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Record W2110083883 · doi:10.1177/0021998310382317

Water sorption and mechanical performance of preheated wood/ thermoplastic composites

2010· article· en· W2110083883 on OpenAlexaff
Alireza Kaboorani, Karl Englund

Bibliographic record

VenueJournal of Composite Materials · 2010
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceComposite materialFlexural strengthSwellingYoung's modulusSorptionImmersion (mathematics)Flexural modulusWood-plastic compositeThermoplasticPorosityPolyethyleneComposite number

Abstract

fetched live from OpenAlex

Wood samples heat treated at 175°C, 190°C, and 205°C with different amounts of high density polyethylene and coupling agent were used for the production of wood/plastic composites. Measuring water sorption, thickness swelling, and diffusion coefficients of composites for a 40-week period immersion in water showed that composites with wood treatment at 190°C and 205°C had considerably higher water resistance. Adding a coupling agent reduced water sorption, thickness swelling, and diffusion coefficients, more pronounced in composites with untreated wood. Measurements of flexural properties in a control state and after 4 and 12 weeks immersion periods in water proved that heat treatment is an effective way to ease detrimental effects of water on mechanical properties. Modulus of elasticity showed more sensitivity to water exposure than modulus of rupture. Strain at maximum load increased after water exposure. Treating wood at 190°C resulted in good flexural properties and excellent water resistance.

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 score0.003
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.220
Teacher spread0.213 · 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

Citations16
Published2010
Admission routes1
Has abstractyes

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