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Automated design of a 3D passive microfluidic particle sorter.

Kuan-Ming LaiZhenya LiuYidan ZhangJunchao WangTsung-Yi Ho
Published in: Biomicrofluidics (2023)
Microfluidic chips that can sort mixtures of cells and other particles have important applications in research and healthcare. However, designing a sorter chip for a given application is a slow and difficult process, especially when we extend the design space from 2D into a 3D scenario. Compared to the 2D scenario, we need to explore more geometries to derive the appropriate design due to the extra dimension. To evaluate sorting performance, the simulation of the particle trajectory is needed. The 3D scenario brings particle trajectory simulation more challenges of runtime and collision handling with irregular obstacle shapes. In this paper, we propose a framework to design a 3D microfluidic particle sorter for a given application with an efficient 3D particle trajectory simulator. The efficient simulator enables us to simulate more samples to ensure the robustness of the sorting performance. Our experimental result shows that the sorter designed by our framework successfully separates the particles with the targeted size.
Keyphrases
  • high throughput
  • circulating tumor cells
  • healthcare
  • single cell
  • virtual reality
  • induced apoptosis
  • machine learning
  • signaling pathway
  • drug delivery