An imaging scheme to study the flow dynamics of co-flow regimes in microfluidics: implications for nanoprecipitation
: Inam, Wali; Vladyka, Anton; Pylvänäinen, Joanna W.; Solis, Junel; Tokic, Dado; Kankaanpää, Pasi; Zhang, Hongbo
Publisher: Royal Society of Chemistry (RSC)
: CAMBRIDGE
: 2024
: Lab on a Chip
: Lab on a Chip
: LAB CHIP
: 24
: 24
: 5374
: 5383
: 10
: 1473-0197
: 1473-0189
DOI: https://doi.org/10.1039/d4lc00652f(external)
: https://doi.org/10.1039/D4LC00652F(external)
: https://research.utu.fi/converis/portal/detail/Publication/471000683(external)
Co-flow microfluidics, in addition to its applications in droplet generation, has gained popularity for use with miscible solvent systems (continuous microfluidics). By leveraging the short diffusional distances in miniature devices, processes like nanomaterial synthesis can be precisely tailored for high-throughput production. In this context, the manipulation of flow regimes-from laminar to vortex formation, as well as the generation of turbulent and turbulent jet flows-plays a significant role in optimizing these processes. Therefore, a detailed understanding of fluid interactions within microchannels is crucial. Imaging with tracer particles is a commonly used approach to study fluid behavior. Alternatively, label-free imaging methodologies are rarely employed for studying fluid dynamics. In this pursuit, we present a new imaging-based scheme to explore fluid interactions in various co-flow regimes through optical flow analysis, specifically using Gaussian window mean squared error (MSE). By examining fluid flow characteristics such as flow intensities (caused by fluctuations) and the projected movement of fluid spots, we characterize slow vortexing and chaotic flow behaviors in co-flow regimes. Consequently, we use imaging data to illustrate the influence of co-flow regimes on particle synthesis. This new tool provides the scientific community with an innovative method to study fluid interactions, which can be further explored to develop a more effective understanding of fluid mixing and optimize fluid manipulation in microfluidic devices.
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This work was supported by the Research Fellow (Grant No. 353146), Project (347897), Solution for Health Profile (336355), and InFLAMES Flagship (337531) grants from Academy of Finland. Biocenter Finland Bioinformatics and Drug Discovery and Chemical Biology networks, CSC IT Center for Science, Joe, Pentti and Tor Borg Memorial Fund, S. J. foundation are acknowledged.
