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Record W4366963660 · doi:10.1039/d3sm00233k

Flows of a nonequilibrated aqueous two-phase system in a microchannel

2023· article· en· W4366963660 on OpenAlexfundno aff
Niki Abbasi, Janine K. Nunes, Zehao Pan, Tejas Dethe, Ho Cheung Shum, Andrej Košmrlj, Howard A. Stone

Bibliographic record

VenueSoft Matter · 2023
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaResearch Grants Council, University Grants CommitteeNational Science Foundation
KeywordsMicrochannelMicrofluidicsMarangoni effectAqueous solutionVolumetric flow rateMerge (version control)Materials scienceFlow (mathematics)PolymerSteady state (chemistry)MechanicsChemistryNanotechnologyPhysicsConvectionComputer science

Abstract

fetched live from OpenAlex

Liquid-liquid phase separation is a rich and dynamic process, which recently has gained new interest, especially in biology and for material synthesis. In this work, we experimentally show that co-flow of a nonequilibrated aqueous two-phase system within a planar flow-focusing microfluidic device results in a three-dimensional flow, as the two nonequilibrated solutions move downstream along the length of the microchannel. After the system reaches steady-state, invasion fronts from the outer stream are formed along the top and bottom walls of the microfluidic device. The invasion fronts advance towards the center of the channel, until they merge. We first show by tuning the concentration of polymer species within the system that the formation of these fronts is due to liquid-liquid phase separation. Moreover, the rate of invasion from the outer stream increases with increasing polymer concentrations in the streams. We hypothesize the invasion front formation and growth is driven by Marangoni flow induced by the polymer concentration gradient along the width of the channel, as the system is undergoing phase separation. In addition, we show how at various downstream positions the system reaches its steady-state configuration once the two fluid streams flow side-by-side in the channel.

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 score0.081
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.248
Teacher spread0.237 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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