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Record W2033717425 · doi:10.1021/jf904088y

Improving the Compatibility of Zein/Poly(vinyl alcohol) Blends by Gamma Irradiation and Graft Copolymerization of Acrylic Acid

2010· article· en· W2033717425 on OpenAlexaff
Magdy M. Senna, Stéphane Salmieri, Abdel‐Wahab M. El‐Naggar, Ágnes Sáfrány, Monique Lacroix

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2010
Typearticle
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsDifferential scanning calorimetryVinyl alcoholMaterials scienceCopolymerFourier transform infrared spectroscopyAcrylic acidMonomerScanning electron microscopePolymer chemistryPolymerChemical engineeringComposite materialNuclear chemistryChemistry

Abstract

fetched live from OpenAlex

The effect of gamma irradiation and graft copolymerization with different ratios of acrylic acid monomer (AAc) on improving the compatibility of polymeric blends based on zein, as natural protein, and different ratios of poly(vinyl alcohol) (PVA) up to 50% were studied. The structure property of the polymeric blends was characterized by Fourier transform infrared spectroscopy (FTIR), mechanical testing, scanning electron microscopy (SEM), differential scanning calorimetry (DSC) and X-ray diffraction (XRD). The FTIR analysis indicated that grafted AAc into zein/PVA matrix was stabilized by hydrogen bonding. The stress-strain curves showed that pure zein films were brittle, whereas pure PVA and zein/PVA blends films were tough materials either before or after gamma irradiation. The SEM micrographs indicated the formation of multilayers during the blending of zein and PVA, and these layers turned to dispersion in matrix after gamma irradiation and grafting with AAc, suggesting an effectiveness of gamma irradiation on improving compatibility.

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 score0.014
Threshold uncertainty score0.207

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 head0.009
GPT teacher head0.193
Teacher spread0.184 · 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

Citations60
Published2010
Admission routes1
Has abstractyes

Explore more

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