Faculty of Medicine and Health Technology, Tampere University, Korkeakoulunkatu 3, 33014 Tampere, Finland.
Langmuir. 2022 Sep 27;38(38):11557-11564. doi: 10.1021/acs.langmuir.2c01061. Epub 2022 Sep 13.
Typical microfluidic devices are application-specific and have to be carefully designed to implement the necessary functionalities for the targeted application. Programmable microfluidic chips try to overcome this by offering reconfigurable functionalities, allowing the same chip to be used in multiple different applications. In this work, we demonstrate a programmable microfluidic chip for the two-dimensional manipulation of droplets, based on ultrasonic bulk acoustic waves and a closed-loop machine-learning-based control algorithm. The algorithm has no prior knowledge of the acoustic fields but learns to control the droplets on the fly. The manipulation is based on switching the frequency of a single ultrasonic transducer. Using this method, we demonstrate 2D transportation and merging of water droplets in oil and oil droplets in water, and we performed the chemistry that underlies the basis of a colorimetric glucose assay. We show that we can manipulate drops with volumes ranging from ∼200 pL up to ∼30 nL with our setup. We also demonstrate that our method is robust, by changing the system parameters and showing that the machine learning algorithm can still complete the manipulation tasks. In short, our method uses ultrasonics to flexibly manipulate droplets, enabling programmable droplet microfluidic devices.
典型的微流控设备是特定于应用的，必须精心设计才能实现针对目标应用所需的功能。可编程微流控芯片试图通过提供可重新配置的功能来克服这一问题，允许同一片芯片在多个不同的应用中使用。在这项工作中，我们展示了一种基于体声波和基于闭环机器学习的控制算法的可编程二维液滴操控微流控芯片。该算法对声场没有先验知识，而是在飞行中学习控制液滴。操控是基于切换单个超声换能器的频率来实现的。使用这种方法，我们演示了在油中运输和合并水液滴以及在水中运输和合并油液滴，并且进行了基于比色葡萄糖测定法的基础化学实验。我们表明，我们可以使用我们的设备操控体积从约 200 pL 到约 30 nL 的液滴。我们还通过改变系统参数并表明机器学习算法仍能完成操控任务来证明我们的方法是稳健的。简而言之，我们的方法使用超声灵活地操控液滴，从而实现可编程液滴微流控设备。
