MétaCan
Menu
Back to cohort
Record W2018461761 · doi:10.1002/pen.22092

Isothermal and non‐isothermal crystallization behavior of PET nanocomposites

2011· article· en· W2018461761 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 crystallization and properties
Canadian institutionsMcGill UniversityPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceIsothermal processDifferential scanning calorimetryCrystallizationNanocompositePolyethylene terephthalateChemical engineeringEndothermCompoundingCrystallitePolymer chemistryComposite materialThermodynamicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract Polyethylene terephthalate (PET)/clay nanocomposites (PCNs) containing 1 wt% Cloisite 30B (C30B) were prepared via melt compounding. Modulated differential scanning calorimetry (MDSC) for isothermally crystallized samples revealed that the third endotherm at the highest temperature may be attributed to the recrystalization and melting of crystals, reorganized during heating. The first and second endotherms may be associated with melting of the secondary and primary crystals, respectively. The overall isothermal crystallization rate in PCNs was faster than in the neat resin. Growth kinetics revealed that the work required for chain folding and the equilibrium melting temperature in PCNs were somewhat higher than for neat PET. During isothermal crystallization, the steric hurdles introduced by clay layers lead to a reduction in the transport of the PET chains into crystallites. The effective non‐isothermal activation energy for the PCNs was higher than for PET, possibly leading to less perfect crystals in the PCNs. POLYM. ENG. SCI., 2012. © 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)0.000
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 score0.019
Threshold uncertainty score0.356

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 head0.013
GPT teacher head0.203
Teacher spread0.190 · 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