signal conditioning and therefore simplifies the sensing circuitry.
Publisher Attribution
This accepted manuscript is published in Small, an imprint under Wiley-VCH Verlag.
This is the peer reviewed version of the following article: High Signal-To-Noise Ratio Event-Driven MEMS Motion Sensing, which has been published in final form at 10.1002/smll.202304591. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
Recommended Citation
Mousavi, Mohammad; Alzgool, Mohammad; Davaji, Benyamin; and Towfighian, Shahrzad, "High Signal-To-Noise Ratio Event-Driven MEMS Motion Sensing" (2023). Mechanical Engineering Faculty Scholarship. 46.
https://orb.binghamton.edu/mechanical_fac/46
Comments
The authors would like to acknowledge the financial support of this study by National Science Founda- tion (NSF) through Grant 1919608. This work was performed in part at the Cornell NanoScale Science & Technology Facility, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the National Science Foundation (Grant NNCI-2025233).