Dynamics of a pulsed negative nanosecond discharge on water surface and comparison with the positive discharge
Bibliographic record
Abstract
Abstract The fundamental physics underlying non-thermal plasmas produced by pulsed discharges at atmospheric pressure is of great interest, especially considering the technological and environmental applications of these plasmas. Discharge dynamics is highly dependent on experimental conditions, such as the propagation medium and the voltage polarity. Herein, we investigate pulsed nanosecond discharges produced by a negatively polarized voltage in a medium of air in-contact with water. Electrical and optical characterization of the discharges is achieved using the appropriate probes and ultrafast imaging, respectively. The time-integrated images are acquired under varying conditions of applied voltage, and the discharge emission is shown to be a homogenous disk at voltages between −4 and −15 kV. When the voltage is increased (absolute value) beyond −15 kV, the homogeneous emission is superimposed with filaments. The temporal evolution of the discharge emission (1 ns integration time) shows that it remains homogeneous and has a ring-like ionization front. At higher voltages and during the falling period, the discharge reignites as filaments that significantly elongate and decrease in intensity until extinguishment. A comparison of discharge emissions obtained at positive and negative polarities indicates that the features of both may be controlled by manipulating the space charge formation dynamics.
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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 | 0.000 |
| 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) | 0.002 | 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 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".