Analysis and Design Optimization of Micromixers (Paperback)

· 제목 : Analysis and Design Optimization of Micromixers (Paperback) 
· 분류 : 외국도서 > 과학/수학/생태 > 과학 > 역학 > 유체역학
· ISBN : 9789813342903
· 쪽수 : 65쪽
· 출판일 : 2020-12-08

1.     1. Mixing at Microscale

 

Micromixers are important components of lab-on-a-chip and micro-total analysis systems (μ-TAS) used for a variety of chemical and biological applications such as sample preparation and analysis, protein folding, DNA analysis, cell separation, among others. Due to small characteristics dimension of the micromixers, the flow is laminar with Reynolds number ranging from 0.01 to 100 for typical microfluidic applications. In microfluidic devices, the laminar flow condition poses a challenge for the mixing of liquid samples. Mixing is dominated by molecular diffusion, and the time scale for diffusion based on the characteristic length scale of microchannels and typical values of diffusivity constant encountered in microfluidic applications is much higher than the timescales associated with fluid motion. This limitation results in prohibitively long channel lengths to achieve complete mixing. Therefore, for high performance lab-on-a-chip and micro-total analysis systems (μ-TAS), it is essential to develop and devise methods to achieve fast and compact mixing at the micro-scale. This chapter provides an introduction to application of micromixers, flow dynamics and mixing in micromixers, and use of dimensionless numbers to characterize flow and mixing regimes.

 

2.     2. Active and Passive micromixers

 

Micromixers are classified into two types: active and passive. The active type promotes mixing using moving parts or some external agitation/energy to stir the fluids. Magnetic energy, electrical energy, pressure disturbance, and ultrasonic are some of the applied sources of external energy to enhance mixing inside the microchannel. Passive micromixers use geometrical modification to cause chaotic advection or lamination to promote the mixing of the fluid samples, and allow easy fabrication and integration with lab-on-a-chip and micro-total analysis systems (μ-TAS). In this chapter, both active and passive types will be discussed, but the major emphasis will be laid on passive micromixer designs and mechanisms. Passive micromixers will be categorized based on the mixing mechanism employed viz. chaotic advection, flow separation, hydrodynamic focusing, and split-and-recombine flows.

 

3.     3. Computational analysis of flow and mixing in micromixers

 

This chapter discusses the computational framework for the analysis of flow and mixing in micromixers. It aims to provide a detailed analysis on the different numerical techniques applied to the design of micromixers. Flow and mixing analysis will be based on both the Eulerian and Lagrangian approaches; relative advantages and disadvantages of the two methods and suitability to different types of mixing problems will be analysed.  The chapter will also discuss the various facets of numerical schemes subjected to discretization errors and computational grid requirements. Since a large number of studies are based on commercial computational fluid dynamics (CFD) packages, relevant details of these packages to the mixing problem using them will be presented. The chapter will conclude with mixing characterization techniques using velocity and concentration data obtained on a finite computational grid, and form the basis for performance evaluation of different micromixer designs.

 

4.     4. Design optimization of micromixers

 

The mixing performance of passive micromixers is sensitive to geometrical shape of flow passage. Therefore, it is important to determine optimal configuration which will maximize the mixing performance of micromixers.  But unfortunately, in some micromixers, enhancement of mixing performance is accompanied by a corresponding increase in pressure drop and thereby affects the overall performance of the micromixers. Therefore, it is important to determine several configurations which represent the trade-off between mixing efficiency and pressure drop penalty. Numerical optimization techniques coupled with CFD analysis of flow and mixing have proved to be an important tool for micromixers design. These techniques will be presented briefly, and focus will be on emphasizing the coupling between CFD code and optimization methodology throughout the design process.

 

5.     5. Epilogue

This chapter will summarize the details of what has been covered in the previous chapters, and how to pursue this research further.

 

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