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Record W2949106519 · doi:10.1515/arh-2007-0019

A Study of Entrance Pressure Loss in Filled Polymer Melts

2007· article· en· W2949106519 on OpenAlexaff
Velichko Hristov, J. Vlachopoulos

Bibliographic record

VenueApplied Rheology · 2007
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTalcComposite materialMaterials sciencePolyethylenePolymerFiller (materials)Wood flourBody orifice

Abstract

fetched live from OpenAlex

Abstract The influence of the molecular structure of the polymer matrix and filler loading on the entrance pressure loss of polyethylene/wood flour composites has been investigated in this research by means of a capillary rheometer equipped with an orifice die. The entry flow of talc- and glass-filled polyethylene composites has been investigated as well. It was found that the entrance pressure loss of wood filled polyethylene composites greatly increased with increasing the wood flour loading. Talc and solid glass spheres also increase the entrance pressure loss, however not as much as wood flour. It was also observed that composites based on narrow molecular weight distribution (MWD) resins exhibited larger entrance pressure loss than the broad MWD and branched polyethylene based ones. It was concluded that measurements of the entrance pressure loss reveal some interesting features of the polymer-filler interactions and could provide significant insights in the processing of highly filled polymer melts.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score0.575

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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 designObservational
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
Published2007
Admission routes1
Has abstractyes

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