A robust and user-agnostic step-emulsion platform for scalable microgel fabrication

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A robust and user-agnostic step-emulsion platform for scalable microgel fabrication

Authors

Pioche-Lee, D.; Yang, S.; Wang, X.; Ho, Y. Q.; Rahman, W.; Vartanian, A. C.; Pavlidis, D. I.; Zhang, I. W.; Vallier, J. E.; McCorkle, E.; Schaefer, A.; Putnam, A. J.; Shikanov, A. A.; DeForest, C. A.; Lesher-Perez, S. C.

Abstract

Over the past decade, the integration of microgel-based granular hydrogels in biomedical technologies has experienced substantial growth due to the numerous benefits microgels offer. However, a major bottleneck or in some cases, a barrier-to-entry stunting further growth of the field, is the inability to easily adopt uniform microgel fabrication workflows at scale. The gold-standard technique for emulsion-based microgel production is through microfluidic droplet-generating devices that produce liquid gel precursor droplets that gel post-production. However, traditional microfluidic workflows often require multiple independent flows and controlled pressure sources, along with a steep learning curve in using microfluidics to achieve uniform droplet sizes reproducibly and repeatedly. This difficulty in adopting microgel fabrication has been further compounded in being low-throughput and requiring extensive flow rate calibration when switching to new formulations (e.g., material type, droplet size). In this work, we present a step-emulsion system that bridges the gap by providing a robust and simple setup. We experimentally characterize and evaluate how flow and outlet channel dimension contribute to the generation of uniform droplet populations at specific sizes. With our large dataset consisting of various outlet channel dimensions, we evaluated outlet channel geometrical impacts (height, width, cross-sectional area, aspect-ratio, etc.) on gel precursor droplet size and generation throughput. We demonstrate robust, highly compatible, and repeatably uniform droplet generation from various gel precursor polymer backbones, users with varying microfluidics experience, and a wide viscosity range, including alginate solutions with 650 times the viscosity of water. Furthermore, we confirmed consistent gel precursor droplet generation outcomes driven by a constant flow source (syringe pump) and by direct manual injection as a simple and highly adoptable option for the generation of gel precursor droplets. This platform is ideal for researchers seeking rapid and easy microgel fabrication, regardless of microfluidics experience.

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