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Record W1996661378 · doi:10.1002/vnl.10221

Challenge to fortyfold expansion of biodegradable polyester foams by using carbon dioxide as a blowing agent

2000· article· en· W1996661378 on OpenAlexaff
Chul B. Park, Yuejian Liu, Hani E. Naguib

Bibliographic record

VenueJournal of Vinyl and Additive Technology · 2000
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBlowing agentMaterials sciencePolyesterSupercritical carbon dioxideExpansion ratioVolume (thermodynamics)Composite materialCarbon dioxideBiodegradable polymerExtrusionChemical engineeringPolymerOrganic chemistryChemistryThermodynamicsPolyurethane

Abstract

fetched live from OpenAlex

Abstract This paper presents a new foaming technology using supercritical carbon dioxide as a blowing agent to obtain large volume expansions of biodegradable polyester foams of over fortyfold. The basic approach for the promotion of a large volume expansion ratio with carbon dioxide was to prevent cell coalescence by using a branched material, to dissolve carbon dioxide completely in the melt by promoting convective diffusion under a high processing pressure, to reduce the diffusivity of gas by lowering the melt temperature, and to optimize the processing conditions in the die to maximize volume expansion. The desirable composition of the materials includes dehydrated branched biodegradable polyester (polybutylene succinate), CO 2 (blowing agent), and tale (nucleating agent). A single‐screw extrusion system was used for foam processing. A large volume expansion ratio of up to forty‐fivefold was achieved from the biodegradable polyester foams. The morphologies and volume expansion ratios of biodegradable polyester foams at various processing temperatures and pressures were studied.

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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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

Citations11
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Vinyl and Additive TechnologySame topicPolymer Foaming and CompositesFrench-language works237,207