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Record W2163304606 · doi:10.1002/pen.11045

Strategies for achieving ultra low‐density polypropylene foams

2002· article· en· W2163304606 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePolymer Engineering and Science · 2002
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPolypropyleneExpansion ratioMaterials scienceBlowing agentExtrusionComposite materialVolume expansionThermal expansionCoalescence (physics)Volume (thermodynamics)Blow molding

Abstract

fetched live from OpenAlex

Abstract The volume expansion behavior of low‐density polypropylene foams in extrusion is investigated in this paper. Since escape of blowing agent from the foam would cause the foam to contract, and to have low expansion, efforts were made to prevent gas loss during foaming. The basic strategies to the promotion of a large volume expansion ratio are: to use a branched material for preventing cell coalescence; to use a long‐chain blowing agent with low diffusivity; to lower the melt temperature for decreasing gas loss during expansion; and to optimize the processing conditions in the die for avoiding too‐rapid crystallization. Use of a branched polypropylene resin was required to achieve large volume expansion because prevention of cell coalescence will retard gas loss from the extruded foam to the environment. The foam morphologies of linear and branched polypropylene materials at various processing temperatures were studied using a single‐screw tandem foam extrusion system and their volume expansion behaviors were compared. Ultra lowdensity, fine‐celled polypropylene foams with very high expansion ratio up to 90 fold were successfully produced from the branched polypropylene resins.

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.

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)0.000
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 score0.035
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

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 communication0.0000.001
Open science0.0000.000
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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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