Vacuum ultraviolet to visible emission from hydrogen plasma: Effect of excitation frequency
Bibliographic record
Abstract
The expanding use of low pressure (p⩽10 Torr), high frequency plasmas in various applications has stimulated research toward increased operating efficiency. In order to optimize a particular plasma process, the operator can vary several “external” (operator-set) parameters, among which the excitation frequency f has received relatively little attention in the literature over the years, probably due to the difficulties encountered in designing meaningful frequency-dependent experiments. These difficulties can be avoided by the use of surface-wave discharges (SWDs), which possess great flexibility: a very broad (continuous) range of excitation frequencies, and wide ranges of operating pressures and plasma densities, under noncritical, almost perfect impedance matching with the power source. In earlier work in these laboratories, we have examined the f dependence of plasma deposition and etching experiments; the present experiments have been designed to investigate the f dependence more “directly” by turning to the plasma through its optical emission. The vacuum ultraviolet to visible emission from SWD plasmas in pure hydrogen or 7%H2 in Ar mixture has been investigated over a broad range of excitation frequency (50⩽f⩽200 MHz) using a spectrophotometer with a known transfer function. The observed f dependence of emission intensity (atomic lines and molecular bands) as f is increased is interpreted in the case of the pure H2 discharge in terms of changes from a nonstationary to a stationary electron energy distribution function (EEDF) while, in the 7%H2/Ar mixture, it is related to changes in the form of the stationary EEDF.
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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) | 0.001 | 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".