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Record W3113012972 · doi:10.1039/d0ra07485c

Morphology and performance relationship studies on biodegradable ternary blends of poly(3-hydroxybutyrate-<i>co</i>-3-hydroxyvalerate), polylactic acid, and polypropylene carbonate

2020· article· en· W3113012972 on OpenAlexafffund
Mary M. Hedrick, Feng Wu, Amar K. Mohanty, Manjusri Misra

Bibliographic record

VenueRSC Advances · 2020
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsUniversity of GuelphDiscovery Centre
FundersMinistry of Agriculture, Food and Rural AffairsAgriculture and Agri-Food CanadaNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural AffairsUniversity of Guelph
KeywordsPolylactic acidMaterials scienceBiodegradable polymerElongationPolypropyleneUltimate tensile strengthTernary operationToughnessPolymerPolymer blendComposite materialWettingChemical engineeringCopolymer

Abstract

fetched live from OpenAlex

optimizing the composition ratio and morphological structure is, to the best of the authors' knowledge, reported here for the first time. The optimal blend formulation is comprised of 20% PLA, 40% PHBV, and 40% PPC, which possesses a tensile strength measuring 44 MPa and an elongation at break measuring at 215%. Thermal performance analysis revealed an HDT value of 72 °C. The Harkins equation predicts that the three immiscible polymers formed a complete wetting morphology, which was confirmed by scanning electrical microscopy. As the PPC content of the ternary blends is increased, the material undergoes morphological transition from droplet to co-continuous structure, resulting in significant improvement of elongation at break (approximately 40 times higher than that of the PLA-PHBV binary blend). Excellent stiffness and over 200% elongation at break make these sustainable ternary blends feasible for use in packaging as substitutes for certain non-biodegradable petroleum-based single use plastics.

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)0.000
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 score0.214
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.043
GPT teacher head0.268
Teacher spread0.224 · 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

Citations25
Published2020
Admission routes2
Has abstractyes

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