Single Red Blood Cell Hydrodynamic Traps via the Generative Design

Abstract

This paper describes a generative design methodology for a micro hydrodynamic single-RBC (red blood cell) trap for applications in microfluidics-based single-cell analysis. One key challenge in single-cell microfluidic traps is to achieve desired through-slit flowrates to trap cells under implicit constraints. In this work, the cell-trapping design with validation from experimental data has been developed by the generative design methodology with an evolutionary algorithm. L-shaped trapping slits have been generated iteratively for the optimal geometries to trap living-cells suspended in flow channels. Without using the generative design, the slits have low flow velocities incapable of trapping single cells. After a search with 30,000 solutions, the optimized geometry was found to increase the through-slit velocities by 49%. Fabricated and experimentally tested prototypes have achieved 4 out of 4 trapping efficiency of RBCs. This evolutionary algorithm and trapping design can be applied to cells of various sizes.

Advances in Microfluidics for Single Red Blood Cell Analysis

“…Grigorev et al applied Evolutionary approach for hydrodynamic traps design and achieved 4 out of 4 trapping efficiency of RBCs (within one FOV) in the fabricated and tested chip, after 30,000 solutions search. The optimized geometry was found to increase the throughslit velocities by 49% [353]. AI applied to the microfluidics design problems remains to be one of the potential growth areas in the near future [354].…”

Editorial for the Special Issue on Micro/Nanofluidic and Lab-on-a-Chip Devices for Biomedical Applications

“…Because of their adaptability, feasibility, and cost-efficiency, these devices can revolutionize the future of preclinical technologies. Furthermore, they allow insights into the performance and toxic effects of responsive drug delivery nanocarriers to be obtained, which consequently allow the shortcomings of two/three-dimensional static cultures and animal testing to be overcome and help to reduce drug development costs and time [ 2 , 3 , 4 ]. With the constant advancements in biomedical technology, the development of enhanced microfluidic devices has accelerated, and numerous models have been reported.…”

“…The optimization of microfluidic devices has also been explored by some authors. Grigorev et al [ 3 ] investigated how to achieve adequate flow rates for trapping single cells in a microfluidic chip. The authors applied a generative design methodology with an evolutionary algorithm and validated the device with experimental data.…”