Processes for the 3D Printing of Hydrodynamic Flow-Focusing Devices.

Flow focusing is an important hydrodynamic technique for cytometric analysis, enabling the rapid study of cellular samples to identify a variety of biological processes. To date, the majority of flow-focusing devices are fabricated using conventional photolithography or flame processing of glass capillaries. This article presents a suite of low-cost, millifluidic, flow-focusing devices that were fabricated using a desktop sterolithgraphy (SLA) 3D printer. The suite of SLA printing strategies consists of a monolithic SLA method and a hybrid molding process. In the monolithic SLA approach, 1.3 mm square millifluidic channels were printed as a single piece. The printed device does not require any post processing, such as bonding or surface polishing for optical access. The hybrid molding approach consists of printing a mold using the SLA 3D printer. The mold is treated to an extended UV exposure and oven baked before using PDMS as the molding material for the channel. To demonstrate the viability of these channels, we performed a series of experiments using several flow-rate ratios to show the range of focusing widths that can be achieved in these devices. The experiments are validated using a numerical model developed in ANSYS.

3D printed imaging platform for portable cell counting.

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.