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Record W4413025723 · doi:10.3390/jcs9080420

Kinetic Analysis of Thermal Degradation of Styrene–Butadiene Rubber Compounds Under Different Aging Conditions

2025· article· en· W4413025723 on OpenAlexafffund
Imen Hamouda, Masoud Tayefi, Mostafa Eesaee, Meysam Hassanipour, Phuong Nguyen‐Tri

Bibliographic record

VenueJournal of Composites Science · 2025
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsHydro-QuébecUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of CanadaHydro-Québec
KeywordsDegradation (telecommunications)Natural rubberStyrene-butadieneMaterials scienceStyrene1,3-ButadieneThermalKinetic energyComposite materialChemistryComputer scienceOrganic chemistryCopolymerPolymerThermodynamicsCatalysisPhysics

Abstract

fetched live from OpenAlex

This study examined the impact of storage and operational aging on the thermal stability, structural degradation, and electrical properties of styrene–butadiene rubber (SBR) compound by analyzing three distinct materials: a laboratory-stored sample, an operationally aged one, and an original unaged reference. Thermal degradation was analyzed through thermogravimetric analysis (TGA), which examined weight loss as a function of temperature and time at different heating rates. Results showed that the onset temperature and peak position in the 457 °C to 483 °C range remained stable. The activation energy (Ea) was determined using the Kissinger–Akahira–Sunose (KAS), Flynn–Wall–Ozawa (FWO), and Friedman methods, with the original unaged sample’s (OUS) Ea averaging 203.7 kJ/mol, decreasing to 163.47 kJ/mol in the laboratory-stored sample (LSS), and increasing to 224.18 kJ/mol in the operationally aged sample (OAS). The Toop equation was applied to estimate the thermal degradation lifetime at a 50% conversion rate. Since the material had been exposed to electricity, the evolution of electrical conductivity was studied and found to have remained stable after storage at around 0.070 S/cm. However, after operational aging, it showed a considerable increase in conductivity, to 0.321 S/cm. Scanning Electron Microscopy (SEM) was employed to analyze microstructural degradation and chemical changes, providing insights into the impact of aging on thermal stability and electrical properties.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.389

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.273
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes2
Has abstractyes

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