Characterization techniques - Micromixers Fundamentals Design and Fabrication - page 311

[x, y] ¼ getline(image_handle);
x ¼ round(x);
y ¼ round(y);
%Getting intensity values in vector c
c ¼ improfile(I, x, y); c ¼ c ' ;
%Getting the total number of pixel in the line
L ¼ length(c);
%Normalizing the spacial variable
%and the concentration
for i 1:L

ystar(i)

¼

¼ (i-1) /L;

(c(i)-cmin) / (cmax-cmin);
end figure
%Plotting the dimensionless concentration distribution
plot(ystar, c, ' - ' );
In the above MATLAB code, cmax and cmin are intensity values of unmixed fluids. The line of interest
is selected from the displayed image using the computer mouse. The resulting concentration profiles
are similar to those in the lower part of Fig. 8.11 .

c(i) ¼

8.3 QUANTIFICATION METHODS FOR MICROMIXERS
8.3.1 Direct statistical methods
The normalized concentration is assumed to be the same as the normalized intensity values of the
recorded image:

I min
I max

I

c ¼ I ¼

I min :

(8.27)

The above assumption is only valid for a dilute fluorescence solution. At a concentration higher than
approximately 50 mM, the fluorescence is saturated. Photo-bleaching also needs to be considered in
measurements using fluorescence dyes. Further techniques for normalizing intensity values of
the recorded image using the background image I bg , flat field image I flat field , and dark field image
I dark field are

I bg
I flat field

I

I ¼

I bg :

(8.28)

I dark field
I flat field

I

I ¼

I dark field :

(8.29)

In large-scale mixers, the mixedness or the degree of uniformity is measured by analyzing the spot
sample taken from the mixed product. Due to the small scale involved and the inaccessibility of the
sample in a micromixer, the analysis relies on images taken by microscopy. Thus, a pixel array taken
from the region of interest (ROI) of the image represents the spot sample. The smallest spot sample is
the pixel itself. In cases of a fluorescence image where the intensity represents the concentration, the
intensity value of the sample is compared to the expected value. The difference between the