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Record W1999103046 · doi:10.1177/0021955x07076532

Foaming of Polystyrene/ Thermoplastic Starch Blends

2007· article· en· W1999103046 on OpenAlexaff
Mihaela Mihai, Michel A. Huneault, Basil D. Favis

Bibliographic record

VenueJournal of Cellular Plastics · 2007
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsNational Research Council CanadaPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceBlowing agentThermoplasticDifferential scanning calorimetryPolystyreneExtrusionComposite materialRheometryStarchPolymer blendScanning electron microscopePolypropylenePolymerCopolymerPolyurethane

Abstract

fetched live from OpenAlex

This study investigates the fabrication of extruded foams from polystyrene/thermoplastic starch (PS/TPS) blends. A specially designed twinscrew extrusion process is used for starch gelatinization, PS incorporation, polymer mixing, and blowing agent incorporation. In-line rheometry is used to monitor the viscosity of the TPS/PS blends and to evaluate the plasticizing effect of 1,1,1,2 tetrafluoroethane (HFC-134a) used as blowing agent. Differential scanning calorimetry, scanning electron microscopy, density measurement, and picnometry are used to evaluate the thermal properties, the blend morphology, and the foam cell structure. Glycerol content in the TPS phase and the TPS content in the overall blend have a strong effect on the blend viscosity and, in turn, on the ability to foam the material. The foams blown with the hydrofluorocarbone alone have large open-cell content and their density cannot be reduced below 170 kg/m 3 . The addition of a small amount of ethanol however results in three-fold reductions in density and much better foam cell homogeneity.

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 head0.018
GPT teacher head0.225
Teacher spread0.206 · 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

Citations43
Published2007
Admission routes1
Has abstractyes

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