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Record W3094366466 · doi:10.1017/exp.2020.54

Nanoparticle Interactions and Molecular Relaxation in PLA/PBAT/Nanoclay Blends

2020· article· en· W3094366466 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

VenueExperimental Results · 2020
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsMcGill UniversityPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceCoalescence (physics)Shearing (physics)NanoparticleAdipateRelaxation (psychology)Stress relaxationChemical engineeringComposite materialNanotechnology

Abstract

fetched live from OpenAlex

Abstract Organo-modified clay nanoparticles were mixed at 1 and 5 wt% concentrations with a molten blend of 75 wt% of polylactide (PLA) and 25 wt% poly[(butylene adipate)-co-terephthalate] (PBAT). Three mixing strategies were used to control the localization of nanoclay. Small amplitude oscillatory shear (SAOS) and stress growth tests were conducted to clarify the nanoclay interactions with the blend components and its effect on the molecular relaxation behavior. SAOS and weighted relaxation spectra properties were determined before and after pre-shearing at a rate of 0.01 s −1 . Molecular relaxation and its characteristics were influenced by PLA degradation, PBAT droplet coalescence, and nanoclay localization.

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 score0.009
Threshold uncertainty score0.337

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 head0.029
GPT teacher head0.265
Teacher spread0.236 · 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