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Record W2102935453 · doi:10.1002/pen.11345

Foaming of PS/wood fiber composites using moisture as a blowing agent

2000· article· en· W2102935453 on OpenAlexaff
Ghaus Rizvi, Laurent M. Matuana, Chul B. Park

Bibliographic record

VenuePolymer Engineering and Science · 2000
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceComposite materialBlowing agentExtrusionComposite numberFiberPolystyreneMoistureExpansion ratioWood-plastic compositeVolume (thermodynamics)PolymerPolyurethane

Abstract

fetched live from OpenAlex

Abstract This paper presents an experimental study on foam processing of polystyrene (PS) and high‐impact polystyrene HIPS/wood‐fiber composites in extrusion using moisture as a blowing agent. Wood‐fiber inherently contains moisture that can potentially be used as a blowing agent. Undried wood‐fiber was processed together with PS and HIPS materials in extrusion and wood‐fiber composite foams were produced. The cellular morphology and volume expansion ratios of the foamed composites were characterized. Because of the high stiffness of styrenic materials, moisture condensation during cooling after expansion at high temperature did not cause much contraction of the foamed composite and a high volume expansion ratio up to 20 was successfully obtained. The experimental results showed that the expansion ratio could be controlled by varying the processing temperature and the moisture content in the wood fiber. The effects of a small amount of a chemical blowing agent and mineral oil on the cell morphologies of plastic/wood‐fiber composite foams were also investigated.

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 score0.004

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 head0.008
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 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

Citations93
Published2000
Admission routes1
Has abstractyes

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