Microfluidics and Nanofluidics

, Volume 18, Issue 3, pp 357–366 | Cite as

Serpentine and leading-edge capillary pumps for microfluidic capillary systems

  • Roozbeh Safavieh
  • Ali Tamayol
  • David JunckerEmail author
Research Paper


Microfluidic capillary systems operate using capillary forces only and require capillary pumps (CPs) to transport, regulate, and meter the flow of small quantity of liquids. Common CP architectures include arrays of posts or tree-like branched conduits that offer many parallel flow paths. However, both designs are susceptible to bubble entrapment and consequently variation in the metered volume. Here, we present two novel CP architectures that deterministically guide the filling front along rows while preventing the entrapment of bubbles using variable gap sizes between posts. The first CP (serpentine pump) guides the filling front following a serpentine path, and the second one (leading-edge pump) directs the liquid along one edge of the CP from where liquid fills the pump row-by-row. We varied the angle of the rows with respect to the pump perimeter and observed filling with minimal variation in pumping pressure and volumetric flow rate, confirming the robustness of this design. In the case of serpentine CP, the flow resistance for filling the first row is high and then decreases as subsequent rows are filled and many parallel flow paths are formed. In the leading-edge pump, parallel flow paths are formed almost immediately, and hence, no spike in flow resistance is observed; however, there is a higher tendency of the liquid for skipping a row, requiring more stringent fabrication tolerances. The flow rate within a single CP was adjusted by tuning the gap size between the microposts within the CP so as to create a gradient in pressure and flow rate. In summary, CP with deterministic guidance of the filling front enables precise and robust control of flow rate and volume.


Capillary flow Passive pumping Microfluidics Pore network modeling Point-of-care 



We would like to acknowledge funding from NSERC, CIHR and CFI, and the assistance of the McGill Nanotools and Microfab Laboratory (funded by CFI, NSERC and Nanoquebec). We also acknowledge Prof. Elizabeth Jones for allowing us to use the facilities in her lab. We also acknowledge Arash Kashi, Mohammad Ameen Qasaimeh, and Mohammadali Safavieh for their helpful discussions. DJ acknowledges the support from Canada Research Chair.

Supplementary material

Supplementary material 1 (MP4 3118 kb)

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10404_2014_1454_MOESM8_ESM.docx (2.5 mb)
Supplementary material 8 (DOCX 2552 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Roozbeh Safavieh
    • 1
    • 2
  • Ali Tamayol
    • 1
    • 2
    • 3
    • 4
  • David Juncker
    • 1
    • 2
    • 5
    Email author
  1. 1.McGill University and Genome Quebec Innovation CentreMcGill UniversityMontrealCanada
  2. 2.Biomedical Engineering DepartmentMcGill UniversityMontrealCanada
  3. 3.Harvard-MIT Division of Health Sciences and TechnologyCambridgeUSA
  4. 4.Harvard Medical SchoolBostonUSA
  5. 5.Department of Neurology and NeurosurgeryMcGill UniversityMontrealCanada

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