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We introduce an approach to generate direction-controlled circulation around cylindrical obstructions in channels using a piezoelectric transducer embedded porous-channel device fabricated by photolithography. To transmit acoustic signals into the channel, a single piezoelectric transducer was attached, operating at voltage levels of 5, 10, 15, and 20 V. Microscopic particle image velocimetry was employed to analyze the flow patterns in the channels. The analysis revealed two opposing circulation tendencies around the pillars located at two opposite sides of the channel in the longitudinal direction. The strength of circulation was found to be minimal in the middle of the channel and increased gradually toward the two ends of the channels. Furthermore, we observed that the circulation strength was maximum near the axial centerline and minimum at the boundaries along the width of the channels. Comparing the voltage levels, the higher voltage signals produced a higher strength of circulation than the lower voltage signals in all cases. Additionally, we found that the strength of circulation increased almost linearly and then decayed exponentially in the radial direction from the surfaces of the pillars. The observed velocity fields around individual cylinders matched well with the Görtler vortex model. The reported circulation phenomenon around pillars can be applied in non-contact fluid stirring and mixing in bio-chemical systems and lab-on-a-chip systems and may also provide additional degrees of freedom in object tweezing, trapping, and levitation.

 

Despite having widespread application in the biomedical sciences, flow cytometers have several limitations that prevent their application to point-of-care (POC) diagnostics in resource-limited environments. 3D printing provides a cost-effective approach to improve the accessibility of POC devices in resource-limited environments. Towards this goal, we introduce a 3D-printed imaging platform (3DPIP) capable of accurately counting particles and perform fluorescence microscopy. In our 3DPIP, captured microscopic images of particle flow are processed on a custom developed particle counter code to provide a particle count. This prototype uses a machine vision-based algorithm to identify particles from captured flow images and is flexible enough to allow for labeled and label-free particle counting. Additionally, the particle counter code returns particle coordinates with respect to time which can further be used to perform particle image velocimetry. These results can help estimate forces acting on particles, and identify and sort different types of cells/particles. We evaluated the performance of this prototype by counting 10 μm polystyrene particles diluted in deionized water at different concentrations and comparing the results with a commercial Beckman-Coulter Z2 particle counter. The 3DPIP can count particle concentrations down to ∼100 particles per mL with a standard deviation of ±20 particles, which is comparable to the results obtained on a commercial particle counter. Our platform produces accurate results at flow rates up to 9 mL h −1 for concentrations below 1000 particle per mL, while 5 mL h −1 produces accurate results above this concentration limit. Aside from performing flow-through experiments, our instrument is capable of performing static experiments that are comparable to a plate reader. In this configuration, our instrument is able to count between 10 and 250 cells per image, depending on the prepared concentration of bacteria samples ( Citrobacter freundii ; ATCC 8090). Overall, this platform represents a first step towards the development of an affordable fully 3D printable imaging flow cytometry instrument for use in resource-limited clinical environments.