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Record W3190626222 · doi:10.1002/cjce.24287

Monitoring the reaction kinetics of waterborne 2‐pack polyurethane coatings in the dispersion and during film formation

2021· article· en· W3190626222 on OpenAlexafffundvenue
Hang Zhou, Yang Liu, Yijie Lu, Kenneth Tran, Emi Schackmann, Margaret Zhang, Mohsen Soleimani, Frédéric Lucas, Mitchell A. Winnik

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2021
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaBASF Corporation
KeywordsPolyolPolyurethaneSolventFourier transform infrared spectroscopyPolymer chemistryHexamethylene diisocyanateTrimerRelative humidityChemical engineeringDispersion (optics)Materials scienceChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract We examine the nature of the chemical reactions taking place in a waterborne two‐component polyurethane formulation consisting of an acrylic polyol latex and a hydrophilically modified polyisocyanate (hmPIC) based on the trimer of hexamethylene diisocyanate. The hmPIC was diluted with 30 wt.% of an organic solvent to reduce its viscosity and formed small (~20 nm) droplets when dispersed in water. In mixtures of the polyol and hmPIC, we monitored the rate of NCO group disappearance in the dispersed state by FTIR and showed that it varied with the choice of organic solvent. We developed a method based upon 19 F NMR to distinguish the reaction of the NCO groups with OH groups from the polyol from its reaction with water. FTIR measurements on films formed from these dispersions showed how the disappearance of NCO groups depended on relative humidity. In a more semi‐quantitative way, these measurements indicated the relative extent of urethane versus urea formation in these model coatings.

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 score0.002
Threshold uncertainty score0.137

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 head0.007
GPT teacher head0.189
Teacher spread0.182 · 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

Citations7
Published2021
Admission routes3
Has abstractyes

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