A comparative study: conventional and modified serpentine micromixers
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Ranjitsinha R. Gidde
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Sandeep S. Wangikar
Abstract
The study of flow and mixing dynamics for conventional micromixers as well as micromixers with split and recombine (SAR) units has been carried out using laminar and transport diluted physics modules. Initially, a pilot numerical analysis was done for the basic Y-shaped curved, rectangular and triangular serpentine micromixers. Later, SAR units have been added to these basic designs and the effect of SAR units on the performance characteristics viz., mixing index, pressure drop, performance index and pumping power has been studied. In-depth qualitative analysis was also carried out to visualize the flow and mixing dynamics for the Reynolds number in the range from 0.1–50. The study results revealed that the square shaped chambers and circular obstacle based rectangular serpentine micromixer (SCCO-RSM) demonstrated better performance as compared to the other designs. The proposed micromixer is the better candidate for microfluidics applications such as Lab-On-a-Chip (LOC), Micro-Total-Analysis-Systems (µTAS) and Point of Care Testing (POCT), etc.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
1. Ta, BQ, Le Thanh, H, Dong, T, Thoi, TN, Karlsen, F. Geometric effects on mixing performance in a novel passive micromixer with trapezoidal-zigzag channels. J Micromech Microeng 2015;25:094004.10.1088/0960-1317/25/9/094004Search in Google Scholar
2. Okuducu, MB, Aral, MM. Novel 3-d t-shaped passive micromixer design with helicoidal flows. Processes 2019;7:637. https://doi.org/10.3390/pr7090637.Search in Google Scholar
3. Shah, I, Kim, SW, Kim, K, Doh, YH, Choi, KH. Experimental and numerical analysis of Y-shaped split and recombination micro-mixer with different mixing units. Chem Eng J 2019;358:691–706. https://doi.org/10.1016/j.cej.2018.09.045.Search in Google Scholar
4. Chen, X, Shen, J. Design and simulation of a chaotic micromixer with diamond-like micropillar based on artificial neural network. Int J Chem React Eng 2017;15. https://doi.org/10.1515/ijcre-2016-0039.Search in Google Scholar
5. Julius, LAN, Jagannadh, VK, Michael, IJ, Srinivasan, R, Gorthi, SS. Design and validation of on-chip planar mixer based on advection and viscoelastic effects. BioChip J 2016;10:16–24. https://doi.org/10.1007/s13206-016-0103-1.Search in Google Scholar
6. Rakoczy, R, Przybył, A, Kordas, M, Konopacki, M, Drozd, R, Fijałkowski, K. The study of influence of a rotating magnetic field on mixing efficiency. Chem Eng Process: Process Intensif 2017;112:1–8. https://doi.org/10.1016/j.cep.2016.12.001.Search in Google Scholar
7. Rashidi, S, Bafekr, H, Valipour, MS, Esfahani, JA. A review on the application, simulation, and experiment of the electrokinetic mixers. Chem Eng Process Process Intensif 2018;126:108–22. https://doi.org/10.1016/j.cep.2018.02.021.Search in Google Scholar
8. Luo, J, Fu, YQ, Milne, W. Acoustic wave based microfluidic and lab-on-chip. In: Meas. methods acoust. waves acoust. microdevices. London, UK: IntechOpen Book Series; 2013:515–56 pp.Search in Google Scholar
9. Biswas, SK, Das, T, Chakraborty, S. Nontrivial augmentations in mixing performance through integrated active and passive mixing in serpentine microchannels. J Appl Phys 2012;111:054904. https://doi.org/10.1063/1.3689808.Search in Google Scholar
10. Alam, A, Afzal, A, Kim, KY. Mixing performance of a planar micromixer with circular obstructions in a curved microchannel. Chem Eng Res Des 2014;92:423–34. https://doi.org/10.1016/j.cherd.2013.09.008.Search in Google Scholar
11. Ward, K, Fan, ZH. Mixing in microfluidic devices and enhancement methods. J Micromech Microeng 2015;25:094001. https://doi.org/10.1088/0960-1317/25/9/094001.Search in Google Scholar PubMed PubMed Central
12. Mondal, B, Mehta, SK, Patowari, PK, Pati, S. Numerical study of mixing in wavy micromixers: comparison between raccoon and serpentine mixer. Chem Eng Process Process Intensif 2019;136:44–61. https://doi.org/10.1016/j.cep.2018.12.011.Search in Google Scholar
13. Cortes-Quiroz, CA, Azarbadegan, A, Zangeneh, M. Effect of channel aspect ratio of 3-D T-mixer on flow patterns and convective mixing for a wide range of Reynolds number. Sensor Actuator B Chem 2017;239:1153–76. https://doi.org/10.1016/j.snb.2016.08.116.Search in Google Scholar
14. Kathuria, SV, Chan, A, Graceffa, R, Paul Nobrega, R, Robert Matthews, C, Irving, TC, et al.. Advances in turbulent mixing techniques to study microsecond protein folding reactions. Biopolymers 2013;99:888–96. https://doi.org/10.1002/bip.22355.Search in Google Scholar PubMed PubMed Central
15. Tran-Minh, N, Dong, T, Karlsen, F. An efficient passive planar micromixer with ellipse-like micropillars for continuous mixing of human blood. Comput Methods Progr Biomed 2014;117:20–9. https://doi.org/10.1016/j.cmpb.2014.05.007.Search in Google Scholar PubMed
16. Chen, X, Li, T, Zeng, H, Hu, Z, Fu, B. Numerical and experimental investigation on micromixers with serpentine microchannels. Int J Heat Mass Tran 2016;98:131–40. https://doi.org/10.1016/j.ijheatmasstransfer.2016.03.041.Search in Google Scholar
17. Gidde, RR, Pawar, PM. Flow feature and mixing performance analysis of RB-TSAR and EB-TSAR micromixers. Microsyst Technol 2020;26:517–30. https://doi.org/10.1007/s00542-019-04498-w.Search in Google Scholar
18. Viktorov, V, Nimafar, M. A novel generation of 3D SAR-based passive micromixer: efficient mixing and low pressure drop at a low Reynolds number. J Micromech Microeng 2013;23:055023. https://doi.org/10.1088/0960-1317/23/5/055023.Search in Google Scholar
19. Gidde, RR. Concave wall-based mixing chambers and convex wall-based constriction channel micromixers. Int J Environ Anal Chem 2019:1–23. https://doi.org/10.1080/03067319.2019.1669585.Search in Google Scholar
20. Gidde, RR. On the computational analysis of short mixing length planar split and recombine micromixers for microfluidic applications. Int J Environ Anal Chem 2019:1–16. https://doi.org/10.1080/03067319.2019.1660875.Search in Google Scholar
21. Xu, J, Chen, X. Mixing performance of a fractal-like tree network micromixer based on Murray’s law. Int J Heat Mass Tran 2019;141:346–52. https://doi.org/10.1016/j.ijheatmasstransfer.2019.06.070.Search in Google Scholar
22. Yeh, SI, Sheen, HJ, Yang, JT. Chemical reaction and mixing inside a coalesced droplet after a head-on collision. In: Microfluidics and nanofluidics. Springer Nature; 2015;18:1355–63 pp.10.1007/s10404-014-1534-4Search in Google Scholar
23. Jung, Y, Hyun, JC, Choi, J, Atajanov, A, Yang, S. Manipulation of cells’ position across a microfluidic channel using a series of continuously varying herringbone structures. Micro Nano Syst Lett 2017;5:1–8. https://doi.org/10.1186/s40486-016-0040-8.Search in Google Scholar
24. Sackmann, EK, Fulton, AL, Beebe, DJ. The present and future role of microfluidics in biomedical research. Nature 2014;507:181–9. https://doi.org/10.1038/nature13118.Search in Google Scholar PubMed
25. Li, Y, Xuan, J, Hu, R, Zhang, P, Lou, X, Yang, Y. Microfluidic triple-gradient generator for efficient screening of chemical space. Talanta 2019;204:569–75. https://doi.org/10.1016/j.talanta.2019.06.018.Search in Google Scholar PubMed
26. Kastania, AS, Tsougeni, K, Papadakis, G, Gizeli, E, Kokkoris, G, Tserepi, A, et al.. Plasma micro-nanotextured polymeric micromixer for DNA purification with high efficiency and dynamic range. Anal Chim Acta 2016;942:58–67. https://doi.org/10.1016/j.aca.2016.09.007.Search in Google Scholar PubMed
27. Lee, CY, Fu, LM. Recent advances and applications of micromixers. Sensor Actuator B Chem 2018;259:677–702. https://doi.org/10.1016/j.snb.2017.12.034.Search in Google Scholar
28. Liu, C, Li, Y, Liu, BF. Micromixers and their applications in kinetic analysis of biochemical reactions. Talanta 2019:120136. https://doi.org/10.1016/j.talanta.2019.120136.Search in Google Scholar PubMed
29. Martínez-López, JI, Mojica, M, Rodríguez, CA, Siller, HR. Xurography as a rapid fabrication alternative for point-of-care devices: assessment of passive micromixers. Sensors 2016;16:705.10.3390/s16050705Search in Google Scholar PubMed PubMed Central
30. Chen, K, Lu, H, Sun, M, Zhu, L, Cui, Y. Mixing enhancement of a novel C-SAR microfluidic mixer. Chem Eng Res Des 2018;132:338–45. https://doi.org/10.1016/j.cherd.2018.01.032.Search in Google Scholar
31. Gidde, RR, Pawar, PM, Gavali, SR, Salunkhe, SY. Flow feature analysis of an eye shaped split and collision (ES-SAC) element-based micromixer for lab-on-a-chip application. Microsyst Technol 2019;25:2963–73. https://doi.org/10.1007/s00542-018-4271-x.Search in Google Scholar
32. Hossain, S, Kim, KY. Mixing analysis of passive micromixer with unbalanced three-split rhombic sub-channels. Micromachines 2014;5:913–28. https://doi.org/10.3390/mi5040913.Search in Google Scholar
33. Gidde, RR, Pawar, PM. Flow feature analysis of T-junction wavy micromixer for mixing application. Int J Chem React Eng 2019;17. https://doi.org/10.1515/ijcre-2018-0306.Search in Google Scholar
34. Cortes-Quiroz, CA, Azarbadegan, A, Zangeneh, M. Evaluation of flow characteristics that give higher mixing performance in the 3-D T-mixer versus the typical T-mixer. Sensor Actuator B Chem 2014;202:1209–19. https://doi.org/10.1016/j.snb.2014.06.042.Search in Google Scholar
35. Xia, GD, Li, YF, Wang, J, Zhai, YL. Numerical and experimental analyses of planar micromixer with gaps and baffles based on field synergy principle. Int Commun Heat Mass Tran 2016;71:188–96. https://doi.org/10.1016/j.icheatmasstransfer.2015.12.029.Search in Google Scholar
36. Chen, X, Li, T, Hu, Z. A novel research on serpentine microchannels of passive micromixers. Microsyst Technol 2016;23:2649–56. https://doi.org/10.1007/s00542-016-3060-7.Search in Google Scholar
37. Gidde, RR. Design optimization of micromixer with circular mixing chambers (M-CMC) using Taguchi-based grey relational analysis. Int J Chem React Eng 2020. https://doi.org/10.1515/ijcre-2020-0057.Search in Google Scholar
38. Gidde, RR. On effects of shape, aspect ratio and position of obstacle on the mixing enhancement in micromixer with hexagonal-shaped chambers. Int J Chem React Eng 2020. https://doi.org/10.1515/ijcre-2020-0054.Search in Google Scholar
39. Capretto, L, Cheng, W, Hill, M, Zhang, X. Micromixing within microfluidic devices, Berlin, Heidelberg; Microfluidics Springer; 2011:27–68 pp.10.1007/128_2011_150Search in Google Scholar PubMed
40. Rezk, AR, Qi, A, Friend, JR, Li, WH, Yeo, LY. Uniform mixing in paper-based microfluidic systems using surface acoustic waves. Lab Chip 2012;12:773–9. https://doi.org/10.1039/c2lc21065g.Search in Google Scholar PubMed
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Articles in the same Issue
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- Statistical modeling and optimization of the bleachability of regenerated spent bleaching earth using response surface methodology and artificial neural networks with genetic algorithm
- Short Communication
- A comparative study: conventional and modified serpentine micromixers
Articles in the same Issue
- Frontmatter
- Research Articles
- Two-stage adsorber optimization of NaOH-prewashed oil palm empty fruit bunch activated carbon for methylene blue removal
- Response surface methodology (RSM) and artificial neural network (ANN) approach to optimize the photocatalytic conversion of rice straw hydrolysis residue (RSHR) into vanillin and 4-hydroxybenzaldehyde
- Computational investigation of erosion wear in the eco-friendly disposal of the fly ash through 90° horizontal bend of different radius ratios
- Optimal sequencing of conventional distillation column train for multicomponent separation system by evolutionary algorithm
- Enhanced design of PID controller and noise filter for second order stable and unstable processes with time delay
- Removal of glycerol from biodiesel using multi-stage microfiltration membrane system: industrial scale process simulation
- Multi-objective optimization of a fluid catalytic cracking unit using response surface methodology
- Effect of pipe rotation on heat transfer to laminar non-Newtonian nanofluid flowing through a pipe: a CFD analysis
- Statistical modeling and optimization of the bleachability of regenerated spent bleaching earth using response surface methodology and artificial neural networks with genetic algorithm
- Short Communication
- A comparative study: conventional and modified serpentine micromixers
