The overall goal of this study is to develop thickness shear mode (TSM) resonators for the real-time, label-free, non-destructive sensing of biological adhesion events in small populations (hundreds) of neurons, in a cell culture medium and subsequently in vivo in the future. Such measurements will enable the discovery of the role of biomechanical events in neuronal function and dysfunction. Conventional TSM resonators have been used for chemical sensing and biosensing applications in media, with hundreds of thousands of cells in culture. However, the sensitivity and spatial resolution of conventional TSM devices need to be further enhanced for sensing smaller cell populations or molecules of interest. In this report, we focus on key challenges such as eliminating inharmonics in solution and maximizing Q-factor while simultaneously miniaturizing the active sensing (electrode) area to make them suitable for small populations of cells. We used theoretical expressions for sensitivity and electrode area of TSM sensors operating in liquid. As a validation of the above design effort, we fabricated prototype TSM sensors with resonant frequencies of 42, 47, 75, and 90 MHz and characterized their performance in liquid using electrode diameters of 150, 200, 400, 800, and 1,200 μm and electrode thicknesses of 33 and 230 nm. We validated a candidate TSM resonator with the highest sensitivity and Q-factor for real-time monitoring of the adhesion of cortical neurons. We reduced the size of the sensing area to 150-400 μm for TSM devices, improving the spatial resolution by monitoring few 100-1,000s of neurons. Finally, we modified the electrode surface with single-walled carbon nanotubes (SWCNT) to further enhance adhesion and sensitivity of the TSM sensor to adhering neurons (Marx, 2003). ,
CITATION STYLE
Khraiche, M. L., Rogul, J., & Muthuswamy, J. (2019). Design and development of microscale thickness shear mode (TSM) resonators for sensing neuronal adhesion. Frontiers in Neuroscience, 13(JUN). https://doi.org/10.3389/fnins.2019.00518
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