Standardized Micro-Scale Mixing Evaluation

Guillermo González-Fernández

Benjamin Yang

Outline

• Introduction and Motivation• Project Goal and Success Measure• Raw Images• Image enhancement• Edge detection• Evaluation• Results• Custom area mixing evaluation

Introduction and Motivation

• Micro scale mixing crucial to success of many fields

• No standardized comparison• Characteristics in microfluidics

– Low Reynolds number– Laminar Flow– Diffusion Limited

Image: A.D. Strook et al., “Chaotic Mixer for Microchannels,” Science, vol 295, pp. 647-651, 2002

Project Goal and Success Measure

• Evaluate the extent of mixing in standardized experimental images

• Success will be based on correlation to existing simulation results

Standard Y-channel Square-wave channel Compartment channel

Raw Images

A B

C DE F G

Image enhancement (I)

• Why image enhancement? Better edge detection• Study the images: histogram, 2D-DFT…

• Apply Matlab filters

• Design new filters: • Min, med, max

• Contraharmonic

• New gaussian filter (gaussian iterations)

• Gaussian

• Sobel

• Prewitt

• Laplacian

• Log

• Unsharp

Image enhancement (II)

Min Max Med

Contraharmonic Gaussian iterations

Image enhancement (III)

• Cascade different combinations of the filters

• Final image obtained by averaging best results :– Average-gaussian-average

– Average-gaussian-gaussian

– Average-gaussian iterations-gaussian

– Average-gaussian iterations-average

Edge detection

• We don’t know the real edge!!

• Matlab edge detection strategies

• New strategies • Y channel: Perfect

boundary • Square channel:

General method

Edge detection

• We don’t know the real edge!!

• Matlab edge detection strategies

• New strategies • Y channel: Perfect

boundary • Square channel:

General method

Evaluation

• Extract part of the image we will evaluate

• Estimate mixing percentage

n

xxM

n

ii

11

Results

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.001 0.01 0.1 1 10

Flow Rate, m/s

Ex

ten

t o

f M

ixin

g

0

100

200

300

400

500

600

700

800

900

1000

Pre

ssu

re D

rop

, P

a

standard

zigzag

serpentine

square wave

compartment

Custom area mixing evaluation

• User defines the image to evaluate

• User defines area (rectangle) to evaluate

• Obtain mixing efficiency

References• [1] Bertsch, S. Heimgartner, P. Cousseau, and P. Renoud. “Static micromixers

based on large-scale industrial mixer geometry”, Lab on a Chip, Vol 1, pp 56-60, 2001.• [2] A.D. Strook et al., “Chaotic Mixer for Microchannels,” Science, vol 295, pp.

647-651, 2002• [3] R. H. Liu, M. A. Stremler, K. V. Sharp, M. G. Olsen, J. G. Santiago, R. J.

Adrian, H Aref, and D. J. Beebe. "Passive mixing in a three-dimensional serpentine microchannel", J. of MEMS, Vol 9, No. 2, pp 190-196, 2000.

• [4] V. Mengeaud, J. Josserand, and H. H. Girault. “Mixing processes in a zigzag microchannel: finite element simulations and optical study”, Analytical Chemistry, Vol 74, pp 4279-4286, 2002.

• [5] R. Gonzalez, R. Woods. Digital Image Processing, 2nd Edition. Prentice Hall, Upper Saddle River, N.J, 2002.

• [6] Kai Kang, R. Chevray. “Visualization of fluid mixing in microchannels”, IEEE Computer Graphics and Applications, Vol 25, Issue 6, pp 16-20, 2005.

• [7] Leming Shi, Weida Tong, Zhenqiang Su, et al. “Microarry scanner calibration curves: characteristics and implications”, BMC Bioinformatics, Vol 6, pp. 1-14, 2005

• [8] Peter A. C. ‘t Hoen, Rolf Turk, Judith M. Boer, et al. “Intensity-based analysis of two color microarrays”, Nucleic Acids Research, Vol 32, No 4, pp. e41-e47, 2004

Questions?