Biomedical Microdevices

, 20:87 | Cite as

Silicon membrane filter designed by fluid dynamics simulation and near-field stress analysis for selective cell enrichment

  • Yo-Chang Jang
  • Hyun-Ju Park
  • Ayoung Woo
  • Kyu-Sung Lee
  • Hui-Sung MoonEmail author
  • Jin Ho OhEmail author
  • Min-Young LeeEmail author


Selective cell enrichment technologies can play an important role in both diagnostic and therapeutic areas. However, currently used cell sorting techniques have difficulties in rapidly isolating only the desired target cells from a large volume of body fluids. In this work, we developed a filtering system that can quickly separate and highly concentrate cells from a large volume of solution, depending on their size, using a silicon membrane filter. To overcome the problems caused by material limitations of the brittle silicon, we designed a novel membrane filter with various pore designs. From these designs, the most optimal design with high pore density, while preventing crack formation was derived by applying fluid dynamics simulation and near-field stress analysis. The membrane filter system using the selected design was fabricated, and cell filtration performance was evaluated. The LNCaP cell in horse blood was recovered up to 86% and enriched to 187-fold compared to initial cell populations after filtration at a flow rate of 5 mL/min. The results demonstrate that the filter presented in this study can rapidly and selectively isolate target cells from a large volume of body fluid sample.


Membrane filter Silicon Fluid dynamics simulation Near-field stress analysis Selective cell enrichment 



This research was supported by the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Ministry of Science, ICT (2017M3A9E4063814), and the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health & Welfare, Republic of Korea (HI14C3229).


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Medical Device Management and Research, Samsung Advanced Institute of Health Sciences and TechnologySungkyunkwan UniversitySeoulSouth Korea
  2. 2.Smart Healthcare Medical Device Research CenterSamsung Medical CenterSeoulSouth Korea
  3. 3.Samsung Genome InstituteSamsung Medical CenterSeoulSouth Korea
  4. 4.Samsung ElectronicsSamsung Biomedical Research Institute, Samsung Advanced Institute of TechnologySeoulSouth Korea

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