Evidence map›Paper›PMID 31645762›Full record

ArticleNature2019

Braess's paradox and programmable behaviour in microfluidic networks.

Daniel J Case, Yifan Liu, István Z Kiss, Jean-Régis Angilella, Adilson E Motter

Abstract read
PubMed Publisher
In one paragraph

Article in Nature, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Exploiting Device Deformability for Fluid and Particle Manipulation.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Review
  3. Article
  4. Fluid inertia controls mineral precipitation and clogging in pore to network-scale flows.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. Review
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

5 authors.

Daniel J CaseDepartment of Physics and Astronomy, Northwestern University, Evanston, IL, USA.
Yifan LiuDepartment of Chemistry, Saint Louis University, St Louis, MO, USA.
István Z KissDepartment of Chemistry, Saint Louis University, St Louis, MO, USA.
Jean-Régis AngilellaNormandie Université, UNICAEN, UNIROUEN, ABTE, Caen, France.
Adilson E MotterDepartment of Physics and Astronomy, Northwestern University, Evanston, IL, USA. motter@northwestern.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microfluidic systems are now being designed with precision as miniaturized fluid manipulation devices that can execute increasingly complex tasks. However, their operation often requires numerous external control devices owing to the typically linear nature of microscale flows, which has hampered the development of integrated control mechanisms. Here we address this difficulty by designing microfluidic networks that exhibit a nonlinear relation between the applied pressure and the flow rate, which can be harnessed to switch the direction of internal flows solely by manipulating the input and/or output pressures. We show that these networks- implemented using rigid polymer channels carrying water-exhibit an experimentally supported fluid analogue of Braess's paradox, in which closing an intermediate channel results in a higher, rather than lower, total flow rate. The harnessed behaviour is scalable and can be used to implement flow routing with multiple switches. These findings have the potential to advance the development of built-in control mechanisms in microfluidic networks, thereby facilitating the creation of portable systems and enabling novel applications in areas ranging from wearable healthcare technologies to deployable space systems.

Identifiers

What OpenQuestion holds

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Registered trials

None linked

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.