A novel method for validating Computational Fluid Dynamics (CFD) outcomes on microfluidic mixer devices: a case study.

Microfluidics technology has become in recent years a powerful innovation driver with many examples of successful products already in the market. Microfluidics is proven an enabling technology in a wide variety of applications such as life sciences instruments and in vitro diagnostic devices. Some ground-breaking examples include organ-on-a-chip systems and Point-Of-Care-Testing devices, which have starred a pivotal role in fighting against the COVID-19 pandemic.

Mixing various liquids (e.g., samples and reagents) is a prevalent operation. Mixing in the miniaturized dimensions of microfluidic circuits is, however, a major challenge since turbulence is suppressed. As a result of the distinctive laminar behavior exhibited by liquids at the microscale, diffusion is the only mechanism by which liquids can mix, a process that is too slow to rely on. While there exists an assortment of solutions to promote mixing in microsystems, the most suitable solution needs to be selected and the design engineered for it to meet the specific requirements of each particular application. This is because the performance of the micro-mixers, as for microfluidic devices in general, is determined by the geometric design parameters (cross-sectional shape and dimensions) and the configuration of the microfluidic network architecture.

Computational Fluid Dynamics (CFD) modeling and numerical simulations are necessary tools in the design process of microfluidic devices. In short, CFD is a powerful toolset that provides detailed information about the behavior of the flow in a design as well as solutions to complex problems related to the mass and heat transport phenomena that cannot be obtained otherwise. CFD models, however, must always be validated experimentally, Innovative hands-on approaches are required. Validated CFD models help to mitigate the risk of failure even before moving forward with prototyping and minimize the number of design-prototyping-testing iterations, ultimately resulting in cost and time savings.

Our case study presents a novel optical method for validating CFD outcomes, which includes an innovative definition of variables and comparative strategy, and obviates the need for costly equipment or specialized personnel. We demonstrate its effectiveness across a range of practical micro-mixer designs and relevant materials and experimental settings. Additionally, we showcase its use for optimizing a microfluidic mixer de


Daniel Blanco (1), Patrick Vlieger (1), Thijs Meewis (2), Koen Beyers (1), Tim Dieryckx (1)


Voxdale BV (1), University of Ghent (2)

Presenting author

Daniel Blanco, Systems engineer and project manager , Voxdale BV
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