A Cascaded Dual Spiral Microfluidic Chip for Continuous Separation of Multicomponent Microparticles

Inertial microfluidics is promising for the high throughput, label-free continuous separation of multicomponent microparticles. However, conventional single spiral microchannels struggle to separate three or more particle types, while traditional cascaded systems relying on sheath fluids or multiple pumps suffer from increased operational complexity. To address this, we propose a cascaded dual spiral microfluidic chip based on passive flow resistance matching. Driven by a single syringe pump without sheath flow, it achieves continuous sorting of three particle types. An adaptive flow resistance network is incorporated: the first stage channel maintains high velocity to preferentially extract large particles via strong inertial lift forces. The fluid then enters the second stage through a predetermined geometric resistance for automatic deceleration. Experiments demonstrate that at 1.6 mL/min, the system achieves continuous separation of a 1:10:10 mixture of 15, 10, and 5 µm microparticles. The 15 µm target recovery rate reaches 92%, while the collection purities for 10 µm and 5 µm particles exceed 98% and 99%, respectively. This purely passive fluidic architecture simplifies cascaded sorting, providing a robust engineering solution for complex multicomponent sample preprocessing.

Authors

Institutions

Publication Details

Journal
Micromachines
Published
2026-04-13
DOI
https://doi.org/10.3390/mi17040469
Primary Topic
Microfluidic and Bio-sensing Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Cascaded Dual Spiral Microfluidic Chip for Continuous Separation of Multicomponent Microparticles

Gaozhe Cai, Jianlong Zhao, Renxuan Zhang
Micromachines
Microfluidic and Bio-sensing Technologies
article

A Cascaded Dual Spiral Microfluidic Chip for Continuous Separation of Multicomponent Microparticles

Gaozhe Cai, Jianlong Zhao, Renxuan Zhang
article en

Abstract

Inertial microfluidics is promising for the high throughput, label-free continuous separation of multicomponent microparticles. However, conventional single spiral microchannels struggle to separate three or more particle types, while traditional cascaded systems relying on sheath fluids or multiple pumps suffer from increased operational complexity. To address this, we propose a cascaded dual spiral microfluidic chip based on passive flow resistance matching. Driven by a single syringe pump without sheath flow, it achieves continuous sorting of three particle types. An adaptive flow resistance network is incorporated: the first stage channel maintains high velocity to preferentially extract large particles via strong inertial lift forces. The fluid then enters the second stage through a predetermined geometric resistance for automatic deceleration. Experiments demonstrate that at 1.6 mL/min, the system achieves continuous separation of a 1:10:10 mixture of 15, 10, and 5 µm microparticles. The 15 µm target recovery rate reaches 92%, while the collection purities for 10 µm and 5 µm particles exceed 98% and 99%, respectively. This purely passive fluidic architecture simplifies cascaded sorting, providing a robust engineering solution for complex multicomponent sample preprocessing.

MicromachinesVol. 17(4)
Shanghai University (CN), Chinese Academy of Sciences (CN), State Key Laboratory of Transducer Technology (CN), Shanghai Institute of Microsystem and Information Technology (CN)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality
Affordable and clean energy
Openalex Percentile: Top 27%
Microfluidic and Bio-sensing Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.