Evidence map›Paper›PMID 42774378›Full record

ArticleResearch (Washington, D.C.)2026

LiqMat: Liquidity-Enabled Matters for Adaptive Electronics.

Sen Chen, Jing Liu

Abstract readEditorial
In one paragraph

Article in Research (Washington, D.C.), 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

2 authors.

Sen ChenState Key Laboratory of Mechanics and Control for Mechanical Structures, Institute for Frontier Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China.ORCID https://orcid.org/0000-0003-3061-1497
Jing LiuKey Laboratory of Cryogenic Science and Technology, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing, China.ORCID https://orcid.org/0000-0002-0844-5296

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Life chooses liquids, whereas modern electronics has long relied on solids. This fundamental distinction has shaped 2 remarkably successful yet largely independent information systems: biological systems that achieve adaptation through dynamic liquid environments and electronic systems that rely on static solid-state architectures. Although flexible electronics have largely improved mechanical compliance, their functionality remains predominantly encoded in fixed conductive pathways and predefined interfaces, limiting their ability to adapt. Here, we introduce LiqMat (liquidity-enabled matters) as a materials paradigm for adaptive electronics. Rather than defining a specific material class, LiqMat describes functional material systems whose properties emerge from liquidity-enabled dynamics rather than relying solely on static structures. We propose that dynamic interfaces, adaptive transport, and structural evolution constitute 3 core characteristics of LiqMat. These characteristics are shared by diverse liquid-enabled material systems, including aqueous systems and hydrogels, ionic liquids and ionogels, and electrofluids, as well as liquid metals and their composites, despite their distinct chemistries and transport mechanisms. Of these, liquid metals provide a particularly illustrative example of LiqMat by combining high electronic conductivity with fluidic adaptability. Looking forward, LiqMat provides a conceptual framework for shifting electronics from mechanically flexible yet functionally static systems toward adaptive electronics inspired by the dynamic organization of living systems.

Identifiers

PMID42774378
PMCPMC13594416

What OpenQuestion holds

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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.