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Record W2313765567 · doi:10.1103/physreve.85.046311

Ring stains in the presence of electrokinetic interactions

2012· article· en· W2313765567 on OpenAlexaff
Siddhartha Das, Suman Chakraborty, Sushanta K. Mitra

Bibliographic record

VenuePhysical Review E · 2012
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCoffee ring effectElectrokinetic phenomenaDrop (telecommunication)Materials scienceChemical physicsEvaporationDeposition (geology)Pressure dropVoltage dropMechanicsSubstrate (aquarium)Molecular physicsNanotechnologyAnalytical Chemistry (journal)ChemistryCurrent (fluid)ThermodynamicsPhysicsChromatography

Abstract

fetched live from OpenAlex

In this paper, we delineate the consequences of electrokinetic interactions on the "coffee stain" effect, induced by the deposition of particles during drop evaporation. We consider evaporation of an electrolytic drop in contact with a charged substrate and probe the effects of electrical double layer formation at the drop-substrate interface on the dynamics of particles suspended inside the drop. We show that the simultaneous considerations of streaming potential and flow-actuation-mechanism-independent description of the evaporation flux and the depth average velocities result in an enhanced induced radial pressure gradient. As a result, the deposition speed of the particles in the disordered packing regime, occurring at the end of the lifetime of the drop [Marin et al., Phys. Rev. Lett. 107, 085502 (2011)], is greatly enhanced. This, in turn, is likely to signify an augmented degree of disordering in the evaporation-induced particle deposition.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.020
GPT teacher head0.299
Teacher spread0.280 · 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 designSimulation or modeling
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

Citations25
Published2012
Admission routes1
Has abstractyes

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