Influence of gap distance and pulse width on the properties of the emulsion produced by pulsed spark discharges at the water-heptane interface
Bibliographic record
Abstract
Abstract Electrical discharges in liquid exhibit unique properties that render them useful in numerous fields of applications. Discharges in mixtures of immiscible liquids are of interest, as they widen the scope of in-liquid discharge applications. For instance, a discharge generated at the water–heptane interface produces nanocarbons and an emulsion of heptane microdroplets in water. Herein, we investigate the influence of injected energy on emulsion properties by adjusting the inter-electrode gap distance ( δ ) in the range of 50–400 µ m and the high-voltage plateau duration ( τ ) between 200 and 500 ns (the pulse rise time is ∼100 ns). The results show that the density and size distribution of heptane droplets in the emulsion are not significantly affected by τ ; however, greater emulsion density with a similar droplet mean size is detected at higher δ . Considering that the emulsification process is driven by discharge-induced cavitation bubble dynamics, a high-speed camera is used to investigate the relationship between discharge parameters ( δ and τ ), injected energy (calculated from electrical characteristics), and emulsion properties. The results indicate that the maximum bubble radius is strongly correlated with the energy delivered during breakdown (∼25 ns). This suggests that the emulsion properties are related to breakdown mechanisms, particularly the rise in temperature and pressure during spark development. The findings reported in this study allow for a better understanding of in-liquid discharges, especially those produced at the interface of two liquids, and their application in emulsion production.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".