Viscoelastic microfluidics for enhanced separation resolution of submicron particles and extracellular vesicles†
Abstract
Manipulation, focusing, and separation of submicron- and nanoparticles such as extracellular vesicles (EVs), viruses and bacteria have broad applications in disease diagnostics and therapeutics. Viscoelastic microfluidic technology emerges as a promising technique, and it shows an unparalleled capacity to manipulate and separate submicron particles in a high resolution based on the elastic effects of non-Newtonian mediums. The maximum particle separation resolution for the reported state-of-the-art viscoelastic microfluidics is around 200 nm. To further enhance the reseparation resolution, this work develops a viscoelastic microfluidic device that can achieve a finer separation resolution up to 100 nm, by optimising the operating conditions such as flow rate, flow rate ratio and polyethylene oxide (PEO) concentration. With these optimised conditions, we separated a ternary mixture of 100 nm, 200 nm and 500 nm polystyrene particles, with purities above 90%, 70% and 82%, respectively. Furthermore, we also applied the developed viscoelastic microfluidic device for the separation of cancer cell-secreted extracellular vesicles (EVs) into three different size groups. After single processing, the separation efficiencies for small EVs (sEVs, <150 nm), medium EVs (mEVs, 150–300 nm), and large EVs (>300 nm) were 86%, 80% and 50%, respectively. The enrichment factors for the three EV groups were 2.4, 1.1 and 1.3, respectively. Moreover, we observed an unexpected effect of high PEO concentrations (2000–5000 ppm) on the lateral migration of nanoparticles where nanoparticles of up to 50 nm surprisingly can migrate and concentrate at the middle of the microchannel. This simple and label-free viscoelastic microfluidic device possesses excellent potential for sorting submicron particles for various chemical, biological, medical and environmental applications.
- This article is part of the themed collection: Nanoscale 2024 Emerging Investigators