MétaCan
Menu
Back to cohort
Record W2060656348 · doi:10.1002/app.32224

Polyurethanes from benzene polyols synthesized from vegetable oils: Dependence of physical properties on structure

2010· article· en· W2060656348 on OpenAlexaff
Marie‐Josée Dumont, Xiaohua Kong, Suresh S. Narine

Bibliographic record

VenueJournal of Applied Polymer Science · 2010
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsTrent UniversityUniversity of Alberta
Fundersnot available
KeywordsDifferential scanning calorimetryFourier transform infrared spectroscopyThermogravimetric analysisPolyurethaneGlass transitionMaterials scienceMonomerPolymer chemistrySteric effectsDynamic mechanical analysisTriolInfrared spectroscopyChemical engineeringOrganic chemistryChemistryPolymerComposite materialDiolThermodynamics

Abstract

fetched live from OpenAlex

Abstract Asymmetric and symmetric aromatic triol isomers were synthesized from erucic acid. The pure asymmetric and symmetric triols were crosslinked with MDI into their corresponding polyurethane sheets. The physico‐chemical properties of these polyurethanes were studied by Fourier transform infrared (FTIR) spectroscopy, X‐ray diffraction (XRD), differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), thermogravimetric analysis coupled with Fourier transform infrared (TGA‐FTIR) spectroscopy, and tensile analysis. The A‐PU and S‐PU demonstrated differences in their glass transition temperatures ( T g ) and crosslinking densities. The difference in T g of these polyurethanes could be explained by the differences in crosslinking densities, which could be related to the increase in steric hindrance, to the crosslinking MDI molecules, between adjacent hydroxyl groups of the asymmetric triol monomers. Overall, it was found that both polyurethanes had similar mechanical and thermal properties. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010

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 score0.004
Threshold uncertainty score0.840

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0020.000
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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied Polymer ScienceSame topicPolymer composites and self-healingFrench-language works237,207