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bioRxiv · 10.1101/2024.12.26.630366

Wafer-scale integration of alpha-quartz thin films towards super high frequency piezoelectric bioNEMS for arbovirus detection

Rathar, R.·Sanchez-Fuentes, D.·Ding, S.·Jolly, C.·Andre, C.·Desgarceaux, R.·Garcia, R.·Gazquez, J.·Plana, S.·Picas, L.·Carretero, A.
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Abstract

Micro and nanoelectromechanical systems (MEMS/NEMS), especially piezoelectric resonators, offer a promising strategy for the manufacturing of point-of-care devices providing rapid, sensitive, and field-deployable tests with minimal user training for the diagnostic of viral infections. High-frequency (HF) MEMS/NEMS have the potential for ultrasensible mass-loading devices. Yet, their use for biomedical applications requires challenging manufacturing qualities. Here, we develop a large-scale chemical integration of epitaxial -quartz (100) thin films on silicon wafers up to 4-inches. This methodology allows the microfabrication of wafer-scale piezoelectric -quartz/silicon bioMEMS using a recognition layer capable of selectively detecting emerging arboviruses over other viral loads. Using contact-free vibrometry, we show a mass sensitivity of the bioMEMS device of 22.4 pg/Hz in liquid conditions and a Chikungunya virus limit of detection of 9 ng/ml. To reach piezoelectric transduction for compact quartz sensor devices, we develop NEMS resonators at super HF, i.e., 17.8 GHz with a quality factor of 280 which represents a QxF product of 4.98{middle dot}1012. These -quartz NEMS can reach thicknesses between 100 and 800 nm and lateral dimensions up to 9 mm2. Our work opens the door for cost-efficient single-chip epitaxial piezoelectric -quartz/Si ultrasensitive NEMS sensors manufactured exclusively by soft-chemistry for biomedical applications and many other fields.

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Rathar, R., Sanchez-Fuentes, D., Ding, S., Jolly, C., Andre, C., Desgarceaux, R., Garcia, R., Gazquez, J., Plana, S., Picas, L., Carretero, A.. 2024-12-26. Wafer-scale integration of alpha-quartz thin films towards super high frequency piezoelectric bioNEMS for arbovirus detection. https://doi.org/10.1101/2024.12.26.630366

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