Microwave sensors can probe intrinsic material properties of analytes in a microfluidic channel at physiologically relevant ion concentrations. While microwave sensors have been used to detect single cells and microparticles in earlier studies, the synergistic use and comparative analysis of microwave sensors with optical microscopy for material classification and size tracking applications have been scarcely investigated so far. Here we combined microwave and optical sensing to differentiate microscale objects based on their dielectric properties. We designed and fabricated two types of planar sensor: a Coplanar Waveguide Resonator (CPW) and a Split-Ring Resonator (SRR). Both sensors possessed sensing electrodes with a narrow gap to detect single cells passing through a microfluidic channel integrated on the same chip. We also show that standalone microwave sensors can track the relative changes in cellular size in real-time. In sensing single 20-micron diameter polystyrene particles, Signal-to-Noise ratio values of approximately 100 for CPW and 70 for SRR sensors were obtained. These findings demonstrate that microwave sensing technology can serve as a complementary technique for single-cell biophysical experiments and microscale pollutant screening.

Precise monitoring of fluid flow rates constitutes an integral problem in various lab-on-a-chip applications. While off-chip flow sensors are commonly used, new sensing mechanisms are being investigated to address the needs of increasingly complex lab-on-a-chip platforms which require local and non-intrusive flow rate sensing. In this regard, the deformability of microfluidic components has recently attracted attention as an on-chip sensing mechanism. To develop an on-chip flow rate sensor, here we utilized the mechanical deformations of a 220 nm thick Silicon Nitride membrane integrated with the microfluidic channel. Applied pressure and fluid flow induce different modes of deformations on the membrane, which are electronically probed by an integrated microwave resonator. The flow changes the capacitance, and in turn resonance frequency, of the microwave resonator. By tracking the resonance frequency, liquid flow was probed with the device. In addition to responding to applied pressure by deflection, the membrane also exhibits periodic pulsation motion under fluid flow at a constant rate. The two separate mechanisms, deflection and pulsation, constitute sensing mechanisms for pressure and flow rate. Using the same device architecture, we also detected pressure-induced deformations by a gas to draw further insight into the sensing mechanism of the membrane. Flow rate measurements based on the deformation and instability of thin membranes demonstrate the transduction potential of microwave resonators for fluid-structure interactions at micro-and nanoscales.

Precise monitoring of fluid flow rates constitutes an integral problem in various lab-on-a-chip applications. While off-chip flow sensors are commonly used, new sensing mechanisms are being investigated to address the needs of increasingly complex lab-on-a-chip platforms which require local and non-intrusive flow rate sensing. In this regard, the deformability of microfluidic components has recently attracted attention as an on-chip sensing mechanism. To develop an on-chip flow rate sensor, here we utilized the mechanical deformations of a 220 nm thick Silicon Nitride membrane integrated with the microfluidic channel. Fluid flow induces deformations on the membrane, which is electronically probed by the changes in the capacitance and resonance frequency of an overlapping microwave resonator. By tracking the resonance frequency, both liquid and gas flows were probed with the same device architecture. For liquid flow experiments, a secondary sensing mechanism emerged when it was observed that steady liquid flow induces periodic deformations on the membrane. Here, the period of membrane deformation depends on the flow rate and can again be measured electronically by the microwave sensor. Flow rate measurements based on the deformation and instability of thin membranes demonstrate the transduction potential of microwave resonators for fluid-structure interactions at micro and nanoscales.

Permittivity of microscopic particles can be used as a classification parameter for applications in materials and environmental sciences. However, directly measuring the permittivity of individual microparticles has proven to be challenging due to the convoluting effect of particle size on capacitive signals. To overcome this challenge, we built a sensing platform to independently obtain both the geometric and electric size of a particle, by combining impedance cytometry and microwave resonant sensing in a microfluidic chip. This way the microwave signal, which contains both permittivity and size effects, can be normalized by the size information provided by impedance cytometry to yield an intensive parameter that depends only on permittivity. The technique allowed us to differentiate between polystyrene and soda lime glass microparticles —below 22 microns in diameter— with more than 94% accuracy, despite their similar sizes and electrical characteristics. Furthermore, we show that the same technique can be used to differentiate between normal healthy cells and fixed cells of the same geometric size. The technique offers a potential route for targeted applications such as environmental monitoring of microplastic pollution or quality control in pharmaceutical industry.This article is protected by copyright. All rights reserved

Coulter counters and impedance cytometry are commonly used for counting microscopic objects, such as cells and microparticles flowing in a liquid, as well as to obtain their size distribution. However, the ability of these techniques to provide simultaneous material information - via dielectric permittivity measurements - has been limited so far. The challenge stems from the fact that the signals generated by microparticles of identical size, but different material composition, are close to each other. The similarity in impedance signals arises because the material-dependent factor is determined mainly by the volume of aqueous solution displaced by the microparticles, rather than the microparticles themselves. To differentiate between materially distinct particles with similar geometry and size, another measurement mode needs to be implemented. Here, we describe a new microfluidics-based sensor that provides material classification between microparticles with similar sizes by integrating impedance cytometry with microwave resonator sensors on the same chip. While low-frequency impedance cytometry provides the geometric size of particles, the microwave sensor operating at three orders-of-magnitude higher frequency provides their electrical size. By combining these two measurements, the Clausius-Mossotti factors of microparticles can be calculated to serve as a differentiation parameter. In addition to distinguishing dielectric materials from cells and metals, we classified two different dielectric microparticles with similar sizes and electrical characteristics: polystyrene and soda lime glass, with 94% identification accuracy. The proposed technique can serve as an automated monitoring system for quality control of manufactured microparticles and facilitate environmental microplastic screening.