Adaptive Bistable Circuitry Network With Piezoelectric Transducers for Bifurcation-Based Mass Measurement
Authors: Kim Jinki 
Published: February 2023

Abstract
Accurate measurement of microscale mass changes is crucial for various applications including toxic gas detection and medical diagnosis. Recent exploration in microelectromechanical systems (MEMS) has brought significant advancements in microscale sensing. Despite unprecedented sensing resolution, linear resonance-based MEMS sensors often require carefully controlled environment for operation due to unavoidable damping and noise. Nonlinear MEMS sensors exploiting large structural responses have shown enhanced robustness against noise and damping; yet, sophisticated preventative control is often required to extend their structural reliability. Recent investigations on nonlinear circuits and feedback controls have focused on detecting mass adsorption by indirectly introducing the essential nonlinearity.
To overcome these challenges, this research presents a novel amplitude-based strategy for microscale mass sensing using an array of adaptive bistable circuits. A hybrid linear and bistable system is devised which utilizes linear cantilever-based resonators integrated with an array of adaptive bistable circuits for quantifying micro-mass adsorption at the linear cantilever beam tip by monitoring sudden and drastic response changes (bifurcation) in the bistable circuit array. The structural response is reflected into the piezoelectric voltage which is provided as an input to the bistable circuit array through the electromechanical coupling of piezoelectric transducer. The input amplitude is adjusted to be near the bifurcation thresholds of the bistable circuits, which are adaptively tuned by the gain of each circuits. The thresholds are distributed by four standard deviations of the bifurcation distribution, which determines the theoretical minimum sensing resolution with 95% probability given ambient noise level. The output levels of each circuit are evaluated whether they exhibit unmistakably different intra- or interwell responses that depend on the minute input voltage variations induced by mass adsorption. By comparing the array of results between the initial and mass-adsorbed states, we could accurately quantify the input amplitude change that linearly corresponds to the adsorbed mass.
The proposed sensing approach utilizing bifurcation phenomena was verified by numerically simulating the integrated electromechanical system. A numerical case study under the presence of Gaussian white noise with 28 dB SNR is performed demonstrating that the proposed bifurcation-based approach shows 300% enhanced resolution compared to the conventional peak detection method. Experimental investigations conducted on a mesoscale proof-of-concept platform also verify the enhanced performance of the proposed approach. The proposed approach yields an added mass ratio of 9.8e−4, which shows more than 700% enhancement compared to that of the prior bifurcation-based detection results. Overall, numerical and experimental results verify that the proposed approach provides remarkably enhanced resolution compared to prior advancements, and suggest that the proposed strategy holds promise for various applications such as low-cost diagnostics and structural health monitoring, which require precise and accurate measurement. Future work will focus on applying the enhanced sensing capability of proposed strategy to linear MEMS resonators which are expected to yield higher resonance frequency and baseline mass sensitivity, for enhancing various applications in medical diagnosis, public health, and safety.