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Record W4234979038 · doi:10.32920/ryerson.14653779.v1

Rheological properties and flow behaviour of wax-stabilized water-in-oil emulsions

2021· preprint· en· W4234979038 on OpenAlexaff
Samira Haj‐Shafiei

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRheologyWaxEmulsionMaterials sciencePulmonary surfactantParaffin waxPhase (matter)Chemical engineeringAqueous two-phase systemFlow propertiesMineral oilChromatographyComposite materialChemistryOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

The objective of this study was to characterize the flow and rheological behaviour of model wax-stabilized water-in-oil (W/O) emulsions consisting of light mineral oil, paraffin wax and glycerol monooleate as the oil phase and water as the dispersed aqueous phase. An[sic] laboratory-scale benchtop flowloop system was used to explore the flow behaviour of the emulsions' oil phase (oil, paraffin wax and surfactant). The key contribution from this work was that the higher initial temperature gradient (40°C compared to 19°C) experienced by the rapidly-cooled oil led to more initial deposition on the flowloop inner wall. The rheological properties of W/O emulsions with different water cuts (10-50wt%) were also studied. Rotational, oscillatory rheology and creep compliance and recovery were characterized on emulsions aged up to 28 days. Overall, the results demonstrated that emulsion composition, and age could significantly influence an emulsion's flow behaviour and rheological properties.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.028
GPT teacher head0.229
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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
Published2021
Admission routes1
Has abstractyes

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Same topicRheology and Fluid Dynamics StudiesFrench-language works237,207