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Record W3194646877 · doi:10.1021/acs.langmuir.1c01274

Phase Separation of an Evaporating Ternary Solution in a Hele-Shaw Cell

2021· article· en· W3194646877 on OpenAlexafffund
Ricardo Arturo Lopez de la Cruz, Noor Schilder, Xuehua Zhang, Detlef Lohse

Bibliographic record

VenueLangmuir · 2021
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Thin Films
Canadian institutionsUniversity of Alberta
FundersH2020 European Research CouncilNatural Sciences and Engineering Research Council of CanadaNederlandse Organisatie voor Wetenschappelijk OnderzoekCanada Research Chairs
KeywordsTernary operationInstabilityNucleationMarangoni effectEvaporationThermodynamicsSeparation processChemistryHele-Shaw flowViscous fingeringPhase (matter)Work (physics)Materials scienceChemical physicsChemical engineeringChromatographySurface tensionPorous mediumMechanicsOrganic chemistryPhysicsReynolds number

Abstract

fetched live from OpenAlex

In the present work, we investigate the dynamic phenomena induced by solvent evaporation from ternary solutions confined in a Hele-Shaw cell. The model solutions consist of ethanol, water, and oil, and with the decrease in ethanol concentration by selective evaporation, they may undergo microdroplet formation via the ouzo effect or macroscopic liquid-liquid phase separation. We varied the initial concentration of the three components of the solutions. For all ternary solutions, evaporation of the good solvent ethanol from the gas-liquid interface, aligned with one side of the cell, leads to a Marangoni instability at the early stage of the evaporation process. The presence of the Marangoni instability is in agreement with our recent predictions based on linear stability analysis of binary systems. However, the location and onset of subsequent microdroplet formation and phase separation are the result of the interplay between the Marangoni instability and the initial composition of the ternary mixtures. We classified the ternary solutions into different groups according to the initial concentration of oil. For each group, based on the ternary diagram of the mixture, we offer a rationale for the way phase separation takes place and discuss how the instability influences droplet nucleation. Our work helps us to understand under what conditions and where droplet nucleation can take place when advection is present during phase separation inside a microfluidic device.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.235

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 head0.009
GPT teacher head0.259
Teacher spread0.250 · 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 routes2
Has abstractyes

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