Shahrivar Keshvad, Del Giudice Francesco
Department of Chemical Engineering, School of Engineering and Applied Science, Faculty of Science and Engineering, Swansea University, Swansea, SA1 8EN, UK.
Soft Matter. 2022 Aug 17;18(32):5928-5933. doi: 10.1039/d2sm00935h.
The encapsulation and co-encapsulation of particles in microfluidic flows is essential in applications related to single-cell analysis and material synthesis. However, the whole encapsulation process is stochastic in nature, and its efficiency is limited by the so-called Poisson limit. We here demonstrate particle encapsulation in microfluidic devices having flow-focusing geometries with efficiency up to 2-fold larger than the stochastic limit imposed by the Poisson statistics. To this aim, we exploited the recently observed phenomenon of particle train formation in viscoelastic liquids, so that particles could approach the encapsulation area with a constant frequency that was subsequently synchronised to the constant frequency of droplet formation. We also developed a simplified expression based on the experimental results that can guide optimal design of the microfluidic encapsulation system. Finally, we report the first experimental evidence of viscoelastic co-encapsulation of particles coming from different streams.
在与单细胞分析和材料合成相关的应用中，微流体流中颗粒的包封和共包封至关重要。然而，整个包封过程本质上是随机的，其效率受到所谓泊松极限的限制。我们在此展示了在具有流动聚焦几何结构的微流体装置中进行颗粒包封，其效率比泊松统计所施加的随机极限高出两倍。为此，我们利用了最近在粘弹性液体中观察到的颗粒链形成现象，使颗粒能够以恒定频率接近包封区域，该频率随后与液滴形成的恒定频率同步。我们还根据实验结果开发了一个简化表达式，可指导微流体包封系统的优化设计。最后，我们报告了来自不同流的颗粒进行粘弹性共包封的首个实验证据。
