Radiation Losses From a Microwave Surface-Wave Sustained Plasma Source (Surfatron)
Bibliographic record
Abstract
Surfatron is an electromagnetic (EM) field applicator yielding surface-wave (SW) discharges (SWDs) within dielectric tubes in a broad range of operating conditions. In this article, the vector wave equation for the electric field is solved numerically in 2-D to determine the influence of plasma parameters, such as electron density, normalized electron-neutral collisions frequency, plasma column length and radius, as well as the length of the surfatron body on the field strength distribution, radiation patterns, and ratio of radiated power to power absorbed in plasma. This analysis allows for estimating the efficiency of plasma generation. The model takes into account the surfatron configuration, reproducing the typical SWD plasma column behavior, namely the fact that the plasma column is “pushed out” of the surfatron interstice as absorbed power increases. The surfatron is assumed to be placed in an air-filled sphere with the surface transparent to the wave. Calculations are performed for a field frequency of 2450 MHz and a fused silica tube, considering plasma parameters typical for both atmospheric- and lower-pressure discharge gases for achieving a parametric survey. It is found that for given plasma parameters, varying the plasma column length from a few up to 30 cm significantly affects the distribution of the electric field around the surfatron and the radiation patterns. It is further shown that the radiated to absorbed power ratio increases with increasing electron density and plasma radius, and decreasing electron-neutral collision frequency. This ratio can exceed 30% for a 30-cm plasma column with a plasma radius of 3 mm and parameters typical for atmospheric and reduced gas pressures. The surfatron length at which radiation losses are minimal is at half the vacuum wavelength.
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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 | 0.001 |
| 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".