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Caged-Dye Imaging of Flows in Microfabricated Systems

Caged-Dye Imaging of Flows in Microfabricated Systems. Microfluidics Laboratory, Dept of Mechanical Engineering 2009 G. G. Brown Laboratory, 2350 Hayward Street, Ann Arbor MI 48109 Advisor : Ernest F. Hasselbrink, Jr. Students Taesung Kim (PhD) Sun Min Kim (PhD) Meng Ping Chang (PhD)

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Caged-Dye Imaging of Flows in Microfabricated Systems

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  1. Caged-Dye Imaging of Flows in Microfabricated Systems Microfluidics Laboratory, Dept of Mechanical Engineering 2009 G. G. Brown Laboratory, 2350 Hayward Street, Ann Arbor MI 48109 Advisor: Ernest F. Hasselbrink, Jr. Students Taesung Kim (PhD) Sun Min Kim (PhD) Meng Ping Chang (PhD) Sanghyun Lee (PhD) Donghyuck Kam (MS) Robert Bartz (MS) Anders Brask (visiting PhD, TUDenmark) Rachel Lance (BS) Alumni Jesse Kirchner, MS Sneha Madhavan-Reese, MS Jung Yim Min, visiting PhD student, KAIST Contact info: microflow.engin.umich.edu Lab phone 734-936-0343 Acknowledgments: NSF WIMS Center, DARPA/DSO, NIH/NIDCR, NASA JPL DRDF

  2. Microfluidics Lab Overview

  3. Electrokinetic pumping (MP Chang, A. Brask, R. Bartz) • Flux through a tube:

  4. O Capillary/channel R O Mask UV light monomer O O cross-linker Initiator/ solvent O O Mobile UV-lithographed Polymer Monoliths • “Ship-in-a-bottle” approach • Electrokinetic or DP mobilization • ~1 psi required for actuation • Material may be tailored for mechanical strength, charge, porosity, etc. (multi-component monomers & solvents) 50 mm

  5. bypass piston Ultimate Goal – mFluidic Engineering Toolbox • We want analogues of the basic functional units we are used to dealing with in the macroscale world • mvalves, mpipettes, actuators, injectors, regulators, etc… • Example: Check-Valve • Dual-level, dual-side HF etch • Photo-initiation at 355 nm

  6. Multi-Port Diverter (XOR gate) A inlet B inlet

  7. pistons pistons 10 nL Pipette load dispense sample inlet running column

  8. 10 nL Pipette – Fluorescence Imaging

  9. Introduction to caged-dye imaging

  10. Motivation: Standard dye imaging lacks spatial resolution due to diffusion Fluorescent dye imaging does not provide contrast over short enough length scales to resolve EOF/PDF components, or to reveal flow details over channel-diameter lengthscales ddiff ~ (2Defft)1/2 Viewing Region

  11. EOF vs. PDF geometric dispersion studies using caged dye EOF can have much lower dispersion … … unless you create sources of geometric dispersion P. H. Paul, unpublished P. H. Paul et al., Anal. Chem. 1998, vol 70 no.13, 2459

  12. UV light (<365nm) CMNCBZ-caged-carboxy-Q-rhodamine dye Uncaged-carboxy-Q-rhodamine dye Caged-Dye Imaging Process of uncaging caged-dye using UV light

  13. Caged Dye Imaging Apparatus • 20mm-thick sheet of 355nm light uncages dye • Array of pulsed blue LED’s (lc=460nm) or inverted fluorescence microscope Hg lamp induces fluorescence of uncaged dye (lc=540nm).

  14. Caged Dye Imaging Apparatus

  15. 500μm Caged Dye Imaging Example

  16. Caged Dye Imaging Example

  17. 500μm Caged Dye Imaging Example

  18. 500μm 500μm Caged Dye Imaging Example

  19. Practical Caged Dye Notes • Dextran, 5-(and-6)-carboxy-Q-rhodamine, CMNCBZ-caged dye, anionic : 10,000MW, 5mg-155.00$, D34678 (probes.com) • Dextran, DMNB-caged fluorescein, anionic : 10,000MW, 5mg-155.00$, D3310 (probes.com) • Dextran, DMNB-caged fluorescein and biotin, lysine fixable : 70,000MW, 5mg-254.00$, D7147 (probes.com) • Typical preparation: • Buffer solution: pH 8.0+, 5mM+ ionic strength • Concentration: ~1 mg/mL or less • Keeping: T< -20 oC.

  20. Particle Imaging Method for a Velocity Field (PIV)

  21. Principle of Particle Imaging Velocimetry t=t0 t=t0+dt • Images of particles at different times are recorded on a camera. • By measuring the particle displacements, the motion of the fluid can be ascertained. • Tracer particles follow the fluid motion. • Tracer particles are distributed homogeneously and properly.

  22. Particle Imaging Procedure Experimental Setup Image Processing Preprocessing Seeding Interrogation & Correlation Fluid Flow Velocity Field Illumination Image capturing Postprocessing

  23. Flow In Flow Out Focal Plane (δz) << Ldepth δz ~ 2.0um in 60x w/ immersion oil δz ~ 8.0um in 40x w/o immersion oil Microscope Objective / CCD Camera (1332X1024 16bit) Particle Imaging Experimental Setup Ldepth Trasparent material (e.g., glass) 1. single frame/multi-exposure 2. multi-frame/single exposure

  24. - = Image Processing - Preprocessing Subtraction of Background Noise The most important image processing that should be done prior to any others. Courtesy of S.H. Lee

  25. Image Processing - Interrogation T=t2 T=t1 • PTV (Particle Tracking Velocimetry) - Tracking each particle movementwith time  Velocity • PIV (Particle Image Velocimetry) - The images are divided into small subsections, interrogation areas(~10particles/IA), and then average interrogation movement with time Velocity

  26. y x Image Processing –Cross/Auto Correlation - multi-frame/single exposure Cross Correlation Displacement = Center to Peak - single frame/multi-exposure Auto Correlation Displacement = Center to either of peaks  Directional Ambiguity Fromhttp://www.ph.ed.ac.uk/~ted/thesis/node41.html

  27. Image Processing - PIV Sleuth

  28. Image Processing Result using PIV Sleuth Courtesy of S.H. Lee

  29. Error Sources • Too high particle density  Background noise from out-of-focus particles reduce the visibility of in-focus paricles. • Too low particle density  Standard cross correlation techniques will fail to provide an adequate signal. • Microchannel  Focal plane depth should be carefully considered. • Brownian motion for a single particle < 3% full-scale error.

  30. Practical Particle Imaging Notes • General PIV Overview (http://www.ph.ed.ac.uk/~ted/thesis/node32.html ) • PIV Sleuth (free software and manual download http://ltcf.tam.uiuc.edu/) • Matlab m.file for PIV(http://matlabpiv.sourceforge.net/) • Particle Purchase • Molecular Probes (http://www.probes.com) • Fluo spheres carboxylate-modified microspheres 0.1um Yellow-Green fluorescent ($191.00)

  31. Reference Papers • Adrian RJ (1991) Particle Imaging techniques for experimental fluid mechanics, Ann Rev Fluid Mech 23:261-304. • Prasad AK, Adrian RJ, Landreth CC, Offutt PW (1992) Effect of resolution on the speed and accuracy of particle image velocimetry interrogation, Exp Fluids 13:105-116. • Meinhart CD, Wereley ST, Santiago JG, (1999) PIV measurements of a microchannel flow, Exp Fluids 27:414-419 • Devasenathipathy S, Santiago JG, Wereley ST, Meinhart CD, Takehara K, (2003) Paricle imaging technique for microfabricated fluidic systems, Exp. Fluids 34:504-514

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