Study On Microfluidic Mixing Efficiency Under Low Reynolds Number

As we all know, the technology of micromixing is very important to"Lab-on-a-chip" or even the "μ-TAS". In order to improve the analytic speed ofbiochemical agents such as amino acid, protein and DNA, many researchers fromdifferent countries have done lots of simulations and experiments.In order todevelop new methods and achieve a better mixing effect and also try to find newtheory to support their research.Here, the main works completed in this paper are as following:Through reviewing the paper both domestic and abroad, this research chose"Mixing Index" as the criteria to evaluate the Mixing Efficiency. In other words,for a fixed mixing duration or a fixed length of mixing channel, a better MixingEfficiency means a bigger Mixing Index. The species chosen for simulation wereliquids with the properties of water at20 C and those properties were assumed tobe the same during the simulation. Simulations of micromixing in a typical 2dimensional T shaped micromixer model were processed under different velocityinlet boundary conditions.Here, each inlet's velocity was kept the same and ensured a very lowReynolds Number (Re<150) during the simulation. The results turns out to be poorwith the invariable velocity inlet boundary, the mixing was dominated strongly bythe diffusivity of these two components under those boundary conditions.Reynolds number is the key factor influencing the final mixing effect, here a lowerReynolds number means a lower velocity and the Mixing Efficiency is highlyrelated to the Reynolds number. The low velocity could support more time fordifferent liquids' contacting and thus the simulation could get a bigger MixingIndex. For example, the simulation with a velocity inlet boundary condition of0.002m/s could get a Mixing Index of 0.7664 within 2.5 seconds, here, mixingeffect was achieved through diffusivity only and a better mixing means a muchlonger mixing duration, so, It seemed that the Mixing Efficiency with invariableinlet boundary condition is always not great.In chapter 3, the velocity inlet condition was set to be periodical changingand the research on different key parameters about their influences to the finalMixing Efficiency was processed. Those key parameters were the averagevelocity, the disturb velocity, the frequency on each velocity inlet boundary andthe phasic difference between different inlets. With each parameter's changingtowards the increase of mixing effect, the Mixing Efficiency could get anenhancement of more than 10 times. For instance, when the phasic differencebetween those two inlets changed from 0 to 180 degrees, within 65 microsecondsthe Mixing Index increased from 0.05 to 0.12, this increase is very notable.Another simulation in the new model of a 2 dimensional mixing structurewas carried out. With the same choice of liquids in chapter 2, here, after 130microseconds' simulation, the Mixing Index increased from 0.3129 to 0.4939, theenhancement is nearly 20% compared with invariable velocity inlet boundarycondition. Besides this, it's clear that there exist a matching between the averagevelocity and the frequency of both inlet boundaries, a smaller period needs alower velocity to match, which could avoid the propagation of the instability tothe outlet of the channel.The model of a typical 3 dimensional T shaped chaotic mixing structure wasestablished in this chapter. Based on the research of the basic influence withdifferent periodical velocity inlet boundary conditions, "mean squared deviation"was chosen as the criteria to evaluate the Mixing Efficiency in this structure. Amethod to pickup the image's pixel value using the Image Processing Toolboxwas fixed on for data processing, then the simulation was carried out. Here,glycerol and pure water were chosen as a new pair of species for the simulationof micromixing and the properties of these two liquids were also assumed to bethe same during the process.The result of the simulation shows that the Mixing Efficiency underperiodical velocity inlet boundary condition is much higher than invariablevelocity inlet condition. The MSD decreased from 0.507 to 0.286 and theenhancement of Mixing Efficiency is nearly 100%, all those enhancement wasaccomplished within 12 microseconds in the inlet region of 12 micrometers' longin a mixing channel, so, I could conclude that the introduction of periodicalvelocity inlet boundary condition into chaotic mixing structure is really helpfuland the enhancement of the Mixing Efficiency is very notable.