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Record W1985224699 · doi:10.1021/ie8009632

Structure and Properties of Blend Films Prepared from Castor Oil-Based Polyurethane/Soy Protein Derivative

2008· article· en· W1985224699 on OpenAlexaff
Dagang Liu, Huafeng Tian, Lina Zhang, Peter R. Chang

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2008
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsAgriculture and Agri-Food Canada
FundersNatural Science Foundation of Guangdong Province
KeywordsMaterials scienceMiscibilityDifferential scanning calorimetryCastor oilUltimate tensile strengthSoy proteinPolyurethaneThermal stabilityChemical engineeringScanning electron microscopeFourier transform infrared spectroscopyDynamic mechanical analysisComposite materialPolymer chemistryChemistryPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

We successfully prepared a series of transparent blend films from castor oil-based polyurethane (PU) and p -phenylene diamine soy protein (PDSP). The miscibility, morphology, and properties of the blend films were investigated with Fourier transform infrared spectroscopy, differential scanning calorimetry, dynamic mechanical thermal analysis, scanning electron microscopy, moisture adsorption, thermal degradation, and tensile testing. The results revealed that the PDSP exhibited certain miscibility with PU varied its content from 10 to 80 wt % and also showed the strong hydrogen-bond and chemical cross-linking interactions lied between PU and PDSP. With an increase in the PU content, the elongation at break, thermal stability, and water resistance were improved whereas the tensile strength and Young’s modulus decreased. It is worth noting that modified soy protein could be blended with hydrophobic polyurethane to obtain the blend films having good mechanical properties and optical transmittance.

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 score0.004
Threshold uncertainty score0.774

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 integrity0.0000.001
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 head0.082
GPT teacher head0.274
Teacher spread0.192 · 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

Citations38
Published2008
Admission routes1
Has abstractyes

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