MétaCan
Menu
Back to cohort
Record W2036483892 · doi:10.1002/app.32989

Evaluating the behavior of castor‐oil‐based polyurethanes in acidic environments on the basis of the sorption behavior and analysis with electron ionization mass spectroscopy and neutron activation analysis

2010· article· en· W2036483892 on OpenAlexaff
Aba Mortley, Hugues W. Bonin, V. T. Bui

Bibliographic record

VenueJournal of Applied Polymer Science · 2010
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsPolyurethaneCastor oilSorptionPermeationHexamethylene diisocyanateMaterials scienceMolar massDiffusionChemical engineeringPolymer chemistryPolymerUltimate tensile strengthDynamic mechanical analysisChemistryComposite materialOrganic chemistryThermodynamicsMembrane

Abstract

fetched live from OpenAlex

Abstract Castor‐oil‐based polyurethanes (COPUs) were fabricated from 2,4‐toluene diisocyanate and hexamethylene diisocyanate. Immersion weight‐gain methods at different temperatures were used to measure the sorption and diffusion of acidic solutions into the polyurethane. It was evident from this study that these COPUs can indeed be used in acid conditions as they exhibited a low absorption of diffusing solutions (<1%) with the apparent activation energies of diffusion and permeation estimated to be 85 and 18 kJ/mol, respectively. Neutron activation analysis confirmed the possibility of the clustering of the acidic diffusing solutions because the acid/water molar values within the polymer matrix were significantly larger than those expected of the bulk solution. Mass spectroscopy indicated that any degradation that may have occurred may have been the result of fracture at the ester bond in the castor oil segment of the polyurethane. Tensile tests showed that the modulus of the saturated polymers remained above the values of the unsaturated ones. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011

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)0.002
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 score0.198
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

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