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Preprogrammed capillarity to passively control system-level sequential and parallel microfluidic flows.

ABSTRACT: In microfluidics, capillarity-driven solution flow is often beneficial, owing to its inherently spontaneous motion. However, it is commonly perceived that, in an integrated microfluidic system, the passive capillarity control alone can hardly achieve well-controlled sequential and parallel flow of multiple solutions. Despite this common notion, we hereby demonstrate system-level sequential and parallel microfluidic flow processing by fully passive capillarity-driven control. After manual loading of solutions with a pipette, a network of microfluidic channels passively regulates the flow timing of the multiple solution menisci in a sequential and synchronous manner. Also, use of auxiliary channels and preprogramming of inlet-well meniscus pressure and channel fluidic conductance allow for controlling the flow direction of multiple solutions in our microfluidic system. With those components orchestrated in a single device chip, we show preprogrammed flow control of 10 solutions. The demonstrated system-level flow control proves capillarity as a useful means even for sophisticated microfluidic processing without any actively controlled valves and pumps.

SUBMITTER: Kim SJ

PROVIDER: S-EPMC3664099 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

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Preprogrammed capillarity to passively control system-level sequential and parallel microfluidic flows.

Kim Sung-Jin SJ Paczesny Sophie S Takayama Shuichi S Kurabayashi Katsuo K

Lab on a chip 20130601 11

In microfluidics, capillarity-driven solution flow is often beneficial, owing to its inherently spontaneous motion. However, it is commonly perceived that, in an integrated microfluidic system, the passive capillarity control alone can hardly achieve well-controlled sequential and parallel flow of multiple solutions. Despite this common notion, we hereby demonstrate system-level sequential and parallel microfluidic flow processing by fully passive capillarity-driven control. After manual loading ...[more]

PMID: 23598742

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Project description:Liquid filling in microfluidic channels is a complex process that depends on a variety of geometric, operating, and material parameters such as microchannel geometry, flow velocity∕pressure, liquid surface tension, and contact angle of channel surface. Accurate analysis of the filling process can provide key insights into the filling time, air bubble trapping, and dead zone formation, and help evaluate trade-offs among the various design parameters and lead to optimal chip design. However, efficient modeling of liquid filling in complex microfluidic networks continues to be a significant challenge. High-fidelity computational methods, such as the volume of fluid method, are prohibitively expensive from a computational standpoint. Analytical models, on the other hand, are primarily applicable to idealized geometries and, hence, are unable to accurately capture chip level behavior of complex microfluidic systems. This paper presents a parametrized dynamic model for the system-level analysis of liquid filling in three-dimensional (3D) microfluidic networks. In our approach, a complex microfluidic network is deconstructed into a set of commonly used components, such as reservoirs, microchannels, and junctions. The components are then assembled according to their spatial layout and operating rationale to achieve a rapid system-level model. A dynamic model based on the transient momentum equation is developed to track the liquid front in the microchannels. The principle of mass conservation at the junction is used to link the fluidic parameters in the microchannels emanating from the junction. Assembly of these component models yields a set of differential and algebraic equations, which upon integration provides temporal information of the liquid filling process, particularly liquid front propagation (i.e., the arrival time). The models are used to simulate the transient liquid filling process in a variety of microfluidic constructs and in a multiplexer, representing a complex microfluidic network. The accuracy (relative error less than 7%) and orders-of-magnitude speedup (30 000X-4 000 000X) of our system-level models are verified by comparison against 3D high-fidelity numerical studies. Our findings clearly establish the utility of our models and simulation methodology for fast, reliable analysis of liquid filling to guide the design optimization of complex microfluidic networks.

Dataset Information

Preprogrammed capillarity to passively control system-level sequential and parallel microfluidic flows.

Publications

Preprogrammed capillarity to passively control system-level sequential and parallel microfluidic flows.

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