Spark discharges at the interface of water and heptane: emulsification and effect on discharge probability
Bibliographic record
Abstract
Abstract Spark discharges in liquid have shown great potential for use in numerous applications, such as pollutant degradation, precision micromachining, and nanomaterials production. Herein, spark discharges are initiated at the interface of two immiscible liquids, heptane and water. This leads to the formation of an emulsion via mechanisms akin to bubble dynamics and instabilities at the gas–liquid. At high discharge number, an additional mechanism contributes to emulsion formation, resulting in an increase in the number of smaller heptane droplets in water. Analyses of the current–voltage characteristics show that high probability of discharge occurrence is obtained when the electrodes are aligned with the interface. This result is correlated with the low erosion rate of the electrodes. In the case of discharges at the interface, we observed that beyond a certain number of discharges, the breakdown voltage drops; far from the interface, it increases with the discharge number. Based on 2D simulation with a Monte Carlo approach to consider various droplet distribution in water, the electric field distribution is determined. The results support the fact that the decrease in breakdown voltage may be attributed to the intensification of the E -field in water close the heptane droplet. Therefore, spark discharges generated at the interface of a heptane/water system produce an emulsion of heptane in water, which facilitates the occurrence of subsequent discharges by intensifying the electric field and reducing the breakdown voltage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".