(117f) Toward a Biological Toolkit: Systematic Characterization of Double Emulsions for Screening Applications

In the past ten years, droplet microfluidic techniques have enabled novel biological investigation at unprecedented scale, with applications ranging from disease diagnosis, synthetic biology, fundamental biochemical characterization, and single cell analysis. Recently, double emulsions (DEs), droplets with a W/O/W architecture, have generated significant interest in the field due to their unique compatibility with fluorescence-activated cell sorting (FACS), allowing droplets to be be screened and sorted by a phenotype-of-interest to expand cellular analysis capabilities. However, producing stable double emulsion droplets of predictable size for optimized reactions, especially under complex biologically-relevant surfactant conditions, remains prohibitively challenging and largely inaccessible to nonmicrofluidic specialists. To address this need, we conducted extensive systematic size parameterization of DE droplets in a microfluidic dual flow-focuser device in a 'drippingdripping' flow regime, building upon our prior development of an open-source microfluidic DE generation platform, Dropception. With the goal of creating a easy-to-use toolkit for biological researchers, we characterized monodisperse droplets with <5% CV across >100 flow conditions and a broad range of 6 biologically relevant aqueous solutions for applications such as cellular lysis, microbial growth, and drug delivery. In parallel, we performed extensive rheological investigation of these aqueous and oil phase components, to quantify previously unexplored multi-surfactant stabilization of complex droplet architectures. We observe that size variation is dominantly explained by simple flow-based volume conservation, whereas surfactant variation influences DE stability ranges. We apply these findings to optimize FACS analysis of different size double emulsions. This interdisciplinary work importantly enables new screening-based biological applications of DEs by lowering the barrier of entry to new researchers.