Evidence map›Paper›PMID 30920553›Full record

ArticleSoft matter2019

Statistical properties of autonomous flows in 2D active nematics.

Linnea M Lemma, Stephen J DeCamp, Zhihong You, Luca Giomi, Zvonimir Dogic

Abstract read
In one paragraph

Article in Soft matter, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Measuring response functions of active materials from data.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Extensile to contractile transition in active microtubule-actin composites generates layered asters with programmable lifetimes.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  14. Flow around topological defects in active nematic films.Proceedings. Mathematical, physical, and engineering sciences · 2022
    Article
  15. Article
  16. Article
  17. Article
  18. Learning active nematics one step at a time.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  19. Machine learning active-nematic hydrodynamics.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  20. 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

5 authors.

Linnea M LemmaDepartment of Physics, Brandeis University, Waltham, MA 02454, USA.
Stephen J DeCamp
Zhihong You
Luca Giomi
Zvonimir Dogic

Funding

Quantitative Biology: a Graduate Curriculum Linking the Physical and Biomedical ST32EB009419 · NIBIB · BRANDEIS UNIVERSITY · PI GELLES, JEFF, KONDEV, JANE · 2009 to 2018
$2.8M
NIBIB NIH HHS T32 EB009419
6 · The paper itself

Abstract

We study the dynamics of a tunable 2D active nematic liquid crystal composed of microtubules and kinesin motors confined to an oil-water interface. Kinesin motors continuously inject mechanical energy into the system through ATP hydrolysis, powering the relative microscopic sliding of adjacent microtubules, which in turn generates macroscale autonomous flows and chaotic dynamics. We use particle image velocimetry to quantify two-dimensional flows of active nematics and extract their statistical properties. In agreement with the hydrodynamic theory, we find that the vortex areas comprising the chaotic flows are exponentially distributed, which allows us to extract the characteristic system length scale. We probe the dependence of this length scale on the ATP concentration, which is the experimental knob that tunes the magnitude of the active stress. Our data suggest a possible mapping between the ATP concentration and the active stress that is based on the Michaelis-Menten kinetics that governs the motion of individual kinesin motors.

Identifiers

PMID30920553
PMCPMC6924514

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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.