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Record W2992764589 · doi:10.1021/acsomega.9b03331

Thickness Dependence of the Diffusivity and Solubility of Cyclohexane in Nanoscale Bitumen Films

2019· article· en· W2992764589 on OpenAlexafffund
Vadim Kislitsin, Phillip Choi

Bibliographic record

VenueACS Omega · 2019
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCyclohexaneNanoscopic scaleMaterials scienceSolubilityAbsorption (acoustics)DispersityDiffusionGravimetric analysisAnalytical Chemistry (journal)Thermal diffusivityChemical engineeringHildebrand solubility parameterChemistryPolymer chemistryComposite materialOrganic chemistryNanotechnologyThermodynamics

Abstract

fetched live from OpenAlex

/s. A double-first-order kinetics model fits well to the absorption data, suggesting that there exists a concentration gradient of polar (or nonpolar) bitumen molecules in the nanoscale films. This is because the hydrophilic substrates attract the relatively polar fraction of bitumen molecules to the region close to the substrates and the nonpolar fraction resides in the region near the free surface. As a result, the measured diffusion coefficients exhibited positive thickness dependence when the thickness of the bitumen films was at the nanoscale. The molecules near the substrates tended to diffuse slower than those in the free surface region. However, diffusivity was insensitive to the cyclohexane RS. On the other hand, the measured solubility of cyclohexane in the nanoscale bitumen films exhibited no thickness dependence but strong cyclohexane RS dependence. These results suggest that solubility is not affected by the inhomogeneous distribution of bitumen molecules in the nanoscale films and that it follows more or less Henry's law.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.220

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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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 designObservational
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

Citations9
Published2019
Admission routes2
Has abstractyes

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