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Record W2004221993 · doi:10.3139/217.2365

Rheological and Molecular Investigations of Polyethylene Degradation in a Batch Mixer

2010· article· en· W2004221993 on OpenAlexaff
Eddy Twite‐Kabamba, Denis Rodrigue

Bibliographic record

VenueInternational Polymer Processing · 2010
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRheologyMaterials sciencePolyethyleneBranching (polymer chemistry)Degradation (telecommunications)Molar mass distributionComposite materialElongationPolymerUltimate tensile strengthComputer science

Abstract

fetched live from OpenAlex

Abstract In this study, polyethylene degradation is related to its thermo-mechanical history from processing in a batch mixer. A focus is made on the rheological and molecular properties of the polyethylene subjected to different processing conditions by changing the temperature, the rotor speed and the time of process. The results indicate that while shear rheological properties changed slightly, the elongational properties were substantially modified, especially the maximum stress and the elongation at break. Due to the formation of macroradicals while processing, macromolecular changes were characterized in terms of molecular weight distribution and the results represent a balance between rates of chain scission and chain branching. It was found that the main parameter to characterize the degradation behaviour was the input power.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.307

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 head0.008
GPT teacher head0.246
Teacher spread0.238 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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