Advanced Simulation of Droplet Microfluidics

Abstract

The complexity of droplet microfluidics grows with the implementation of parallel processes and multiple functionalities on a single device. This poses a serious challenge to the engineer designing the corresponding microfluidic networks. In today's design processes, the engineer relies on calculations, assumptions, simplifications, as well as his/her experiences and intuitions. In order to validate the obtained specification of the microfluidic network, usually a prototype is fabricated and physical experiments are conducted thus far. In case the design does not implement the desired functionality, this prototyping iteration is repeated -obviously resulting in an expensive and time-consuming design process. In order to avoid unnecessary debugging loops involving fabrication and testing, simulation methods could help to initially validate the specification of the microfluidic network before any prototype is fabricated. However, state-of-the-art simulation tools come with severe limitations, which prevent their utilization for practically-relevant applications. More precisely, they are often not dedicated to droplet microfluidics, cannot handle the required physical phenomena, are not publicly available, and can hardly be extended. In this work, we present an advanced simulation approach for droplet microfluidics which addresses these shortcomings and, eventually, allows to simulate practically-relevant applications. To this end, we propose a simulation framework which directly works on the specification of the design, supports essential physical phenomena, is publicly available, and easy to extend. Evaluations and case studies demonstrate the benefits of the proposed simulator: While current state-of-the-art tools were not applicable for practically-relevant microfluidic networks, the proposed solution allows to reduce the design time and costs e.g. of a drug screening device from one person month and USD 1200, respectively, to just a fraction of that.

Computer-Aided Design of Microfluidic Circuits

“…However, this approach is not guided by a physical model of droplet dynamics. The design challenge for droplet-based microfluidics is complex since simulating or modeling droplet behavior is not a trivial task, and it is not readily addressable by current modeling environments (84). Glawdel & Ren (85) proposed a set of rules to guide designers into a limited relevant design space.…”

Design and realization of flexible droplet-based lab-on-a-chip devices

“…One example of such a tool is the simulator proposed in [18], which utilizes the 1D model described in Sect. 2 and simulates droplet-based microfluidic devices.…”

Compact Empirical Model for Droplet Generation in a Lab-on-Chip Cytometry System

“…Thus, in addition to the high computational workload, the major problem of the physical approach is often the presence of nonmeasurable physical parameters and the hidden influence of numerical factors such as reduced spatial dimensionality and mesh step sizes. Although many authors have illustrated their studies with simulated droplet images, for example, [23]- [26], several respected research groups, for example, [24], [27]- [29], emphasize the unreliability of numerical physical modelling, particularly if the droplet size, generation rate, and monodispersity characteristics must all be reliably calculated simultaneously. Moreover, considering the three main droplet generation geometry typesco-axial, T-junction and flowfocused [27], [30], the third option, which is also analyzed in the present study, has been estimated most difficult for the point of view of accurate modelling [20], [30], [31].…”