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Record W2094893529 · doi:10.1002/pen.10986

Gross melt fracture elimination: The role of surface energy of boron nitride powders

2002· article· en· W2094893529 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

VenuePolymer Engineering and Science · 2002
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceBoron nitrideSurface energyComposite materialExtrusionShear (geology)BoronPenetration (warfare)Contact anglePolarStrain energy release rateFracture (geology)Organic chemistry

Abstract

fetched live from OpenAlex

Abstract Boron nitride (BN) is an effective processing aid for the extrusion of polyethylenes. It postpones the onset of gross melt fracture to significantly high shear rates not previously attained with conventional fluoropolymers. However, BN particles containing relatively high amounts of boron oxide (B 2 O 3 ) do not perform well as processing aids. A reliable procedure has been developed for measurement of surface energy of powders using the capillary rise technique through the use of Washburn's equation. It is based on finding the contact angle from liquid penetration experiments with polar and non‐polar liquids. Both the dispersive and non‐dispersive components of surface energy are determined. With this technique, the surface energy of a number of different powders has been assessed. These results of the surface energy of BN powders have been found to correlate well with the critical shear rate for the onset of melt fracture, indicating the important role that surface energy plays in gross melt fracture elimination.

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 score0.031
Threshold uncertainty score0.230

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 head0.007
GPT teacher head0.183
Teacher spread0.176 · 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