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Record W4306733853 · doi:10.1021/acs.langmuir.2c01828

Charge–Dipole Attraction as a Surface Interaction between Water Droplets Immersed in Organic Phases

2022· article· en· W4306733853 on OpenAlexafffund
Hadi Afsaneh, Janet A.W. Elliott

Bibliographic record

VenueLangmuir · 2022
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsAttractionChemical physicsDipoleCharge (physics)Surface chargeSurface (topology)Materials scienceChemistryNanotechnologyPhysicsPhysical chemistryOrganic chemistryGeometry

Abstract

fetched live from OpenAlex

The dynamic behavior of emulsion droplets during their interactions with one another or with solid surfaces plays a paramount role in their ultimate stability in various applications. While the interaction of oil droplets through a surrounding aqueous phase is well understood, recent studies on the interaction of water droplets through a surrounding pure organic phase showed the presence of an unexplained attraction between water droplets at relatively long ranges. In this research study, we propose fixed-surface-charge-bulk-dipole attraction as a new interaction force between water-in-oil droplets and then derive an equation for its disjoining pressure. The behavior of water droplets in the presence and absence of this charge-dipole interaction was numerically quantified using the Stokes-Reynolds-Young-Laplace model and compared to the experimental data. Numerically calculated net force curves are in excellent agreement with experimental data from the literature when charge-dipole attraction is included, while they deviate in its absence. In addition, the water droplet and thin oil film profiles in the presence and absence of charge-dipole attraction were calculated and compared. This research indicates that charge-dipole attraction can adequately explain the mysterious force observed in some studies, which demonstrates its unexplored potential to capture the physical properties and dynamic behavior of water droplets in organic phases with useful implications to unravel unidentified interactions between emulsion droplets in different industries.

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 categoriesInsufficient payload (model declined to judge)
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 score0.057
Threshold uncertainty score0.989

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)0.0120.001

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 head0.027
GPT teacher head0.288
Teacher spread0.260 · 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.

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

Citations5
Published2022
Admission routes2
Has abstractyes

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