Plane model of fluid interface rupture in an electric field
Bibliographic record
Abstract
Modeling of an air-fluid interface in an electric field is presented. Specifically, equilibrium of the interface under the dominant forces—electric stress, surface tension, and pressure—is investigated. Since interface shape and equilibrium are related, the shape of an electrified interface is also addressed. To determine the electric stress, an analytical expression for the electric field in the vicinity of the interface is determined. The operating point of the interface is shown to exist in a three-dimensional parameter space that is divided by a critical surface into equilibrium, quasiequilibrium, and nonequilibrium subdomains. The three parameters are applied voltage, electrode separation, and pressure difference. Interface size, counterelectrode size, and fluid properties are also considered. The subdomain in which the operating point resides defines the important characteristics of the interface. The operating point moves within, and transfers between, equilibrium subdomains, and points on the critical surface represent “rupture points” of the interface. The final shape of the interface is solved iteratively using this equilibrium model. Interfaces emitting an electrospray can have a range of apex angles, and it is shown that the magnitude of this angle impacts equilibrium. It is revealed that the excess pressure difference term is critical in determining the interface shape (specifically the cone generatrix) and that minimization of the potential energy of all forces can be used to predict the magnitude of the apex angle and pressure immediately after interface rupture. The equilibrium model is important from an operational and optimization perspective, as it is useful to predict the conditions required to break equilibrium and transfer to a quasiequilibrium state (i.e., an electrospray), and the conditions necessary to maintain quasiequilibrium once it is formed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".