Evidence map›Paper›PMID 39341839›Full record

ArticleNature communications2024

Structurally-colored adhesives for sensitive, high-resolution, and non-invasive adhesion self-monitoring.

Quanqian Lyu, Miaomiao Li, Lianbin Zhang, Jintao Zhu

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

4 authors.

Quanqian LyuState Key Laboratory of Material Processing and Die & Mould Technology and School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), Wuhan, China.
Miaomiao LiState Key Laboratory of Material Processing and Die & Mould Technology and School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), Wuhan, China.
Lianbin ZhangState Key Laboratory of Material Processing and Die & Mould Technology and School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), Wuhan, China. zhanglianbin@hust.edu.cn.ORCID http://orcid.org/0000-0002-8548-1506
Jintao ZhuState Key Laboratory of Material Processing and Die & Mould Technology and School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), Wuhan, China. jtzhu@mail.hust.edu.cn.ORCID http://orcid.org/0000-0002-8230-3923

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52373075
6 · The paper itself

Abstract

Polymeric adhesives are critical in many applications, from daily life to implantable devices and soft robotics. Monitoring adhesion in a real-time and convenient manner before premature failure is essential yet challenging. Herein, we present structurally-colored adhesives for sensitive, high-resolution, and non-invasive adhesion self-monitoring via distinct color change for detecting subtle deformation and debonding. The structurally-colored adhesives are designed by integrating one-dimensional photonic nanochains into exemplified acrylate-copolymer-based adhesives and demonstrate distinct color-changing capability through a unique tilting mechanism of nanochains under shear. Our structurally-colored adhesives can be customized as pressure-sensitive and structural adhesives, exhibiting ultrafast response (<60 ms), high sensitivity, and high resolution (~120 μm). Moreover, predicting adhesion states and premature failure can be achieved assisted by imaging systems and machine learning algorithms with an average accuracy of up to 97.2%. Our structurally-colored adhesives are expected to offer a practical paradigm for structural health monitoring in the Internet of Things era.

Identifiers

PMID39341839
PMCPMC11438979

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.