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Record W3164607668 · doi:10.1177/02624893211018825

Morphological, thermal and mechanical properties of polypropylene foams via rotational molding

2021· article· en· W3164607668 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCellular Polymers · 2021
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsMaterials sciencePolypropyleneComposite materialBlowing agentCompression moldingMolding (decorative)Thermal conductivityDeformation (meteorology)Compression (physics)Mold

Abstract

fetched live from OpenAlex

In this work, polypropylene (PP) was foamed via rotational molding using a chemical blowing agent (CBA) based on azodicarbonamide over a range of concentration (0 to 0.5% wt.). The samples were then analyzed in terms of morphological, thermal and mechanical properties. The morphological analysis showed a continuous increase in the average cell size and cell density with increasing CBA content. Increasing the CBA content also led to lower foam density and thermal conductivity. Similarly, all the mechanical properties (tension, flexion and impact) were found to decrease with increasing CBA content. Finally, the efficiency of the rotomolding process was assessed by producing neat PP samples via compression molding. The results showed negligible differences between the rotomolded and compression molded properties at low deformation and rate of deformation indicating that optimal rotomolding conditions were selected.

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 score0.010
Threshold uncertainty score0.774

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 communication0.0000.000
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 head0.017
GPT teacher head0.206
Teacher spread0.189 · 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