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Record W2434169420 · doi:10.3390/membranes6020034

Emulsification Characteristics Using a Dynamic Woven Metal Microscreen Membrane

2016· article· en· W2434169420 on OpenAlexafffund
Rana Sabouni, Hassan Gomaa, Jiangshan Liu, Jesse Zhu

Bibliographic record

VenueMembranes · 2016
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceMetalMembraneChemistryMetallurgy

Abstract

fetched live from OpenAlex

An oscillatory emulsification system for the production of oil in water emulsions using a commercially available low-cost woven metal microscreen (WMMS) is investigated. The system allows for independent control of both the oscillation frequencies and amplitudes such that it provides two degrees of freedom for controlling the emulsion properties. The investigations included the production of both surfactant and particle-stabilized emulsions. The average droplet size was found to decrease when both the oscillation frequency and amplitude was increased. For surfactant-stabilized emulsions, using bi-surfactants in both the continuous and dispersed phases resulted in a smaller droplet size due to lower interfacial tension. For particle-stabilized emulsions, both the hydrodynamics of the system and the hydrophobic and hydrophilic nature of the stabilizing particles influenced the interfacial properties at the oil-water interface, which in turn affected the final droplet size and distribution with potential droplet breakage. In absence of the latter, a simple torque balance model can be used to reasonably predict the average emulsion droplet size.

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 score0.018
Threshold uncertainty score0.551

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)0.0010.000

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 head0.025
GPT teacher head0.272
Teacher spread0.247 · 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

Citations2
Published2016
Admission routes2
Has abstractyes

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