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Record W4294660178 · doi:10.18280/rcma.320407

Morphological and Thermal Properties of Polystyrene/Poly (Vinyl Chloride) Blends

2022· article· en· W4294660178 on OpenAlexvenueno aff
Nassira Tourta, Ahmed Meghezzi, Hamida Boussehel

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2022
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Science and PVC
Canadian institutionsnot available
Fundersnot available
KeywordsDifferential scanning calorimetryMiscibilityPolystyreneMaterials sciencePolyvinyl chlorideThermal stabilityGlass transitionThermogravimetric analysisCastingVinyl chlorideScanning electron microscopePolymer blendPolymer chemistryFourier transform infrared spectroscopyPolymerChemical engineeringComposite materialCopolymerThermodynamics

Abstract

fetched live from OpenAlex

The present study investigated the morphological and thermal properties of polystyrene and polyvinyl chlorides blends (PS/PVC). The PS and PVC mixed by the solution casting by using cyclohexanone the ratios presented are 100/0,80/20,50/50,20/80 and 0/100 according to the weight of PS/PVC. Where the mixture formation is confirmed by Fourier transform infrared (FT-IR), thermal gravimetric analysis (TGA), and differential scanning calorimetry (DSC) respectively. The spectral FT-IR results showed that the blend of PS/PVC did not have molecular reactions. The thermal gravimetry was used to achieve the thermal stability of the polymer blends. Two degrees of glass transition temperature were observed for each mixture. The results of DSC supported the absence of miscibility in the blend. The distribution of the phases in the virgin and blends was studied through scanning electron microscopy (SEM).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.070
GPT teacher head0.260
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

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