Evidence map›Paper›PMID 42198091›Full record

ArticlePolymers2026

Kinetic Study of the Oxidative Thermal Degradation of Polymer Composites Loaded with Hybrid Nanostructured Forms of Carbon: Correlation with Electrical and Morphological Properties.

Annalisa Paolone, Francesco Trequattrini, Marialuigia Raimondo, Liberata Guadagno, Stefano Vecchio Ciprioti

Abstract read
In one paragraph

Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Annalisa PaoloneConsiglio Nazionale delle Ricerche-Istituto dei Sistemi Complessi, U.O.S. La Sapienza, Piazzale A. Moro 5, 00185 Roma, Italy.ORCID 0000-0002-4839-7815
Francesco TrequattriniConsiglio Nazionale delle Ricerche-Istituto dei Sistemi Complessi, U.O.S. La Sapienza, Piazzale A. Moro 5, 00185 Roma, Italy.ORCID 0000-0002-6521-7441
Marialuigia RaimondoDipartimento di Ingegneria Industriale, Università di Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy.ORCID 0000-0003-1963-9472
Liberata GuadagnoDipartimento di Ingegneria Industriale, Università di Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Italy.ORCID 0000-0001-5839-1321
Stefano Vecchio CipriotiDipartimento di Scienze di Base ed Applicate per l'Ingegneria, Sapienza Università di Roma, Palazzina RM017, Via del Castro Laurenziano 7, 00161 Roma, Italy.ORCID 0000-0002-7864-4266

Funding

European Union's Horizon Europe 101091828
6 · The paper itself

Abstract

The present research article deals with the thermal degradation study of epoxy resins filled with hybrid nanostructured forms of carbon under oxidative conditions. In particular, the formulated polymer composites (denoted as HYB_0.1%_CNTs:GNs and HYB_0.5%_CNTs:GNs, respectively) consist of two kinds of fillers, namely multi-walled carbon nanotubes (CNTs) and graphene nanosheets (GNs), mixed together with two different total mass amounts: 0.1 and 0.5%. In both kinds of nanocomposites, three different CNT:GN mixing ratios were considered (5:1, 1:1, and 1:5, respectively), thus providing a total of six hybrid samples. The thermal behavior of these samples was studied by simultaneous thermogravimetry and differential thermal analysis (TG/DTA) under flowing air, and two processes took place in distinct temperature ranges. In each step, about 50% of mass loss is detected with an exothermic effect in the corresponding DTA curve, with the second one accompanied by an intense heat release. The kinetic analysis of the two-stage oxidative thermal degradation was investigated using a model-free isoconversional approach. A non-Arrhenian behavior of the temperature function k(T) was assumed, and lifetime prediction was estimated at temperatures close to those of the possible applications. Isoconversional analysis shows nearly constant activation energies for all composites except HYB_0.1%_5:1 (from 142 to 96 kJ·mol

Indexed as

carbon nanotubesgraphene fillerhybrid nanostructuresisoconversional kinetic methodsoxidative thermal degradation

Identifiers

PMID42198091
PMCPMC13210792

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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.