Bending-Stable Pressure Sensor Based on Natural Wood Nanofibers for Ultra-Low Detection Limit.

Xu Zeng, Zhengnan Sun, Yilin Wang, Yao Tan, Ranran Xu, Beomjoon Kim, Juergen Brugger, Xiaosheng Zhang

Abstract read

In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

8 authors.

Xu ZengSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Zhengnan SunSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Yilin WangSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Yao TanSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Ranran XuSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Beomjoon KimCREMeB, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0001-9565-299X

Juergen BruggerMicrosystems Laboratory, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

Xiaosheng ZhangSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China.ORCID https://orcid.org/0000-0001-9719-0573

Funding

Fundamental Research Funds for the Central Universities ZYGX2025TS008National Key Research and Development Program of China 2022YFB3206100National Natural Science Foundation of China T2541035Sichuan Science and Technology Program 2026YFHZ0313

6 · The paper itself

Abstract

Flexible pressure sensors, essential for intelligent electronic skins, are valued for their versatility and integration. However, the inherent coupling between the pressure and bending strain effects limits their sensing features atop curved surfaces and hinders ultralow detection thresholds. Inspired by natural nests, we present a bioinspired all-fiber flexible pressure sensor that effectively decouples pressure and bending strain. Mimicking the interwoven fiber networks, the proposed device employs a fully fiber-based structure derived from natural wood to replicate the pressure-bending strain decoupling mechanism. This configuration isolates pressure from strain under bending deformation through synergistic modulation of the dielectric constants and interelectrode spacing. Therefore, it first enables precise pressure detection even on curved and dynamic surfaces. Besides the exceptional conformability and long-term stability, its detection limit achieves a record of 0.03 Pa. Furthermore, this natural wood-based sensor demonstrates recyclability through a dissolving-reproducing strategy and spatial pressure mapping through machine learning, offering a sustainable and cost-effective solution for physiological and environmental monitoring.

Indexed as

flexible electronicsMEMS （Micro‐Electro‐Mechanical Systems）nanofibrous membranewearable sensors

Identifiers

PMID42565527

DOI10.1002/advs.76900

PMCPMC13449535

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

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.