Evidence map›Paper›PMID 36297949›Full record

ArticlePolymers2022

Electrically Conductive Adhesive Based on Thermoplastic Hot Melt Copolyamide and Multi-Walled Carbon Nanotubes.

Paulina Latko-Durałek, Michał Misiak, Anna Boczkowska

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2022. 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
0.3field-weighted citation impact, top 53% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

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 at 1 institution in 1 country.

Paulina Latko-DurałekFaculty of Materials Science and Engineering, Warsaw University of Technology, Wołoska 141 Street, 02-507 Warsaw, Poland.
Michał MisiakFaculty of Materials Science and Engineering, Warsaw University of Technology, Wołoska 141 Street, 02-507 Warsaw, Poland.ORCID 0000-0002-2892-418X
Anna BoczkowskaFaculty of Materials Science and Engineering, Warsaw University of Technology, Wołoska 141 Street, 02-507 Warsaw, Poland.ORCID 0000-0002-3694-1342
Warsaw University of Technology · PL

Funding

EEA and Norway Grants NOR/SGS/3DforCOMP/0171/2020-00
6 · The paper itself

Abstract

For the bonding of the lightweight composite parts, it is desired to apply electrically conductive adhesive to maintain the ability to shield electromagnetic interference. Among various solvent-based adhesives, there is a new group of thermoplastic hot melt adhesives that are easy to use, solidify quickly, and are environment-friendly. To make them electrically conductive, a copolyamide-based hot melt adhesive was mixed with 5 and 10 wt% of carbon nanotubes using a melt-blending process. Well-dispersed nanotubes, observed by a high-resolution scanning microscope, led to the formation of a percolated network at both concentrations. It resulted in the electrical conductivity of 3.38 S/m achieved for 10 wt% with a bonding strength of 4.8 MPa examined by a lap shear test. Compared to neat copolyamide, Young's modulus increased up to 0.6 GPa and tensile strength up to 30.4 MPa. The carbon nanotubes improved the thermal stability of 20 °C and shifted the glass transition of 10 °C to a higher value. The very low viscosity of the neat adhesive increased about 5-6 orders of magnitude at both concentrations, even at elevated temperatures. With a simultaneous growth in storage and loss modulus this indicates the strong interactions between polymer and carbon nanotubes.

Indexed as

adhesioncarbon nanotubeshot melt adhesivemicrostructurerheology

Identifiers

PMID36297949
PMCPMC9609002
OpenAlexW4306403109

What OpenQuestion holds

Textmetadata
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.