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Record W2049917073 · doi:10.1002/mame.201000417

The Effects of Process Engineering on the Performance of PLA and PHBV Blends

2011· article· en· W2049917073 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

VenueMacromolecular Materials and Engineering · 2011
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMiscibilityMaterials scienceCrystallinityPolymer blendPolymerComposite materialModulusGlass transitionUltimate tensile strengthElongationPhase (matter)CopolymerOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The effects of process engineering in the fabrication of PHBV, PLA and their blends prepared by melt blending are studied. The elongation of an optimized blend can be improved by 148 and 250% over the virgin PHBV and PLA polymers, respectively. DSC shows that the two polymers are immiscible in blends of any composition. The crystallinity of PHBV is hindered by the presence of PLA. UV‐Vis demonstrates the opacity of the blend with incorporation of PHBV to the PLA phase. The observed tensile modulus of the optimized sample is compared with theoretical values from the rule of mixtures. Gordon‐Taylor's equation is applied on the glass transition temperatures for theoretical modeling to explain the miscibility of the polymers. 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 score0.003
Threshold uncertainty score0.295

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 head0.007
GPT teacher head0.164
Teacher spread0.157 · 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