Evidence map›Paper›PMID 41680166›Full record

ArticleNature communications2026

Dielectrocapillarity for exquisite control of fluids.

Anna T Bui, Stephen J Cox

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. A unified machine-learning framework for ab initio multiscale modeling of liquids.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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  3. Article
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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

2 authors.

Anna T BuiYusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, UK.ORCID http://orcid.org/0000-0003-0981-4329
Stephen J CoxDepartment of Chemistry, Durham University, South Road, Durham, UK. stephen.j.cox@durham.ac.uk.ORCID http://orcid.org/0000-0003-2708-8711

Funding

RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/X035859Royal Society URF\R1\211144
6 · The paper itself

Abstract

Spatially varying electric fields are prevalent throughout nature, such as in nanoporous materials and biological membranes, and technology, e.g, patterned electrodes and van der Waals heterostructures. While uniform fields cause free ions to migrate, for polar fluids they simply reorient the constituent molecules. In contrast, electric field gradients (EFGs) induce a dielectrophoretic force, offering fine control of polar fluids even in the absence of free charges. Despite their vast potential for optimizing fluid behavior, EFGs remain largely unexplored at the microscopic level due to the absence of a rigorous first-principles theory of electrostriction. By integrating state-of-the-art advances in liquid state theory and deep learning, we reveal how EFGs modulate fluid structure and capillarity. We demonstrate that dielectrophoretic coupling enables tunable control over the liquid-gas phase transition, capillary condensation, and fluid uptake into porous media. Our findings establish "dielectrocapillarity"-the use of EFGs to manipulate confined fluids-as a powerful mechanism for controlling volumetric capacity in nanopores, holding immense potential for energy storage, selective gas separation, and tunable hysteresis in neuromorphic nanofluidics. Furthermore, by linking nanoscale dielectrocapillarity to macroscopic dielectrowetting, we establish a foundation for field-controlled wetting and adsorption phenomena of polar fluids across length scales.

Identifiers

PMID41680166
PMCPMC13009173

What OpenQuestion holds

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LicenceCC BY
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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.