Influence of electrode gap on breakdown voltages of a multi-gap pseudospark discharge device under nanosecond pulses
Bibliographic record
Abstract
Pseudospark-sourced electron beams of high energy can be produced in multi-gap pseudospark devices under high breakdown voltages. The breakdown voltages and the gap separation of the discharge device have been studied. Collisional ionization in the gaps has been semi-quantitatively analyzed. Based on the results, the influence of the electrode gap on the breakdown voltages has been verified. Collisional ionization during device discharge begins initially in the first gap near the cathode. The electrons produced in the first gap move towards the second gap and contribute to the collisional ionization in the second gap. The process proceeds to successive gaps with collisional ionization occurring in all gaps. For wider gap separations, the number of collisional ionizations in the gap is large, and hence, more electrons move through the intermediate electrodes into the posterior gaps. This creates a cascading of collisional ionizations, leading to a decrease in breakdown voltage. The influence of the coefficient of collisional ionization on the whole process in the posterior gaps may be slight under different gap separations, as electrons moving into the posterior gaps are plentiful. The breakdown voltage mainly depends on the first gap separation near the cathode.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".