A novel viscoelastic microfluidic platform for nanoparticle/small extracellular vesicle separation through viscosity gradient-induced migration
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Updated: Jun 22, 2025

Author Spotlight: Asymmetric Field Flow Fractionation for Bioreactor Integration
Published on: February 2, 2024
Han Guo, Dayin Wang, Shilun Feng
1State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, People's Republic of China.
Abstract:
Small extracellular vesicles (sEVs) are extracellular vesicles with diameters ranging from 30 to 150 nm, harboring proteins and nucleic acids that reflect their source cells and act as vital mediators of intercellular communication. The comprehensive analysis of sEVs is hindered by the complex composition of biofluids that contain various extracellular vesicles. Conventional separation methods, such as ultracentrifugation and immunoaffinity capture, face routine challenges in operation complexity, cost, and compromised recovery rates. Microfluidic technologies, particularly viscoelastic microfluidics, offer a promising alternative for sEV separation due to its field-free nature, fast and simple operation procedure, and minimal sample consumption. In this context, we here introduce an innovative viscoelastic approach designed to exploit the viscosity gradient-induced force with size-dependent characteristics, thereby enabling the efficient separation of nano-sized particles and sEVs from larger impurities. We first seek to illustrate the underlying mechanism of the viscosity gradient-induced force, followed by experimental validation with fluorescent nanoparticles demonstrating separation results consistent with qualitative analysis. We believe that this work is the first to report such viscosity gradient-induced phenomenon in the microfluidic context. The presented approach achieves ∼80% for both target purity and recovery rate. We further demonstrate effective sEV separation using our device to showcase its efficacy in the real biological context, highlighting its potential as a versatile, label-free platform for sEV analysis in both fundamental biological research and clinical applications.
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