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Record W2021073460 · doi:10.1002/mame.201100147

Morphology and Properties of Poly(propylene)/Ethylene‐Octene Copolymer Blends Containing Nanosilica

2011· article· en· W2021073460 on OpenAlex
Sung Hyo Lee, Mathieu Bailly, Marianna Kontopoulou

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

VenueMacromolecular Materials and Engineering · 2011
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsQueen's University
Fundersnot available
KeywordsMaterials scienceCopolymerCoalescence (physics)OcteneMorphology (biology)NanoparticleUltimate tensile strengthEthyleneComposite materialMicrostructurePhase (matter)Chemical engineeringTacticityPolymerNanotechnologyCatalysisOrganic chemistryPolymerization

Abstract

fetched live from OpenAlex

Abstract The effect of nanosilica addition on the morphology and mechanical properties of blends of isotactic PP and an ethylene/octene copolymer (EOC) is studied. TEM reveals that the well‐dispersed nanoparticles are localized exclusively in the PP phase. In the presence of a maleated PP compatibilizer addition of nanosilica leads to more finely dispersed EOC domains and a finer co‐continuous morphology. The nanoparticles reduce the rate of coalescence of the dispersed phase domains. The mechanical properties depend on the EOC and PP ‐g‐ MA content. Tensile and flexural properties are significantly enhanced in the presence of the silica nanoparticles, whereas impact properties are not affected. These enhancements are attributed to the favorable microstructure of the blends. magnified image

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 score0.008
Threshold uncertainty score0.678

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 head0.018
GPT teacher head0.191
Teacher spread0.174 · 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