Predictive Model for Cell Positioning during Periodic Lateral Migration in Spiral Microchannels
The periodic lateral migration of submicrometer cells is the primary factor leading to low precision in a spiral microchannel during cell isolation. In this study, a mathematical predictive model (PM) is derived for the lateral position of cells during the periodic lateral migration process. We analyze the relationship of migration period, migration width, and starting point of lateral migration with microchannel structure and flow conditions and determine the empirical coefficients in PM. Results indicate that the aspect ratio of the microchannel and the Reynolds number (<i>Re</i>) are key factors that influence the periodicity of the cell lateral migration. The lateral migration width is jointly affected by <i>Re</i>, the cell blockage ratio, and the microchannel curvature radius. The inlet structure of the microchannel and the ratio of the cell sample to the sheath flow rate are critical parameters for regulating the initial position. Moreover, the structure of the pressure field at the inlet constrains the distribution range of the starting point of the lateral migration. Regardless of whether the particles/cells undergo 0.5, 1, or multiple lateral migration cycles, the lateral positions predicted by PM align well with the experimental observations, thus verifying the accuracy of PM. This research helps to elucidate the characteristics of periodic lateral migration of cells in spiral microchannels and can provide practical guidance for the development and optimization of miniature spiral microchannel chips for precise cell isolation.
Authors
- Siyu Zhao (ORCID: https://orcid.org/0000-0001-8021-9237)
- Kai Zheng (ORCID: https://orcid.org/0000-0001-7266-7080)
- Fanming Cai (ORCID: https://orcid.org/0000-0002-6436-0035)
- Zhaomiao Liu (ORCID: https://orcid.org/0000-0002-3408-595X)
- Nan Zheng (ORCID: https://orcid.org/0000-0001-9765-5297)
- Xiang Wang (ORCID: https://orcid.org/0000-0001-6144-9301)
- Chenchen Zhang (ORCID: https://orcid.org/0009-0003-6900-8289)
- Yan Pang
Institutions
- Beijing University of Technology (CN)
Publication Details
- Journal
- Analytical Chemistry
- Published
- 2024-10-22
- DOI
- https://doi.org/10.1021/acs.analchem.4c04456
- Citations
- 4
- Primary Topic
- Microfluidic and Bio-sensing Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.74
Funders
- National Natural Science Foundation of China
- Beijing Municipal Natural Science Foundation