MétaCan
Menu
Back to cohort
Record W2050930324 · doi:10.1002/pen.20401

Thermal and rheological properties of mLLDPE/LDPE blends

2005· article· en· W2050930324 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 · 2005
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsComonomerMiscibilityMaterials scienceLinear low-density polyethyleneRheometryDifferential scanning calorimetryRheologyPolymer chemistryPolymer blendComposite materialViscoelasticityLow-density polyethyleneThermodynamicsCopolymerPolyethylenePolymer

Abstract

fetched live from OpenAlex

Abstract The thermal and rheological properties of two types of metallocene‐catalyzed linear low‐density PEs (mLLDPEs) and two LDPEs, as well as their blends, were studied using differential scanning calorimeter (DSC) measurements and rheometry. The DSC results showed that the mLLDPE‐1 based on the hexene comonomer is immiscible with both LDPEs in crystalline states, whereas the mLLDPE‐2 based on the octene comonomer is miscible with the LDPEs. This suggests that increasing the length of short chains in mLLDPEs can promote the miscibility of mLLDPE/LDPE blends. The linear viscoelastic properties confirmed the immiscibility of the mLLDPE‐1 with the LDPEs in the molten state, and the miscibility of mLLDPE‐2 with LDPEs. In addition, the Palierne [1] emulsion model provided good predictions of the linear viscoelastic data for both miscible and immiscible PE blends. However, as expected, the low‐frequency data showed a clear influence of the interfacial tension on the elastic modulus of the blends for the immiscible blends. POLYM. ENG. SCI., 45:1254–1264, 2005. © 2005 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)0.000
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 score0.020
Threshold uncertainty score0.255

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 studies0.0000.001
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 head0.016
GPT teacher head0.202
Teacher spread0.186 · 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