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Record W2024578504 · doi:10.1177/0021955x07079209

Physical Characteristics of PLLA/PMMA Blends and Their CO2 Blowing Foams

2007· article· en· W2024578504 on OpenAlexaff
Baisheng Yao, A. Victoria Nawaby, Xia Liao, Robert Burk

Bibliographic record

VenueJournal of Cellular Plastics · 2007
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Foaming and Composites
Canadian institutionsNational Research Council CanadaCarleton University
Fundersnot available
KeywordsMaterials scienceBlowing agentMethyl methacrylateSorptionComposite materialPolymer blendCrystallizationAnnealing (glass)PolymerPoly(methyl methacrylate)KineticsThermal decompositionChemical engineeringPolypropyleneCopolymerOrganic chemistryAdsorptionPolyurethane

Abstract

fetched live from OpenAlex

This article reports on sample preparation, characterization, CO2 sorption behavior, and foaming of blends of poly L-lactic acid (PLLA) and poly methyl methacrylate (PMMA) in compositions of 75/25, 50/50, and 25/75 wt.%. The crystallization and thermal decomposition behavior of the polymer blends were found to be dependant on concentration of PLLA in the samples. Annealing the specimens in air at 90°C for 24 h resulted in complete recrystallization in the 75/25 and 50/50 wt.% samples. Detailed studies on the sorption kinetics of CO2 in the prepared blend samples indicated gas solubilities to be comparable to those observed in neat PMMA, however, foam morphologies significantly improved in the blends when compared to neat PLLA.

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.

How this classification was reachedexpand

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)0.001
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 score0.028
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2007
Admission routes1
Has abstractyes

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