Numerical investigation of droplet generation process in symmetric and asymmetric cross-junction microchannels

LI Xiang; LI Yan; LI Yingyan; DONG Zhiqiang; ZHUANG Xiaoru; ZHONG Zhigang; YU Peng

doi:10.7498/aps.74.20250474

Abstract

Droplet microfluidics technology possesses significant potential applications in chemical analysis, biological detection, and material preparation. Passive droplet generation method can rapidly achieve droplet formation by using the geometric characteristics of microchannels and shear flow. As a typical structure, the influences of fluid parameters and symmetry differences in cross microchannels on the droplet generation process have not been fully studied. Therefore, this paper uses the lattice Boltzmann method to numerically simulate droplet generation in symmetric and asymmetric cross microchannels, thereby systematically analyzing the action mechanisms of capillary number, viscosity ratio, and microchannel symmetry. First, this study verifies the computational reliability of the numerical model through two classic cases, i.e. the droplet deformation under planar shear flow and stationary droplets on ideal solid surfaces. Then, this work focuses on studying the three flow stages in symmetric cross microchannels, i.e. interface immersion stage, shear-induced breakup stage, and the droplet migration and coalescence stage, and analyzes the synergistic mechanism of capillary number and viscosity ratio. In the symmetric cross microchannel structure, the capillary number is the main factor determining the droplet size in the cross microchannel. With the increase of the capillary number, the surface tension gradually weakens, causing the liquid bridge at the droplet neck to break more easily and generate droplets. In contrast, the effect of the viscosity ratio on the droplet size is relatively small, but it can suppress the generation of sub-droplets and improve the uniformity of droplets by adjusting the viscous resistance of the continuous phase. On this basis, this study further quantifies the influence of microchannel symmetry on the droplet generation process in cross microchannels. In the asymmetric cross microchannel structure, the microchannel deviation breaks the flow symmetry and weakens the cooperative shearing effect of the oil-phase fluid on the immersion structure of the water-phase fluid. When the microchannel deviates within the centerline range of the water-phase microchannel, the droplet size increases significantly with the increase of the microchannel deviation. This is mainly because the oil-phase fluid on the side far from the deviation first squeezes the immersion structure of the water-phase fluid, and then the oil-phase fluid near the deviation side exerts a secondary squeeze on the immersion structure, causing the neck liquid bridge of the immersion structure to continuously elongate and the shear position to shift along the microchannel deviation direction. When the microchannel deviation exceeds the centerline position of the water-phase microchannel, the interface fracture of the water-phase immersion structure mainly relies on the double squeezing effect of the oil-phase fluid and the surface tension of water-phase fluid, and the droplet size tends to be stable. The relevant research results lay a theoretical foundation for microchannel design and fluid parameter regulation in droplet microfluidics and thus further promote the application and development of droplet microfluidic technology.

Keywords:

Authors and contacts

1.
Guangdong Provincial Key Laboratory of Turbulence Research and Applications, Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen 518055, China
2.
Key Laboratory of Icing and Anti/De-icing, China Aerodynamics Research and Development Center, Mianyang 621000, China
3.
School of Mechanical and Electrical Engineering, Shenzhen Polytechnic University, Shenzhen 518055, China
4.
Shenzhen Foreach Technology Co., Ltd., Shenzhen 518132, China
5.
Shenzhen Key Laboratory of Complex Aerospace Flows, Shenzhen 518055, China

Corresponding author: YU Peng, yup6@sustech.edu.cn

Funds: Project supported by the Fund for Fostering Talents of the Shenzhen Science and Technology Innovation Commission, China (Grant No. RCBS20221008093107026), the National Natural Science Foundation of China (Grant Nos. 12302361, 12402328), the Open Fund Project of the Key Laboratory of Icing and Anti/De-icing of CARDC (Grant No. IADL20220302), the Shenzhen Natural Science Foundation, China (Grant No. JCYJ20240813094221028), the Department of Science and Technology of Guangdong Province, China (Grant Nos. 2025A1515010156, 2025A1515012960, 2023B1212060001), and the Shenzhen Key Laboratory of Complex Aerospace Flows, China (Grant No. ZDSYS201802081843517).

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References

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Cited By

图 1 平板剪切流动下的液滴初始位置示意图

Figure 1. A schematic diagram of the initial position of a droplet in a shear flow.

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图 2 剪切流动中不同Ca数下的液滴界面形状

Figure 2. Interface profiles of droplet in shear flow under different Ca number.

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图 3 毛细数Ca与液滴变形参数D的关系

Figure 3. Relation between Ca number and the deformation parameter of droplet.

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图 4 接触角的数值模拟结果与准确值和文献[44, 45]的对比

Figure 4. Comparisons between numerical contact angle with exact contact angle and published data [44, 45]

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图 5 对称十字微通道结构示意图

Figure 5. Schematic diagram of symmetric cross microchannel structure.

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图 6 不同毛细数Ca下十字微通道内的液滴生成过程

Figure 6. Droplet generation process in cross microchannels under different capillary numbers Ca.

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图 7 不同黏度比下, t*= 7.2时的十字微通道内液滴状态

Figure 7. Droplet shape in a cross microchannel at t*= 7.2 under different viscosity ratios.

DownLoad: Full-Size Img PowerPoint

图 8 不同黏度比下, 十字微通道内液滴长度随着毛细数变化的关系

Figure 8. The relationship between droplet size and capillary number in a cross microchannel under different viscosity ratios.

DownLoad: Full-Size Img PowerPoint

图 9 非对称十字微通道结构示意图

Figure 9. Schematic diagram of asymmetric cross microchannel structure.

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图 10 不同流道偏差下, t* = 7.2时的非对称十字微通道内液滴状态

Figure 10. Droplet shape in a cross microchannel at t* = 7.2 under different eccentricity values.

DownLoad: Full-Size Img PowerPoint

图 11 非对称十字微通道内液滴长度随着流道偏差变化的关系

Figure 11. Relationship between droplet size and channel deviation in an asymmetric cross microchannel.

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map

[1]	Zhu P, Wang L 2017 Lab Chip 17 34 Google Scholar
[2]	Cybulski O, Garstecki P, Grzybowski B A 2019 Nat. Phys. 15 706 Google Scholar
[3]	Chen P C, Wu M H, Wang Y N 2014 Microfluid. Nanofluid. 17 275 Google Scholar
[4]	Li X, Li D, Liu X, Chang H 2016 Sens. Actuators, B 229 466 Google Scholar
[5]	Theberge A B, Courtois F, Schaerli Y, Fischlechner M, Abell C, Hollfelder F, Huck W T S 2010 Angew. Chem. Int. Ed. 49 5846 Google Scholar
[6]	Teo A J T, Tan S H, Nguyen N T 2020 Anal. Chem. 92 1147 Google Scholar
[7]	Zhang Q, Li H, Zhu C, Fu T, Ma Y, Li H Z 2018 Colloids Surf. , A 537 572 Google Scholar
[8]	Jin S, Wei X, Liu Z, Ren J, Jiang Z, Abell C, Yu Z 2019 Sens. Actuators, B 291 1
[9]	Zhang H, Palit P, Liu Y, Vaziri S, Sun Y 2020 ACS Appl. Mater. Interfaces 12 26936 Google Scholar
[10]	Thorsen T, Roberts R W, Arnold F H, Quake S R 2001 Phys. Rev. Lett. 86 4163 Google Scholar
[11]	Zhang Y Y, Xia H M, Wu J W, Zhang J, Wang Z P 2019 Appl. Phys. Lett. 114 073701 Google Scholar
[12]	Zhang Y Y, Xia H M 2022 Sens. Actuators, B 368 132183 Google Scholar
[13]	Dreyfus R, Tabeling P, Willaime H 2003 Phys. Rev. Lett. 90 144505 Google Scholar
[14]	Tan Y C, Cristini V, Lee A P 2006 Sens. Actuators, B 114 350 Google Scholar
[15]	Chae S K, Lee C H, Lee S H, Kim T S, Kang J Y 2009 Lab Chip 9 1957 Google Scholar
[16]	Nisisako T, Hatsuzawa T 2010 Microfluid. Nanofluid. 9 427 Google Scholar
[17]	Liu H, Zhang Y 2011 Commun. Comput. Phys. 9 1235 Google Scholar
[18]	Rostami B, Morini G L 2019 Exp. Therm. Fluid Sci. 103 191 Google Scholar
[19]	Yu W, Liu X, Zhao Y, Chen Y 2019 Chem. Eng. Sci. 203 259 Google Scholar
[20]	Nozaki Y, Yoon D H, Furuya M, Fujita H, Sekiguchi T, Shoji S 2021 Sens. Actuators, A 331 112917 Google Scholar
[21]	Liu Z, Ma Y, Wang X, Pang Y, Ren Y, Li D 2022 Exp. Therm. Fluid Sci. 139 110739 Google Scholar
[22]	Umbanhowar P B, Prasad V, Weitz D A 2000 Langmuir 16 347 Google Scholar
[23]	Utada A S, Lorenceau E, Link D R, Kaplan P D, Stone H A, Weitz D A 2005 Science 308 537 Google Scholar
[24]	Garstecki P, Fuerstman M J, Whitesides G M 2005 Phys. Rev. Lett. 94 234502 Google Scholar
[25]	Deng C, Wang H, Huang W, Cheng S 2017 Colloids Surf. , A 533 1 Google Scholar
[26]	刘汉涛, 刘谋斌, 常建忠, 苏铁熊 2013 62 064705 Google Scholar Liu H T, Liu M B, Chang J Z, Su T X 2013 Acta Phys. Sin. 62 064705 Google Scholar
[27]	梁宏, 柴振华, 施保昌 2016 65 204701 Google Scholar Liang H, Chai Z H, Shi B C 2016 Acta Phys. Sin. 65 204701 Google Scholar
[28]	张晓林, 黄军杰 2023 72 024701 Google Scholar Zhang X L, Huang J J 2023 Acta Phys. Sin. 72 024701 Google Scholar
[29]	Wang W, Liu Z, Jin Y, Cheng Y 2011 Chem. Eng. J. 173 828 Google Scholar
[30]	Ngo I L, Dang T D, Byon C, Joo S W 2015 Biomicrofluidics 9 024107 Google Scholar
[31]	Liu H, Zhang Y 2011 Phys. Fluids 23 082101 Google Scholar
[32]	Boruah M P, Sarker A, Randive P R, Pati S, Sahu K C 2021 Phys. Fluids 33 122101 Google Scholar
[33]	Wang H, Yuan X, Liang H, Chai Z, Shi B 2019 Capillarity 2 32
[34]	Niu X D, Li Y, Ma Y R, Chen M F, Li X, Li Q Z 2018 Phys. Fluids 30 013302 Google Scholar
[35]	Li X, Dong Z Q, Li Y, Wang L P, Niu X D, Yamaguchi H, Li D C, Yu P 2022 Int. J. Multiphase Flow 149 103982 Google Scholar
[36]	Li X, Yu P, Niu X D, Li D C, Yamaguchi H 2021 Appl. Math. Comput. 393 125769
[37]	Qian Y H, Humières D D, Lallemand P 1992 Europhys. Lett. 17 479 Google Scholar
[38]	van der Graaf S, Nisisako T, Schroën C G P H, van der Sman R G M, Boom R M 2006 Langmuir 22 4144 Google Scholar
[39]	Ding H, Spelt P D M, Shu C 2007 J. Comput. Phys. 226 2078 Google Scholar
[40]	Liang H, Liu H, Chai Z, Shi B 2019 Phys. Rev. E 99 063306 Google Scholar
[41]	Shi Y, Tang G H, Xia H H 2014 Comput. Fluids 90 155 Google Scholar
[42]	Yue P, Feng J J, Liu C, Shen J 2004 J. Fluid Mech. 515 293 Google Scholar
[43]	Roths T, Friedrich C, Marth M, Honerkamp J 2002 Rheol. Acta 41 211 Google Scholar
[44]	Wang Y, Shu C, Huang H B, Teo C J 2015 J. Comput. Phys. 280 404 Google Scholar
[45]	Li X, Dong Z Q, Wang L P, Niu X D, Yamaguchi H, Li D C, Yu P 2023 Appl. Math. Modell. 117 219 Google Scholar

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