High-voltage, high repetition rate nanosecond pulse generator for high-pressure non-thermal plasma generation
Bibliographic record
Abstract
Summary form only given. Recently, high-voltage pulsed power has received increasing attention in the fields of plasma-assisted ignition, and combustion. These applications require a high degree of disequilibrium and overvoltage to produce highly energetic electrons and molecules, which drive the plasma chemistry. Therefore, high-voltage, low duty cycle, and high frequency pulse generators are required as sources for the production of such energetic particles. A few commercial solid-state generators are available, but their introduction in research laboratory and industrial environments is hindered by their high cost. In this contribution we present the development of a low cost high-voltage, high frequency pulse generator used for the production of atmospheric pressure air plasmas. The generator is equipped with short-circuit protection to withstand operation in harsh electrical environments. Corona, glow and spark discharges are produced in atmospheric pressure air at voltages of tens of kilovolts and pulse repetition frequencies up to 10 kHz. Synchronized electrical diagnostics are presented and used to explain the generator's operating principles. Imaging and optical emission spectroscopy results are presented to assess the level of disequilibrium in the plasma. Results show that low gas temperatures can be maintained, all the while achieving high electronic and vibrational temperatures in species such as nitrogen. Also, results show that the generator is robust, and capable of operating in short-circuit mode for extended periods of time without any observed damage to the pulse generator.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".