Evidence map›Paper›PMID 40290904›Full record

ArticleACS omega2025

Cellulose Nanocrystal and Self-Assembling Lignin Enhanced the PEDOT/PSS/PVA Composite on Mechanical and Self-Powered Wearable Properties.

Shih-Chen Shi, Yan-Ching Hsieh, Dieter Rahmadiawan

Abstract read
In one paragraph

Article in ACS omega, 2025. 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

3 authors.

Shih-Chen ShiDepartment of Mechanical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
Yan-Ching HsiehDepartment of Mechanical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
Dieter RahmadiawanDepartment of Mechanical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.ORCID https://orcid.org/0000-0002-3301-5407

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lignin nanomicelle (LNM) synthesis via deep eutectic solvent (DES) has been optimized from a conventional duration of 2-3 days to a streamlined 12 h procedure utilizing autoclave reactor heating. This approach facilitates the efficient extraction of lignin from straw and its subsequent formation into LNMs via a simultaneous self-assembly mechanism. Integration of these amphiphilic LNMs into a cellulose nanocrystal (CNC) framework, combined with PEDOT: PSS in a poly(vinyl alcohol) (PVA) matrix, yields a self-powered strain sensor characterized by enhanced tensile properties and heightened strain sensitivity. Incorporating carboxyl functional groups from LNMs on the PVA matrix significantly augments the sensor's mechanical strength and elasticity. This is evidenced by achieving Young's modulus of 65.9 MPa and an elongation capacity of 320%, ensuring its efficacy in human motion detection. The synergistic inclusion of CNCs and LNMs amplifies the sensor's gauge factor, thereby augmenting its strain responsiveness. The elevated aspect ratio of CNCs establishes an efficacious electrical network that, in concert with the interaction between CNCs and PEDOT: PSS, diminishes the electrical percolation threshold, culminating in an improved gauge factor of 19, indicative of enhanced strain detection capabilities. Furthermore, the sensor can generate a thermoelectric voltage in response to thermal gradients, with the dynamic structures of LNM improving the conductivity and PEDOT: PSS dispersion within the PVA matrix, thereby optimizing the Seebeck coefficient. After enduring 5000 cycles of 100% strain deformation tests, the sensor demonstrates consistent performance, underscoring its reliability and durability. The fabricated PVA/Gly-LNM/CNCs/PEDOT: PSS composite material has been successfully applied to detect nuanced human gestures, including finger and wrist movements, affirming its potential utility in wearable technology applications.

Identifiers

PMID40290904
PMCPMC12019433

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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.