A Computational Model for the Design of ElectroWetting On Dielectric (EWOD) Systems

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Microfluidics has enabled the development of integrated lab-on-a-chip (LoC) devices for use in a clinical diagnostics, high throughput screening, drug discovery, biodefense and environmental monitoring. Although most microfluidic devices are based on continuous flow of liquids in microchannels fabricated mainly from glass or plastics, there is an increasing interest in devices that rely on manipulation of discrete droplets using surface tension effects that are dominant at the small length scales associated with these devices. One such technique is ElectroWetting-On-Dielectric (EWOD), which is based on changing the wettability of liquids on a dielectric solid surface by varying the electric potential. This method offers advantages over conventional continuious-flow microfluidic chips, by way of significantly reduced sample size, as well as reconfigurability and scalability of architecture. The similarity of the EWOD system with digital microelectronic systems, has led to the term “digital microfluidics” [1]. The phenomenon of EWOD has been demonstrated for dispensing, cutting, and transport of tiny droplets [2, 3], and more recently, a proof-of-concept has been demonstrated for an integrated lab-on-a-chip system for clinical diagnostic applications [1]. While considerable attention has been focused on fabrication and demonstration, there has been little attention to modeling of droplet transport and bioassays in these systems. Most of the studies have focused on using basic equations describing interfacial phenomena (Young’s equation) [2], but there has been no quantitative application for design analysis of these systems. The present paper demonstrates the use of a CFD model to describe transport of biological species in EWOD systems, including reactions involved in bioassays and passive binding of proteins to the dielectric surface. We have used a Volume Of Fluid (VOF) method to describe the transport of droplets, as a result of the gradients in contact angle generated by application of the electric field. This is coupled with the equations for transport of biological species that includes appropriate biochemical reactions occurring in the system. Figure 1 shows the validation of the model for splitting and merging of a droplet as demonstrated in [2]. The behavior is identical to that observed, including the time required for the process. We have also investigated the role of non-specific protein binding to the dielectric surface in determining the efficiency of the assay. Figure 2 shows the binding of glucose oxidase from the droplet to the Teflon surface as the droplet moves through the chip. The rate constants for protein binding have been estimated from microcapillary experiments [4]. The simulations give an estimate of the extent of bio-fouling that can take place in microfluidic devices. The computational model will also be used to understand the role of convective and diffusive transport of protein within the droplet when used for a clinical diagnostic application, along with comparison with experimental data. This model provides a powerful tool for rapid “virtual prototyping” of microfluidic devices and allows engineers to design analysis and optimization of EWOD devices for various applications.

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Journal: TechConnect Briefs
Volume: 1, Technical Proceedings of the 2005 NSTI Nanotechnology Conference and Trade Show, Volume 1
Published: May 8, 2005
Pages: 648 - 651
Industry sectors: Medical & Biotech | Sensors, MEMS, Electronics
Topic: Micro & Bio Fluidics, Lab-on-Chip
ISBN: 0-9767985-0-6