Biosensing, crucial for healthcare, environmental monitoring, and various scientific fields, utilizes diverse transduction principles. Acoustic gravimetric biosensors, particularly attractive for point-of-care applications due to their simplicity and low cost, are often hampered by low Q-factors in liquid measurements, resulting from acoustic radiation energy loss and friction within the shear evanescent boundary layer. Previous attempts to enhance Q-factors through wave interference, isolation, and metamaterials have yielded limited success. This study presents a novel microfluidic approach to address this fundamental limitation by integrating microfluidic channels with a quartz crystal microbalance (QCM), a widely used and cost-effective TSM resonator. The hypothesis is that controlling the relationship between channel dimensions and acoustic wavelengths will significantly reduce dissipation, leading to a substantial increase in the Q-factor. The QCM serves as a model system due to its established applications and relevance to other acoustic sensors. The research combines simulations, theoretical studies, and experimental validation to demonstrate the effectiveness of this approach.

The introduction provides a comprehensive overview of biosensing technologies and the limitations of acoustic gravimetric sensors. It highlights the importance of the Q-factor in determining the sensitivity and accuracy of these sensors and reviews previous attempts to improve their performance by manipulating wave interference, sensor isolation, and metamaterials. The literature review implicitly emphasizes the novelty of the proposed microfluidic approach by demonstrating the inadequacy of previously explored methods in fully resolving the issue of low Q-factors in liquid environments.

The µ-QCM device design incorporates rigid microfluidic channels (2 µm × 10 µm) oriented perpendicular to the QCM crystal's shearing direction. The channel width (10 µm) is significantly smaller than the pressure wavelength (~42 µm in water at 35 MHz, the target operating frequency). Approximately 100 channels, spaced 20 µm apart, are centrally positioned on the sensor's active area. Capillary action drives liquid flow, with a diverging inlet system and wicking outlet design (inspired by tree-line capillary pumping) preventing bubble formation. Aluminum, chosen for its high modulus-to-density ratio, forms the microfluidic channels, with a conformal gold coating for surface modification. Finite element analysis (FEA) is used to model both conventional and µ-QCM behavior, considering factors like channel width-to-pressure wavelength ratio (W/λp) and channel height-to-shear evanescent wavelength ratio (H/λs). Experimental validation involves measuring frequency and dissipation shifts with DI water and ethanol-water mixtures. The original and extended Sauerbrey equations are used to analyze the data and assess the sensor's response to mass and viscosity changes. The mass resolution or Figure of Merit (FOM) is used to compare performance against the theoretical limit and existing literature.

Experimental results demonstrate a 10-fold decrease in dissipation shift (ΔD) in the µ-QCM compared to conventional QCM after admitting DI water. The µ-QCM exhibits a normalized resonance frequency shift five times larger than that of the conventional QCM, indicating greater liquid mass coupling despite significantly lower dissipation. FEA simulations accurately predict experimental results for conventional QCM and largely match µ-QCM results, particularly at higher modes. Parametric FEA studies confirm that the W/λp ratio is the most significant factor influencing dissipation, with low dissipation observed when this ratio is below 0.2. The µ-QCM shows a linear relationship between frequency shift and mass change, unaffected by viscosity variations as demonstrated using ethanol-water mixtures; unlike conventional QCM whose response depends on both viscosity and density. The µ-QCM significantly surpasses the theoretical FOM limit for conventional QCMs in liquid, demonstrating superior performance.

The findings directly address the research question by demonstrating the effectiveness of the microfluidic approach in significantly improving the Q-factor of acoustic gravimetric sensors. The 10-fold reduction in dissipation, coupled with enhanced mass sensitivity and independence from viscosity, represents a substantial advancement in gravimetric sensing technology. The results' relevance to the field lies in overcoming a long-standing limitation of acoustic biosensors, paving the way for more sensitive and accurate devices. The insights gained from FEA modeling provide valuable guidance for future designs, enabling optimization for various applications.

This research successfully demonstrates a new paradigm for in-liquid gravimetric sensing through the development of a microfluidic QCM. The µ-QCM achieves a 10-fold improvement in dissipation compared to conventional QCM, leading to superior mass sensitivity and independence from liquid viscosity. Future work could focus on integrating the µ-QCM with specific biosensing assays, exploring different microchannel geometries and materials, and extending the design principles to other types of acoustic sensors.

The FEA model, while effectively capturing the essential physics, exhibits minor discrepancies with experimental data at lower modes of the µ-QCM, possibly due to the simplified representation of the device and the liquid droplet at the inlet. Future refinements of the model could aim to account for these effects more accurately. Additionally, while the current design employs capillary action for liquid filling, alternative methods could be explored to improve control and prevent potential issues like bubble formation.