Evidence map›Paper›PMID 34035293›Full record

ArticleNature communications2021

Dynamic manipulation of droplets using mechanically tunable microtextured chemical gradients.

Ali J Mazaltarim, John J Bowen, Jay M Taylor, Stephen A Morin

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Topological elastic liquid diode.Science advances · 2025
    Article
  10. Review
  11. Article
  12. Functional PDMS Elastomers: Bulk Composites, Surface Engineering, and Precision Fabrication.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Review
  13. Review
  14. Article
  15. Janus Charged Droplet Manipulation Mediated by Invisible Charge Walls.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Article
  16. Article
  17. Article
  18. 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

4 authors.

Ali J MazaltarimDepartment of Chemistry, University of Nebraska - Lincoln, Lincoln, NE, USA.
John J BowenDepartment of Chemistry, University of Nebraska - Lincoln, Lincoln, NE, USA.
Jay M TaylorDepartment of Chemistry, University of Nebraska - Lincoln, Lincoln, NE, USA.
Stephen A MorinDepartment of Chemistry, University of Nebraska - Lincoln, Lincoln, NE, USA. smorin2@unl.edu.ORCID http://orcid.org/0000-0002-8652-0511

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Materials and strategies applicable to the dynamic transport of microdroplets are relevant to surface fluidics, self-cleaning materials, thermal management systems, and analytical devices. Techniques based on electrowetting, topographic micropatterns, and thermal/chemical gradients have advanced considerably, but dynamic microdroplet transport remains a challenge. This manuscript reports the fabrication of mechano-tunable, microtextured chemical gradients on elastomer films and their use in controlled microdroplet transport. Specifically, discreet mechanical deformations of these films enabled dynamic tuning of the microtextures and thus transport along surface-chemical gradients. The interplay between the driving force of the chemical gradient and the microtopography was characterized, facilitating accurate prediction of the conditions (droplet radius and roughness) which supported transport. In this work, the use of microtextured surface chemical gradients in mechano-adaptive materials with microdroplet manipulation functionality was highlighted.

Identifiers

PMID34035293
PMCPMC8149645

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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.