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Record W2053099539 · doi:10.1002/mame.200500075

In Situ Polymerization of Hybrid Polyethylene‐Alumina Nanocomposites

2005· article· en· W2053099539 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

VenueMacromolecular Materials and Engineering · 2005
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Nanocomposites and Properties
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceNanocompositePolyethyleneVinyl alcoholPolymerizationNanoparticleChemical engineeringIn situ polymerizationCopolymerDispersion (optics)Polymer chemistryComposite materialPolymerNanotechnology

Abstract

fetched live from OpenAlex

Abstract Summary: Polyethylene‐alumina nanocomposites were prepared using in situ polymerization. Alumina nanomers were prepared by treating alumina nanoparticles with an alkylaluminium compound and a vinyl alcohol. This approach led to (a) grafting double bonds onto the alumina surface, and (b) dispersion of alumina nanoparticles in toluene minimizing aggregation. The level of dispersion of nanomers was a function of the molar ratio between the alkylaluminium compound and the vinyl alcohol. Copolymerization of ethylene and nanomers catalyzed by the coordination catalyst (diimine)NiCl 2 /MAO produced hybrid nanocomposites with polyethylene chains covalently bonded to the surface of alumina nanoparticles. Using excess of vinyl alcohol produced crosslinked material. Appropriate preparation of nanomers has produced a good dispersion of alumina nanoparticles in the polyethylene matrix. At certain compositions the final material had better mechanical properties, such as yield strength and toughness, than the homopolyethylene. magnified image

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 score0.002
Threshold uncertainty score0.626

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 head0.004
GPT teacher head0.187
Teacher spread0.183 · 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