Evidence map›Paper›PMID 37686935›Full record

ArticleNanomaterials (Basel, Switzerland)2023

Thermo-Mechanical Performance of Epoxy Hybrid System Based on Carbon Nanotubes and Graphene Nanoparticles.

Liberata Guadagno, Carlo Naddeo, Andrea Sorrentino, Marialuigia Raimondo

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2023. 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

4 authors.

Liberata GuadagnoDepartment of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy.ORCID 0000-0001-5839-1321
Carlo NaddeoDepartment of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy.ORCID 0000-0001-6882-9489
Andrea SorrentinoInstitute for Polymers, Composites, and Biomaterials (IPCB-CNR), Via Previati n. 1/E, 23900 Lecco, Italy.ORCID 0000-0003-1048-3002
Marialuigia RaimondoDepartment of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy.ORCID 0000-0003-1963-9472

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study focuses on epoxy hybrid systems prepared by incorporating multi-wall carbon nanotubes (MWCNTs) and graphene nanosheets (GNs) at two fixed filler amounts: below (0.1 wt%) and above (0.5 wt%), with varying MWCNT:GN mix ratios. The hybrid epoxy systems exhibited remarkable electrical performance, attributed to the π-π bond interactions between the multi-wall carbon nanotubes and the graphene layers dispersed in the epoxy resin matrix. The material's properties were characterized through dynamic mechanical and thermal analyses over a wide range of temperatures. In addition to excellent electrical properties, the formulated hybrid systems demonstrated high mechanical performance and thermal stability. Notably, the glass transition temperature of the samples reached 255 °C, and high storage modulus values at elevated temperatures were observed. The hybrid systems also displayed thermal stability up to 360 °C in air. By comparing the mechanical and electrical performance, the formulation can be optimized in terms of the electrical percolation threshold (EPT), electrical conductivity, thermostability, and mechanical parameters. This research provides valuable insights for designing advanced epoxy-based materials with multifunctional properties.

Indexed as

carbon nanotubesgraphene nanosheetshybrid nanocompositesmechanical propertiessurface analysisthermal propertiestunneling atomic force microscopy (TUNA)

Identifiers

PMID37686935
PMCPMC10489851

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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.