MétaCan
Menu
Back to cohort
Record W2334259923 · doi:10.1177/0021955x14529137

Polyurethane foam mechanical reinforcement by low-aspect ratio micro-crystalline cellulose and glass fibres

2014· article· en· W2334259923 on OpenAlexaff
Sadakat Hussain, Mark T. Kortschot

Bibliographic record

VenueJournal of Cellular Plastics · 2014
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials sciencePolyurethaneComposite materialCelluloseReinforcementComposite numberModulusGlass fiberChemical engineering

Abstract

fetched live from OpenAlex

The effect of fibre length and fibre aspect ratio on the reinforcement of soybean-based polyurethane foams was investigated. Micro-crystalline cellulose fibres and 260-µm long glass fibres embedded inside polyurethane foams were studied separately. Using X-ray tomography, it was determined that short micro-crystalline cellulose fibres were found solely embedded within the cell struts of the polyurethane foam. The cell struts were reinforced by the micro-crystalline cellulose fibres based on composite theory. An attempt was made to predict the reinforcement by using existing micro-mechanical models including the rule of mixtures and shear-lag theory. The overall foam compressive modulus increased based on the reinforcement of the cell struts and correlated with the foam mechanics model developed by Gibson and Ashby. The intermediate length 260-µm long glass fibres were found to span cells in polyurethane foam and were not embedded within the cell struts. These glass fibres did not contact each other. The reinforcement performance of the intermediate length glass fibres was found to be worse than the short micro-crystalline cellulose fibres. Therefore, these intermediate length fibres that span cells should be avoided for use in reinforcement of soybean-based polyurethane foams.

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)0.001
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 score0.224
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.005
GPT teacher head0.204
Teacher spread0.198 · 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 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

Citations8
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cellular PlasticsSame topicNatural Fiber Reinforced CompositesFrench-language works237,207