Double emulsion droplets (DEs) are water/oil/water droplets that can be sorted via fluorescence-activated cell sorting (FACS), allowing for new opportunities in high-throughput cellular analysis, enzymatic screening, and synthetic biology. These applications require stable, uniform droplets with predictable microreactor volumes. However, predicting DE droplet size, shell thickness, and stability as a function of flow rate has remained challenging for monodisperse single core droplets and those containing biologically-relevant buffers, which influence bulk and interfacial properties. As a result, developing novel DE-based bioassays has typically required extensive initial optimization of flow rates to find conditions that produce stable droplets of the desired size and shell thickness. To address this challenge, we conducted systematic size parameterization quantifying how differences in flow rates and buffer properties (viscosity and interfacial tension at water/oil interfaces) alter droplet size and stability, across 6 inner aqueous buffers used across applications such as cellular lysis, microbial growth, and drug delivery, quantifying the size and shell thickness of >22 000 droplets overall. We restricted our study to stable single core droplets generated in a 2-step dripping–dripping formation regime in a straightforward PDMS device. Using data from 138 unique conditions (flow rates and buffer composition), we also demonstrated that a recent physically-derived size law of Wang et al. can accurately predict double emulsion shell thickness for >95% of observations. Finally, we validated the utility of this size law by using it to accurately predict droplet sizes for a novel bioassay that requires encapsulating growth media for bacteria in droplets. This work has the potential to enable new screening-based biological applications by simplifying novel DE bioassay development.

中文翻译：

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流速和缓冲液组成对双乳液液滴体积和稳定性影响的系统表征

双乳化液滴 (DE) 是水/油/水滴，可以通过荧光激活细胞分选 (FACS)，为高通量细胞分析、酶筛选和合成生物学带来新机遇。这些应用需要具有可预测微反应器体积的稳定、均匀的液滴。然而，对于单分散单核液滴和含有生物相关缓冲液的液滴，预测 DE 液滴尺寸、壳厚度和稳定性作为流速的函数仍然具有挑战性，这会影响体积和界面特性。因此，开发新的基于 DE 的生物测定通常需要对流速进行广泛的初始优化，以找到产生所需尺寸和壳厚度的稳定液滴的条件。为了应对这一挑战，我们进行了系统的尺寸参数化，量化了流速和缓冲液特性（水/油界面处的粘度和界面张力）的差异如何改变液滴尺寸和稳定性，在细胞裂解、微生物生长和药物输送等应用中使用的 6 种内部水缓冲液中，量化> 22 000个液滴的大小和壳厚度。我们将我们的研究限制在简单的 PDMS 设备中在两步滴落形成方案中产生的稳定单核液滴。使用来自 138 个独特条件（流速和缓冲液成分）的数据，我们还证明了 Wang 最近的物理衍生尺寸定律 微生物生长和药物输送，量化 > 22 000 个液滴的大小和壳厚度。我们将我们的研究限制在简单的 PDMS 设备中在两步滴落形成方案中产生的稳定单核液滴。使用来自 138 个独特条件（流速和缓冲液成分）的数据，我们还证明了 Wang 最近的物理衍生尺寸定律 微生物生长和药物输送，量化 > 22 000 个液滴的大小和壳厚度。我们将我们的研究限制在简单的 PDMS 设备中在两步滴落形成方案中产生的稳定单核液滴。使用来自 138 个独特条件（流速和缓冲液成分）的数据，我们还证明了 Wang 最近的物理衍生尺寸定律等。可以准确预测 > 95% 的观察结果的双乳液壳厚度。最后，我们通过使用它来准确预测液滴大小来验证这种尺寸定律的实用性，这种新型生物测定需要将细菌的生长培养基封装在液滴中。这项工作有可能通过简化新的 DE 生物测定开发来实现新的基于筛选的生物学应用。