Experiments in Fluids

, Volume 34, Issue 4, pp 504–514 | Cite as

Particle imaging techniques for microfabricated fluidic systems

  • S. DevasenathipathyEmail author
  • J. G. Santiago
  • S. T. Wereley
  • C. D. Meinhart
  • K. Takehara


This paper presents the design and implementation of velocimetry techniques applicable to the analysis of microfluidic systems. The application of both micron-resolution particle image velocimetry (micro-PIV) and particle tracking velocimetry (PTV) to the measurement of velocity fields within micromachined fluidic channels is presented. The particle tracking system uses epifluorescent microscopy, CCD imaging, and specialized image interrogation algorithms to provide microscale velocity measurement resolution. The flow field in a straight channel section is measured using cross-correlation micro-PIV and compared to the analytical solution for a measured mass flow rate. Velocity field measurements of the flow at the intersection of a cross-channel are also presented and compared with simulations from a commercially available flow solver, CFD-ACE+. Discussions regarding flow seeding, imaging optics, and the flow setup for measuring flows in microfabricated fluidic devices are presented. A simple process for estimating measurement uncertainty of the in-plane velocity measurements caused by three-dimensional Brownian motion is described. A definition for the measurement depth for PTV measurements is proposed. The agreement between measured and predicted values lends further support to the argument that liquid microflows with characteristic dimensions of order 50-μm dimension channels follow macroscale flow theory.


Particle Image Particle Displacement Particle Tracking Velocimetry Interrogation Region Silicon Channel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



numerical aperture of objective lens


refractive index of immersing medium


half-angle of the collection cone




magnification of objective lens


diameter of point spread function


particle diameter


image diameter of particle


depth of field of objective


measurement depth


time spacing between laser pulses


exposure time


dynamic viscosity of fluid


Boltzmann constant




diffusion coefficient

u, v, w

x-, y-, z-components of time-averaged velocity

Δx, Δy, Δz

displacements along x-, y-, and z-dimensions

σx, σy

root-mean-square diffusion distances in the x- and y-dimensions

εx, εy

relative error caused by Brownian motion in the x- and y-dimensions


probability density function

x0, y0

location of center of particle image


standard deviation (representative radius) of particle image


cross-correlation coefficient


correlation coefficient threshold



The authors would like to thank Mr. Daniel Laser and Prof. Thomas Kenny of the Mechanical Engineering Department of Stanford University for the use of their silicon microchannel system, and ACLARA BioSciences for the use of several acrylic microchannel systems. Shankar Devasenathipathy is supported by an Agilent Technologies PhD fellowship. This research was supported by the Defense Advanced Research Projects Agency under contracts F33615-98-1-2853 and F30602-98-2-0178, and by the National Science Foundation under Grant No. CTS-9874839.


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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  • S. Devasenathipathy
    • 1
    Email author
  • J. G. Santiago
    • 1
  • S. T. Wereley
    • 2
  • C. D. Meinhart
    • 3
  • K. Takehara
    • 4
  1. 1.Department of Mechanical Engineering, Thermosciences DivisionStanford UniversityStanfordUSA
  2. 2.Department of Mechanical EngineeringPurdue UniversityWest LafayetteUSA
  3. 3.Department of Mechanical and Environmental EngineeringUniversity of CaliforniaSanta BarbaraUSA
  4. 4.Department of Civil EngineeringKinki UniversityHigashi-Osaka 577-8502Japan

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