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Record W2067276838 · doi:10.1122/1.3479389

Polymer-polymer interfacial slip by direct visualization and by stress reduction

2010· article· en· W2067276838 on OpenAlexaff
Heon E. Park, Patrick Lee, Christopher W. Macosko

Bibliographic record

VenueJournal of Rheology · 2010
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials sciencePolymerFluoropolymerSlip (aerodynamics)Capillary actionPolyethyleneRheologyFlow visualizationBilayerComposite materialFlow (mathematics)ThermodynamicsMechanicsPhysicsChemistryMembrane

Abstract

fetched live from OpenAlex

We studied polymer-polymer interfacial slip in bilayer films of highly immiscible (interaction parameter, χ≅0.1) polyethylene and fluoropolymer from medium to higher shear stresses (10–200 kPa) using both visualization and stress reduction. We found good agreement between results from the two methods as well as with previous studies using multilayers by Lee et al. [J. Rheol. 53, 893–915 (2009)] and visualization of flow in a transparent capillary by Migler et al. [J. Rheol. 45, 565–581 (2001)]. We observed two power-law regions: Vslip∝τ6.2 with a transition to Vslip∝τ1.8 at 50 kPa. This is in contrast to the theory of Brochard-Wyart and de Gennes [C. R. Acad. Sci., Ser. II: Mec., Phys., Chim., Sci. Terre Univers 317, 13–17 (1993)], which predicts a transition from infinite slope to a slope of one at a critical stress.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.003
GPT teacher head0.230
Teacher spread0.226 · 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

Citations36
Published2010
Admission routes1
Has abstractyes

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