Evidence map›Paper›PMID 34845343›Full record

ArticleNature chemistry2022

Continuous, autonomous subsurface cargo shuttling by nature-inspired meniscus-climbing systems.

Ganhua Xie, Pei Li, Paul Y Kim, Pei-Yang Gu, Brett A Helms, Paul D Ashby, Lei Jiang, Thomas P Russell

Abstract read
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Article in Nature chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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

8 authors.

Ganhua XieMaterials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Pei LiMaterials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Paul Y KimMaterials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Pei-Yang GuMaterials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Brett A HelmsMaterials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0003-3925-4174
Paul D AshbyMaterials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID http://orcid.org/0000-0003-4195-310X
Lei JiangKey Laboratory of Bio-inspired Materials and Interfacial Science, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, China.ORCID http://orcid.org/0000-0003-4579-728X
Thomas P RussellMaterials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. russell@mail.pse.umass.edu.ORCID http://orcid.org/0000-0001-6384-5826

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water-walking insects can harness capillary forces by changing their body posture to climb or descend the meniscus between the surface of water and a solid object. Controlling surface tension in this manner is necessary for predation, escape and survival. Inspired by this behaviour, we demonstrate autonomous, aqueous-based synthetic systems that overcome the meniscus barrier and shuttle cargo subsurface to and from a landing site and a targeted drop-off site. We change the sign of the contact angle of a coacervate sac containing an aqueous phase or of a hydrogel droplet hanging from the surface by controlling the normal force acting on the sac or droplet. The cyclic buoyancy-induced cargo shuttling occurs continuously, as long as the supply of reactants diffusing to the sac or droplet from the surrounding aqueous phase is not exhausted. These findings may lead to potential applications in autonomously driven reaction or delivery systems and micro-/milli-robotics.

Identifiers

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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.