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Record W2038144077 · doi:10.1002/pen.22011

Effect of nanoclay addition on the foaming behavior of linear polypropylene‐based soft thermoplastic polyolefin foam blown in continuous extrusion

2011· article· en· W2038144077 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 · 2011
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials sciencePolypropylenePolyolefinExtrusionComposite materialExpansion ratioThermoplasticBlowing agentPolyurethaneNanocomposite

Abstract

fetched live from OpenAlex

Abstract The goal of this study is to fabricate a soft foam with high cell density and high foam expansion based on thermoplastic polyolefin (TPO), and to supply a potential candidate for soft thermoset foams. It was found that a linear polypropylene (PP)‐based TPO foam exhibited very poor cell morphology because of its weak melt strength. Nanoclay was introduced into the TPO to improve its foaming behavior. The extrusion foaming experiments demonstrated that the introduction of 0.5 wt% nanoclay significantly increased the cell morphology and expansion ratio of TPO/clay nanocomposite foams due to the enhanced cell nucleation and the possible cell coalescence suppression at low temperatures. At a high nanoclay content of 2.0 wt%, the cell density and foam expansion of foams increased continuously compared with the 0.5 wt% nanoclay addition. Our study suggested that it was possible to produce soft TPO foams with a well‐defined cell structure and high foam expansion using a continuous method, but that a proper PEOc content control was needed to maximize foam expansion. POLYM. ENG. SCI., 2011. ©2011 Society of Plastics Engineers.

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)0.001
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 score0.014
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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