Flexible Sensor with Material-Microstructure Synergistic Optimization for Wearable Physiological Monitoring.

Yaojia Mou, Cong Wang, Xiaohu Jiang, Jingxiang Wang, Changchao Zhang, Linpeng Liu, Ji'an Duan

Abstract read

In one paragraph

Article in Materials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing 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

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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

1 citing paper in PubMed.

Advances in Laser-Induced Graphene for Flexible Sensors.Materials (Basel, Switzerland) · 2026
Review

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

7 authors.

Yaojia MouState Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.

Cong WangState Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.

Xiaohu JiangCollege of Mechanical and Electrical Engineering, Hunan Agricultural University, Changsha 410128, China.

Jingxiang WangCollege of Engineering Technology, Jilin Agricultural University, Changchun 130118, China.

Changchao ZhangKey Laboratory of Bionic Engineering Ministry of Education, Jilin University, Changchun 130022, China.

Linpeng LiuState Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.ORCID 0000-0001-7234-9779

Ji'an DuanState Key Laboratory of Precision Manufacturing for Extreme Service Performance, College of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China.

Funding

National Natural Science Foundation of China No. 52205320Natural Science Foundation of Hunan Province No. 2023JJ40736Project of State Key Laboratory of Precision Manufacturing for Extreme Service Performance, Central South University Grant No. ZZYJKT2024-03Science and Technology Research Project of Education Department of Jilin Province No. JJKH20250570KJ, JJKH20250134KJ

6 · The paper itself

Abstract

Flexible sensors have emerged as essential components in next-generation technologies such as wearable electronics, smart healthcare, soft robotics, and human-machine interfaces, owing to their outstanding mechanical flexibility and multifunctional sensing capabilities. Despite significant advancements, challenges such as the trade-off between sensitivity and detection range, and poor signal stability under cyclic deformation remain unresolved. To overcome the aforementioned limitations, this work introduces a high-performance soft sensor featuring a dual-layered electrode system, comprising silver nanoparticles (AgNPs) and a composite of multi-walled carbon nanotubes (MWCNTs) with carbon black (CB), coupled with a laser-engraved crack-gradient microstructure. This structural strategy facilitates progressive crack formation under applied strain, thereby achieving enhanced sensitivity (1.56 kPa

Indexed as

bilayer electrodeflexible sensorgradient crack microstructurelaser direct writingmaterial optimization

Identifiers

PMID40805585

DOI10.3390/ma18153707

PMCPMC12348704

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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.