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Record W2019240015 · doi:10.1021/la0494167

Development of a New Methodology To Study Drop Shape and Surface Tension in Electric Fields

2004· article· en· W2019240015 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLangmuir · 2004
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsUniversity of TorontoUniversity of Alberta
Fundersnot available
KeywordsSurface tensionElectric fieldDrop (telecommunication)Rotational symmetryMechanicsSpinning drop methodCapillary lengthContact angleMaximum bubble pressure methodSessile drop techniqueOpticsChemistryClassical mechanicsPhysicsThermodynamicsMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Development of a new methodology for the study of both shape and surface tension of conducting drops in an electric field is presented. This methodology, called axisymmetric drop shape analysis-electric fields (ADSA-EF), generates numerical drop profiles in an electrostatic field, for a given surface tension. Then, it calculates the true value of the surface tension by matching theoretical profiles to the shape of experimental drops, using the surface tension as an adjustable parameter. ADSA-EF can be employed to simulate and study drop shapes in the electric field and to determine its effect on liquid surface tension. The method can also be used to measure surface tension in microgravity, where current drop-shape techniques are not applicable. The axisymmetric shape of the drop is the only assumption made in the development of ADSA-EF. The new scheme is applicable when both gravity and electrostatic forces are present. Preliminary measurements using ADSA-EF suggest that the surface tension of water increases by about 2% when an electric field with the magnitude of 10(6) V/m is applied.

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.

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 score0.811
Threshold uncertainty score0.314

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 head0.025
GPT teacher head0.262
Teacher spread0.238 · 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