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Research Papers: Flows in Complex Systems

Modeling and Experimental Characterization of Pressure Drop in Gravity-Driven Microfluidic Systems

[+] Author and Article Information
Antti-Juhana Mäki

Department of Automation Science and Engineering,
Tampere University of Technology,
Korkeakoulunkatu 3,
Tampere 33720, Finland
Institute of Biosciences and Medical Technology,
Biokatu 10,
Tampere 33520, Finland
e-mail: antti-juhana.maki@tut.fi

Samu Hemmilä

Department of Automation Science and Engineering,
Tampere University of Technology,
Korkeakoulunkatu 3,
Tampere 33720, Finland
Institute of Biosciences and Medical Technology,
Biokatu 10,
Tampere 33520, Finland
e-mail: samu.hemmila@tut.fi

Juha Hirvonen

Department of Automation Science and Engineering,
Tampere University of Technology,
Korkeakoulunkatu 3,
Tampere 33720, Finland
e-mail: juha.hirvonen@tut.fi

Nathaniel Narra Girish

Department of Electronics and
Communications Engineering,
Tampere University of Technology,
Korkeakoulunkatu 3,
Tampere 33720, Finland
Institute of Biosciences and Medical Technology,
Biokatu 10,
Tampere 33520, Finland
e-mail: nathaniel.narragirish@tut.fi

Joose Kreutzer

Department of Automation Science and Engineering,
Tampere University of Technology,
Korkeakoulunkatu 3,
Tampere 33720, Finland
Institute of Biosciences and Medical Technology,
Biokatu 10,
Tampere 33520, Finland
e-mail: joose.kreutzer@tut.fi

Jari Hyttinen

Professor
Department of Electronics and
Communications Engineering,
Tampere University of Technology,
Korkeakoulunkatu 3,
Tampere 33720, Finland
Institute of Biosciences and Medical Technology,
Biokatu 10,
Tampere 33520, Finland
e-mail: jari.hyttinen@tut.fi

Pasi Kallio

Professor
Department of Automation Science and Engineering,
Tampere University of Technology,
Korkeakoulunkatu 3,
Tampere 33720, Finland
Institute of Biosciences and Medical Technology,
Biokatu 10,
Tampere 33520, Finland
e-mail: pasi.kallio@tut.fi

1Corresponding author.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received May 2, 2014; final manuscript received August 26, 2014; published online October 8, 2014. Assoc. Editor: Ali Beskok.

J. Fluids Eng 137(2), 021105 (Oct 08, 2014) (8 pages) Paper No: FE-14-1238; doi: 10.1115/1.4028501 History: Received May 02, 2014; Revised August 26, 2014

Passive pumping using gravity-driven flow is a fascinating approach for microfluidic systems. When designing a passive pumping system, generated flow rates should be known precisely. While reported models used to estimate the flow rates do not usually consider capillary forces, this paper shows that their exclusion is unrealistic in typical gravity-driven systems. Therefore, we propose a new analytical model to estimate the generated flow rates. An extensive set of measurements is used to verify that the proposed model provides a remarkably more precise approximation of the real flow rates compared to the previous models. It is suggested that the developed model should be used when designing a gravity-driven pumping system.

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References

Figures

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Fig. 1

Working principle (not to scale) of the gravity-driven pump device presented in this paper. Liquid flow is driven by hydrostatic pressure created by the liquid level difference (Δh) between inlet and outlet reservoirs.

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Fig. 2

(a) The schematic of the whole PDMS-based microfluidic test structure with three parallel test setups. (b) and (c) Dimensions of the reservoir and channel layers, respectively. (d) The fabricated device.

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Fig. 3

A snapshot of the image-based analysis showing calculated inlet (squares) and outlet (triangles) reservoirs' plug height levels

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Fig. 4

The main steps for contact angle measurement: (a) original image, (b) modified inlet plug image to define the contact angle in the inlet reservoir, and (c) modified outlet plug image to define the contact angle in the outlet reservoir. All images were taken at 600 min using a 100 μm wide microchannel.

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Fig. 5

(a) An original μCT image snapshot of a 500 μm wide channel cross section, scale bar is 250 μm. Image-based analyses of channel dimensions: (b) area and perimeter, (c) height, and (d) widths, scale bar is 250 μm.

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Fig. 6

Experimental average height difference (in mm) as a function of time (minutes) when the targeted microchannel width was 100 μm. Each individual channel was measured three times.

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Fig. 7

Comparison of the experimental data and the three analytical models. Height difference (in mm) is plotted as a function of time (minutes) when targeted microchannel width was (a) 50 μm, (b) 100 μm, (b) 250 μm, and (d) 500 μm.

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