Mass spectrometry of intact nanoparticles and viruses can serve as a potent characterization tool for material science and biophysics. Inaccessible by widespread commercial techniques, the mass of single nanoparticles and viruses (>10MDa) can be readily measured by nanoelectromechanical systems (NEMS)-based mass spectrometry, where charged and isolated analyte particles are generated by electrospray ionization (ESI) in air and transported onto the NEMS resonator for capture and detection. However, the applicability of NEMS as a practical solution is hindered by their miniscule surface area, which results in poor limit-of-detection and low capture efficiency values. Another hindrance is the necessity to house the NEMS inside complex vacuum systems, which is required in part to focus analytes toward the miniscule detection surface of the NEMS. Here, we overcome both limitations by integrating an ion lens onto the NEMS chip. The ion lens is composed of a polymer layer, which charges up by receiving part of the ions incoming from the ESI tip and consequently starts to focus the analytes toward an open window aligned with the active area of the NEMS electrostatically. With this integrated system, we have detected the mass of gold and polystyrene nanoparticles under ambient conditions and with two orders-of-magnitude improvement in capture efficiency compared to the state-of-the-art. We then applied this technology to obtain the mass spectrum of SARS-CoV-2 and BoHV-1 virions. With the increase in analytical throughput, the simplicity of the overall setup, and the operation capability under ambient conditions, the technique demonstrates that NEMS mass spectrometry can be deployed for mass detection of engineered nanoparticles and biological samples efficiently.

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.

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The size of a cell is one of the most fundamental biophysical parameters it possesses. Traditionally size measurements are done by using optical microscopy and quantitative phase imaging. However, a sensor with higher resolution, high throughput and lower cost is still needed. Here, a novel microfluidics-integrated microwave sensor is demonstrated to characterize single cells in real-time without labelling. Coplanar waveguide resonator is designed with a bowtie-shaped sensing electrodes separated by 50 μm. Cells are transported to sensing region by microfluidic channels and their sizes are measured simultaneously by the microwave sensors and optical microscopy. To enhance the microwave resolution, the microwave resonator is equipped with external heterodyne measurement circuitry detecting each and every cell passing through the sensing region. By comparing quantitative microscopic image analysis with frequency shifts, we show that microwave sensors can effectively measure cellular size. Our results indicate that microfluidicsintegrated microwave sensors (MIMS ) can be used for detecting.

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