Evidence map›Paper›PMID 34567714›Full record

ArticleMicrosystems & nanoengineering2020

Mapping inertial migration in the cross section of a microfluidic channel with high-speed imaging.

Jian Zhou, Zhangli Peng, Ian Papautsky

Abstract read
In one paragraph

Article in Microsystems & nanoengineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Isolation Techniques of Micro/Nano-Scaled Species for Biomedical Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  4. Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jian ZhouDepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL USA.ORCID 0000-0002-8676-8891
Zhangli PengDepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL USA.ORCID 0000-0002-1506-2365
Ian PapautskyDepartment of Bioengineering, University of Illinois at Chicago, Chicago, IL USA.ORCID 0000-0002-1396-9625

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The wide adoption of inertial microfluidics in biomedical research and clinical settings, such as rare cell isolation, has prompted the inquiry of its underlying mechanism. Although tremendous improvement has been made, the mechanism of inertial migration remains to be further elucidated. Contradicting observations are not fully reconciled by the existing theory, and details of the inertial migration within channel cross sections are missing in the literature. In this work, for the first time, we mapped the inertial migration pathways within channel cross section using high-speed imaging at the single-particle level. This is in contrast to the conventional method of particle streak velocimetry (PSV), which provides collective information. We also applied smoothed particle hydrodynamics (SPH) to simulate the transient motion of particles in 3D and obtained cross-sectional migration trajectories that are in agreement with the high-speed imaging results. We found two opposing pathways that explain the contradicting observations in rectangular microchannels, and the force analysis of these pathways revealed two metastable positions near the short walls that can transition into stable positions depending on the flow condition and particle size. These new findings significantly improve our understanding of the inertial migration physics, and enhance our ability to precisely control particle and cell behaviors within microchannels for a broad range of applications.

Indexed as

EngineeringPhysics

Identifiers

PMID34567714
PMCPMC8433405

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.