Enhancement Mechanism of Fish-Scale Surface Texture on Flow Switching and Mixing Efficiency in Microfluidic Chips
Source abstract
Abstract
Surface textures have a significant influence on surface-functional properties, which provide an alternative solution to create an accurate control of microfluidics flow. This paper studies the modulation ability of fish-scale surface textures on microfluidics flowing behavior on the ground of the early research on vibration machining-induced surface wettability variation. A microfluidic directional flow function is proposed by modifying the wall of the microchannel at the T-junction with different surface textures. The retention force caused by the surface tension difference between the two outlets in the T-junction is studied. In order to investigate the influence of fish-scale textures on the performance of the directional flowing valve and micromixer, T-shaped and Y-shaped microfluidic chips were fabricated. The experimental results indicated that with the aid of the fish-scale surface textures generated by vibration-assisted micromilling, directional liquid flow can be achieved at a specific input pressure range and the mixing efficiency of microfluidics can be improved dramatically.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Microfluidic and Capillary Electrophoresis Applications · Microfluidic and Bio-sensing Technologies · Fluid Dynamics and Thin Films
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Engineering, China Agricultural University, Beijing 100083, China
Centre for Precision Engineering, Harbin Institute of Technology, Harbin 150001, P. R. China
Mechanical Engineering, School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, U.K.
Funding
Engineering and Physical Sciences Research Council
References (30)
Show source-provided references
1. 10.1021/acs.langmuir.5b0032810.1021/acs.langmuir.5b00328 ↗
2. 10.1088/0960-1317/15/2/R0110.1088/0960-1317/15/2/R01 ↗
3. 10.1142/s233954781620004110.1142/s2339547816200041 ↗
4. 10.3390/MI1105045510.3390/MI11050455 ↗
5. 10.1039/b618851f10.1039/b618851f ↗
6. 10.1016/j.biotechadv.2007.05.00310.1016/j.biotechadv.2007.05.003 ↗
7. 10.1016/j.cep.2020.10798410.1016/j.cep.2020.107984 ↗
8. 10.1039/c3nr05865d10.1039/c3nr05865d ↗
9. 10.1021/la101750510.1021/la1017505 ↗
10. 10.1039/b915079j10.1039/b915079j ↗
11. 10.1002/adma.20080371010.1002/adma.200803710 ↗
12. 10.1002/adma.20130500110.1002/adma.201305001 ↗
13. 10.1021/ac010895d10.1021/ac010895d ↗
14. 10.1126/science.106623810.1126/science.1066238 ↗
15. 10.1039/c5lc00234f10.1039/c5lc00234f ↗
16. 10.1142/s233954781620004110.1142/s2339547816200041 ↗
17. 10.1016/j.precisioneng.2018.09.00610.1016/j.precisioneng.2018.09.006 ↗
18. 10.1016/j.ijmecsci.2017.12.03710.1016/j.ijmecsci.2017.12.037 ↗
19. 10.1088/1361-6439/aaa06f10.1088/1361-6439/aaa06f ↗
20. 10.1016/j.jmatprotec.2018.11.01110.1016/j.jmatprotec.2018.11.011 ↗
21. 10.1109/tmech.2020.297820910.1109/tmech.2020.2978209 ↗
22. 10.1088/0960-1317/26/6/06501710.1088/0960-1317/26/6/065017 ↗
23. 10.1007/s00170-013-4801-810.1007/s00170-013-4801-8 ↗
24. 10.1016/j.ijmecsci.2006.09.01210.1016/j.ijmecsci.2006.09.012 ↗
25. 10.1016/S0017-9310(99)00148-910.1016/S0017-9310(99)00148-9 ↗
26. Huo D. · 2013
27. 10.1016/j.snb.2011.09.05110.1016/j.snb.2011.09.051 ↗
28. 10.1039/c0lc00658k10.1039/c0lc00658k ↗
29. 10.1063/1.166940010.1063/1.1669400 ↗
30. 10.1103/PhysRevLett.85.98010.1103/PhysRevLett.85.980 ↗