Evidence map›Paper›PMID 35267826›Full record

ArticlePolymers2022

Effects of Thermal Activation on CNT Nanocomposite Electrical Conductivity and Rheology.

Joel Hubbard, Joaquin Tirano, Hugo Zea, Claudia Luhrs

Abstract 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
–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

0 citing papers in PubMed.

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

4 authors.

Joel HubbardMechanical and Aerospace Engineering Department, Naval Postgraduate School, Monterey, CA 93943, USA.ORCID 0000-0001-8030-7536
Joaquin TiranoDepartamento de Ingeniería Química y Ambiental, Universidad Nacional de Colombia, Bogotá 111321, Colombia.
Hugo ZeaDepartamento de Ingeniería Química y Ambiental, Universidad Nacional de Colombia, Bogotá 111321, Colombia.
Claudia LuhrsMechanical and Aerospace Engineering Department, Naval Postgraduate School, Monterey, CA 93943, USA.ORCID 0000-0002-1655-2593

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbon-based nanocomposites featuring enhanced electrical properties have seen increased adoption in applications involving electromagnetic interference shielding and electrostatic dissipation. As the commercialization of these materials grows, a thorough understanding of how thermal activation affects the rheology and electrical performance of CNT-epoxy blends can inform quality decisions throughout the production process. The aim of this work was the identification of the effects that thermal activation has on the electrical and rheological properties of uncured epoxy mixtures and how those may be tied to the resulting cured composites. Herein, three distinct CNT-loaded composite mixtures were characterized for changes in electrical resistivity and viscosity resulting from varying activation times. Electrical conductivity decreased as activation time increased. Uncured mixture viscosity exhibited a strong dependence on CNT loading and applied strain, with activation time being found to significantly reduce the viscosity of the uncured mixture and surface profile of cured composite films. In all cases, cured composites featured improved electrical conductivity over the uncured mixtures. Factors contributing to the observed behavior are discussed. Raman analysis, optical microscopy of CNT networks, and data from silica bead mixing and dispersion studies are presented to contextualize the results.

Indexed as

CNT compositeselectrically conductiverheologythermal activationviscosity

Identifiers

PMID35267826
PMCPMC8914633

What OpenQuestion holds

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LicenceCC BY
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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.