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Design and implementation of mode localised resonant MEMS oscillators for gravimetric sensing

Authors :
Chellasivalingam, Malar
Seshia, Ashwin
Publication Year :
2021
Publisher :
University of Cambridge, 2021.

Abstract

In a spectrum ranging from a subatomic particle which is approximately 10^(-26) m, to the observable universe, which is of the order of 10^(26) m, airborne ultrafine particles have a diameter of less than 100nm. The adverse impact of these ultrafine airborne particles on human health has been the focus of numerous clinical studies, including respiratory and cardiovascular diseases. Empirical results of the clinical studies suggest that it is essential to map the emission sources of these ultrafine airborne particles to monitor and regulate them. Recognizing the cumbersome nature of the traditional optical methods and their inability to count individual particles below 100nm due to diffraction limit, new approaches are being researched for sensing these ultrafine particles. In recent decades, Richard Feynman's (1961) vision of building minuscule machines has been translated to a reality using Microelectromechanical Systems (MEMS) Technology. Integration of miniature electrical and mechanical components fabricated using integrated circuit batch processing techniques is achievable utilising MEMS Technology. As a result, MEMS devices have witnessed exponential growth over the last decade in various fields and have had a significant impact on the field of sensors and sensor systems. This thesis investigates the potential of mode localisation in MEMS devices for sensing ultrafine particles as an approach towards future sensor technologies for gravimetric sensing that could eventually be deployed as part of the emerging Internet-of-Things (IoT) paradigm. Furthermore, this thesis aims to examine the influence of "real-world" conditions during the field deployment of mode localised MEMS resonators for sensing ultrafine particles. In that regard, weakly coupled MEMS resonators utilising mode localisation have been proposed as an alternative to resonant frequency MEMS sensors due to their increased sensitivity and first-order common-mode rejection to variations in temperature. This thesis presents a number of contributions to the design of coupled MEMS resonators for sensing ultra-fine particles. Firstly, piezoelectrically transduced, coupled MEMS resonators are modelled by numerical simulations, including finite element simulations for modal analysis. Secondly, the coupled MEMS resonators are designed and fabricated using silicon-on-insulator (SOI) wafers via the PiezoMUMPs process offered by MEMSCAP, Inc. Thirdly, critical aspects of the MEMS mass sensors such as sensitivity, stability, and common-mode rejection are analysed through laboratory experiments. These experiments involve interfacing the MEMS element to a source of ultrafine particles and observing amplitude ratio as the output electrical signal. The ultrafine particles generated in the laboratory for this experimental execution include polystyrene latex nanoparticles and diesel soot nanoparticles. The results highlight the three orders of magnitude enhancement in relative mass sensitivity for mode-localised MEMS sensors over the resonant frequency shift-based approach. Notably, the resolution of the mode localised MEMS sensors is explored by implementing a single oscillator for the coupled MEMS resonators in the array. Following this, the coupled MEMS resonators are subjected to temperature variations to demonstrate their insensitivity to temperature. In addition, an investigation of the coupled MEMS sensor lifetime by depositing particles on both resonators to achieve mass balancing has been addressed. Finally, suggestions for future work are presented to optimise the accuracy of the mode localised MEMS sensors towards future miniaturisation and deployment as population-based exposure assessment tools.

Details

Language :
English
Database :
British Library EThOS
Publication Type :
Dissertation/ Thesis
Accession number :
edsble.852878
Document Type :
Electronic Thesis or Dissertation
Full Text :
https://doi.org/10.17863/CAM.83791