Evidence map›Paper›PMID 36033682›Full record

ArticleACS omega2022

Multifunctional MXene/Aramid Nanofiber Composite Films for Efficient Electromagnetic Interference Shielding and Repeatable Early Fire Detection.

Tianshu Peng, Shanchi Wang, Zhiguang Xu, Tingting Tang, Yan Zhao

Abstract read
In one paragraph

Article in ACS omega, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

5 authors.

Tianshu PengCollege of Textile and Clothing Engineering, Soochow University, Suzhou 215123, China.
Shanchi WangCollege of Textile and Clothing Engineering, Soochow University, Suzhou 215123, China.
Zhiguang XuChina-Australia Institute for Advanced Materials and Manufacturing, Jiaxing University, Jiaxing 314001, China.
Tingting TangCollege of Textile and Clothing Engineering, Soochow University, Suzhou 215123, China.
Yan ZhaoCollege of Textile and Clothing Engineering, Soochow University, Suzhou 215123, China.ORCID https://orcid.org/0000-0002-2386-2901

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid development of highly integrated electronic and telecommunication devices has led to urgent demands for electromagnetic interference (EMI) shielding materials that incorporate flame retardancy, and more desirably the early fire detection ability, due to the potential fire hazards caused by heat propagation and thermal failure of the devices during operation. Here, multifunctional flexible films having the main dual functions of high EMI shielding performance and repeatable fire detection ability are fabricated by vacuum filtration of the mixture of MXene and aramid nanofiber (ANF) suspensions. ANFs serve to reinforce MXene films via the formation of hydrogen bonding between the carbonyl groups of ANFs and the hydroxyl groups of MXene. When the ANF content is 20 wt %, the tensile strength of the film is increased from 24.6 MPa for a pure MXene film to 79.5 MPa, and such a composite film (9 μm thickness) exhibits a high EMI shielding effectiveness (SE) value of ∼40 dB and a specific SE (SSE) value of 4361.1 dB/mm. Upon fire exposure, the composite films can trigger the fire detection system within 10 s owing to the thermoelectric property of MXene. The self-extinguishing feature of ANFs ensures the structural integrity of the films during burning, thus allowing for continuous alarm signals. Moreover, the films also exhibit excellent Joule heating and photothermal conversion performances with rapid response and sufficient heating reliability.

Identifiers

PMID36033682
PMCPMC9404508

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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.