Influence of N <sub>2</sub> , O <sub>2</sub> , and H <sub>2</sub> admixtures on the electron power balance and neutral gas heating in microwave Ar plasmas at atmospheric pressure
Bibliographic record
Abstract
Abstract A combination of optical emission and absorption spectroscopy of argon 2 p –1 s transitions (Paschen notation) combined with collisional-radiative (CR) modelling of argon 2 p states was used to characterize microwave argon plasmas at atmospheric pressure in presence of N 2 , O 2 , and H 2 admixtures. In particular, the neutral gas temperature (obtained from the broadening of argon 2 p 2 –1 s 2 and 2 p 3 –1 s 2 emission lines), the number density of argon 1 s 5 atoms (obtained from absorption spectroscopy of the argon 2 p 9 –1 s 5 transition using a tunable laser diode), the electron temperature (obtained from the comparison between measured and simulated argon 2 p -to-1 s relative line emission intensities), and the electron density (obtained from the Stark broadening of the H β line and argon relative line emission intensities) were recorded as a function of the axial distance along the microwave plasma column. The results show that, for a given position in the plasma and a higher amount of admixture in the nominally pure argon plasma, the neutral gas temperature increases and the electron number density decreases, while the electron temperature and the population of argon metastable atoms first decreases and then increases at higher concentrations. With such information, a detailed analysis of the electron power balance was performed. It is found that less than 1% of the admixture in the argon plasma already absorbed more than 80% of the microwave power. Part of this energy is used for neutral gas heating, mostly through electron-impact excitation of rotational levels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".