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Record W2932440466 · doi:10.1177/0262489319839632

Density graded polyethylene foams: Effect of processing conditions on mechanical properties

2019· article· en· W2932440466 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 · 2019
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsPolytechnique MontréalMcGill UniversityUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite materialBlowing agentFlexural strengthCompression moldingScanning electron microscopeFlexural modulusPolyethyleneRelative densityHigh-density polyethyleneIzod impact strength testModulusMolding (decorative)Compression (physics)Low-density polyethyleneMoldPolyurethaneMicrostructure

Abstract

fetched live from OpenAlex

Uniform foams (UF) and density graded foams (DGF) were produced by using similar or different temperatures on both sides of a compression molding system. The samples were produced using linear low density polyethylene as the matrix and activated azodicarbonamide as the chemical blowing agent. Morphological properties of the produced samples were analyzed via scanning electron microscopy to relate them to their mechanical properties. In particular, flexural and impact properties are reported for samples produced under a range of temperatures (140–200°C) and blowing agent concentration (0.7–1.0 wt%). The experimental results showed that a significant difference can be obtained in flexural modulus (up to 17%) and impact strength (up to 48%) depending on the side the stress is applied on. In all cases, the DGF showed better mechanical responses than UF of similar relative density for the range of conditions tested.

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 score0.002
Threshold uncertainty score0.655

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)0.0000.000

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 head0.008
GPT teacher head0.215
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