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Record W2524917831 · doi:10.1002/cjce.22608

In‐situ production of polyethylene/cellulose nanocrystal composites

2016· article· en· W2524917831 on OpenAlexafffundvenue
Tariq M. Mannan, João B. P. Soares, Richard M. Berry, Wadood Y. Hamad

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsCelluForce (Canada)FPInnovationsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolyolefinMaterials sciencePolyethyleneCellulosePolymerBifunctionalComposite materialNanocrystalPhase (matter)Chemical engineeringCatalysisOrganic chemistryNanotechnologyChemistryLayer (electronics)

Abstract

fetched live from OpenAlex

ABSTRACT Cellulose nanocrystals (CNC) are renewable, sustainable, and non‐toxic nanomaterials with high surface area, low density, and strength properties several times higher than many metals and polymers. Cellulose nanocrystals, however, are polar and hard to disperse in nonpolar polymers such as polyethylene. Considering that polyethylene is one of the most important commodity polymers today, a significant sector of the polymer market has not benefited yet from the remarkable properties of CNCs. In this article we present a novel method to overcome this difficulty. Our approach was to modify the surface of CNCs with bifunctional organic molecules having terminal vinyl groups that copolymerize, in‐situ, with ethylene using a constrained geometry catalyst. These hybrid materials compatibilize the hydrophilic CNC and the hydrophobic polyolefin phases, leading to good dispersion of the CNC phase in the polyethylene matrix.

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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.221
Teacher spread0.212 · 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

Citations14
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicAdvanced Cellulose Research StudiesFrench-language works237,207