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Record W1922029506 · doi:10.1155/2015/493206

Carbon Fiber Composites of Pure Polypropylene and Maleated Polypropylene Blends Obtained from Injection and Compression Moulding

2015· article· en· W1922029506 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Polymer Science · 2015
Typearticle
Languageen
FieldEngineering
TopicTribology and Wear Analysis
Canadian institutionsPolytechnique Montréal
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsMaterials scienceComposite materialUltimate tensile strengthPolypropyleneDifferential scanning calorimetryScanning electron microscopeIzod impact strength testFourier transform infrared spectroscopyInjection mouldingFiberDynamic mechanical analysisPolymerChemical engineering

Abstract

fetched live from OpenAlex

A comparative study of the mechanical performance of PP and PP/PP-g-MAH blends reinforced with carbon fibre (CF) obtained by two different moulding techniques is presented. Three filler contents were used for fabricating the composites: 1, 3, and 5 pph (parts per hundred). The crystallisation behaviour of the composites was studied by differential scanning calorimetry. Morphological and structural features of these samples were observed by atomic field microscopy and Fourier-transform infrared spectroscopy, respectively. Mechanical properties of the injection and compression moulded composites were evaluated by means of tensile and impact resistance tests. The fracture surface of the impacted samples was observed by scanning electron microscopy. The processing method had a noticeable effect on the results obtained in these tests. Young’s modulus was enhanced up to 147% when adding 5 pph CF to a PP matrix when processed by compression moulding. Addition of PP-g-MAH and CF had a favourable effect on the tensile and impact strength properties in most samples; these composites showed improved performance as the filler content was increased.

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.

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)0.000
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 score0.051
Threshold uncertainty score0.289

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.242
Teacher spread0.233 · 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