Filter-less submicron hydrodynamic size sorting
1CNRS, LAAS, 7 avenue du colonel Roche, F-31400 Toulouse, France. pjoseph@laas.fr.
Lab on a Chip
|January 19, 2016
Summary
This study introduces a filter-less microfluidic device for separating submicron particles using hydrodynamic filtration. The innovative design achieves efficient particle sorting without clogging, offering a robust and simple solution.
Area of Science:
- Microfluidics
- Biotechnology
- Particle Separation
Background:
- Traditional particle separation methods often rely on filters, which can clog and limit throughput.
- Achieving precise separation of submicron particles from complex samples remains a challenge in microfluidic applications.
Purpose of the Study:
- To develop a simple, filter-less microfluidic device for efficient submicron particle separation.
- To create a predictive model for microfluidic chip sorting properties based on geometry.
- To demonstrate the device's capability for both rapid small-size sorting and high-throughput micron-sized sorting.
Main Methods:
- Hydrodynamic filtration utilizing a microfluidic device with a minimum channel dimension of 5 μm.
- Development of a predictive model incorporating velocity profiles and hydrodynamic resistances.
- Fabrication and testing of two distinct chip designs: low-aspect ratio (two-level) and 3D architecture (lamination-based).
Main Results:
- The microfluidic device successfully separates submicron particles (critical size ~0.1 μm) without filters.
- The developed model accurately predicts chip sorting performance, showing quantitative agreement with experimental and numerical results.
- Two design families demonstrated efficient sorting: rapid separation of small sizes and micron-sized sorting at μL flow rates.
Conclusions:
- A passive, filter-less microfluidic device for submicron particle separation has been successfully demonstrated.
- The proposed hydrodynamic filtration method is simple, robust, and easy to fabricate.
- The study provides a validated model for predicting and optimizing microfluidic sorting performance.


