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Record W1969799168 · doi:10.1063/1.4903223

Deformation of a nearly hemispherical conducting drop due to an electric field: Theory and experiment

2014· article· en· W1969799168 on OpenAlexfundno aff
Lindsey T. Corson, C. Tsakonas, B. R. Duffy, N. J. Mottram, I. Sage, C. V. Brown, S. K. Wilson

Bibliographic record

VenuePhysics of Fluids · 2014
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilLeverhulme TrustTrent UniversityNottingham Trent University
KeywordsPhysicsElectric fieldLaplace's equationMechanicsDrop (telecommunication)Contact angleSurface tensionLaplace transformClassical mechanicsElectric potentialSessile drop techniqueComputationMathematical analysisBoundary value problemVoltageThermodynamicsMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

We consider, both theoretically and experimentally, the deformation due to an electric field of a pinned nearly hemispherical static sessile drop of an ionic fluid with a high conductivity resting on the lower substrate of a parallel-plate capacitor. Using both numerical and asymptotic approaches, we find solutions to the coupled electrostatic and augmented Young–Laplace equations which agree very well with the experimental results. Our asymptotic solution for the drop interface extends previous work in two ways, namely, to drops that have zero-field contact angles that are not exactly π/2 and to higher order in the applied electric field, and provides useful predictive equations for the changes in the height, contact angle, and pressure as functions of the zero-field contact angle, drop radius, surface tension, and applied electric field. The asymptotic solution requires some numerical computations, and so a surprisingly accurate approximate analytical asymptotic solution is also obtained.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.233
Teacher spread0.224 · 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 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

Citations37
Published2014
Admission routes1
Has abstractyes

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