Evidence map›Paper›PMID 42726850›Full record

ArticleScience advances2026

Flexoelectricity and ion transport synergy for high efficient energy conversion.

Dongze Yan, Li-Hua Shao, Huiling Duan, Wanlin Guo

Abstract read
In one paragraph

Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Dongze YanNational Key Laboratory of Strength and Structural Integrity, Institute of Solid Mechanics, School of Aeronautic Science and Engineering, Beihang University, Beijing 102206, P.R. China.ORCID 0000-0001-7283-9161
Li-Hua ShaoNational Key Laboratory of Strength and Structural Integrity, Institute of Solid Mechanics, School of Aeronautic Science and Engineering, Beihang University, Beijing 102206, P.R. China.ORCID 0000-0003-3694-0523
Huiling DuanCollege of Engineering, Peking University, Beijing 100871, P.R. China.ORCID 0000-0003-1478-5649
Wanlin GuoKey Laboratory for Intelligent Nano Materials and Devices of Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, P.R. China.ORCID 0000-0002-2302-8044

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ion transport is a fundamental process governing biological functions and energy conversion in electrochemical systems, but breaking through the efficiency limitations of these systems remains a challenge. Here, we report an ion transport mechanism in electrolytes driven by flexoelectricity of a carbon nanotube-filled porous polydimethylsiloxane composite. Because of the synergistic effect of flexoelectricity and ion transport, the efficiency of converting the total mechanical work into electrical energy reaches 6.54%, and the net energy conversion efficiency without the reversible elastic deformation energy being reckoned reaches 28.81%. The mass-specific and deformability-specific current of polydimethylsiloxane is enhanced by 1,000,000 times compared to that of solid truncated pyramid polydimethylsiloxane in air. The mass-specific electrical energy per unit stress is over 10 times that of the reported nanogenerators, and the performance remains stable for 10,000,000 cycles. Compressing 1.02 gram of the material once can generate enough electricity to light 800 light-emitting diodes. Our work provides a practical route for compliant and low-cost energy converting devices for applications in sensing, energy harvesting, and biosignaling.

Identifiers

PMID42726850
PMCPMC13564877

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.