摘要
Acoustic gravimetric biosensors attract attention due to their simplicity,robustness,and low cost.However,a prevailing challenge in these sensors is dissipation which manifests in a low quality factor(Q-factor),which limits their sensitivity and accuracy.To mitigate dissipation of acoustic sensors in liquid environments we introduce an innovative approach in which we combine microfluidic channels with gravimetric sensors.To implement this novel paradigm we chose the quartz crystal microbalance(QCM)as our model system,owing to its wide applicability in biosensing and the relevance of its operating principles to other types of acoustic sensors.We postulate that the crucial determinant for enhancing performance lies in the ratio between the width of the microfluidic channels and the wavelength of the pressure wave generated by the oscillating channel side walls driven by the QCM.Our hypothesis is supported by finite element analysis(FEA)and dimensional studies,which revealed two key factors that affect device performance:(1)the ratio of the channel width to the pressure wavelength(W=λp)and(2)the ratio of the channel height to the shear evanescent wavelength(H=λs).To validate our hypothesis,we fabricated a microfluidic QCM(μ-QCM)and demonstrated a remarkable 10-fold improvement in its dissipation when compared to conventional QCM.The novel microfluidic approach offers several additional advantages,such as direct data interpretation,reduced volume requirement for sample liquids,and simplified temperature control,augmenting the sensor’s overall performance.By fostering increased sensitivity,accuracy,and ease of operation,our novel paradigm unlocks new possibilities for advancing gravimetric technologies,potentially for biosensing applications.
基金
funded by grant STTR 1721833 and SBIR 2025974 from the National Science Foundation(NSF)and also by grant 70NANB19H042 from the National Institute of Standards and Technology(NIST)
supported by QATCH Technologies,LLC and the Shared Materials Instrumentation Facility(SMIF).SMIF is located at Duke University and is a member of the Research Triangle Nanotechnology Network(RTNN),a National Science Foundation-funded site in the National Nanotechnology Coordinated Infrastructure(NNCI).
