Evidence map›Paper›PMID 32751199›Full record

ArticlePolymers2020

Effects of Carbonyl Iron Powder (CIP) Content on the Electromagnetic Wave Absorption and Mechanical Properties of CIP/ABS Composites.

Wenwen Lai, Yan Wang, Junkun He

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 26% of its field
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

6 citing papers in PubMed, 32 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Wenwen LaiSchool of Materials Science and Engineering, Wuhan Institute of Technology, Wuhan 430074, Hubei, China.ORCID 0000-0002-5484-591X
Yan WangSchool of Materials Science and Engineering, Wuhan Institute of Technology, Wuhan 430074, Hubei, China.
Junkun HeSchool of Materials Science and Engineering, Wuhan Institute of Technology, Wuhan 430074, Hubei, China.
Wuhan Institute of Technology · CN

Funding

Guangdong Key Laboratory of Enterprise of 3D Printing Polymer and Composite Materials 2018B030323001
6 · The paper itself

Abstract

Three-dimensional (3D) printing technology has proven to be a convenient and effective method to fabricate structural electromagnetic wave (EMW) absorbers with tunable EMW absorption properties. To obtain a functional material with strong EMW absorbing performance and excellent mechanical properties for fused deposition modeling (FDM) 3D printing technology, in this work, carbonyl iron powder (CIP)/acrylonitrile-butadiene-styrene copolymer (ABS) composites with different CIP contents were prepared by the melt-mixing process. The effects of the CIP content on the EMW absorption and mechanical properties of CIP/ABS composites were investigated. The CIP/ABS composite with a CIP content of 40 wt.% presented the lowest reflection loss (RL) of -48.71 dB for the optimal impedance matching. In addition, this composite exhibited optimal mechanical properties due to the good dispersion of the CIPs in the matrix ABS. Not only were the tensile and flexural strength similar to pure ABS, but the tensile and flexural modulus were 32% and 37% higher than those of pure ABS, respectively. With a CIP content of 40 wt.%, the CIP/ABS composite proved to be a novel functional material with excellent EMW absorbing and mechanical properties, providing great potential for the development of structural absorbers via FDM 3D printing technology.

Indexed as

CIP/ABS compositeselectromagnetic wave absorptionFDMfunctional materialmechanical properties

Identifiers

PMID32751199
PMCPMC7463693
OpenAlexW3046199737

What OpenQuestion holds

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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.