Characterization of a microwave argon plasma column at atmospheric pressure by optical emission and absorption spectroscopy coupled with collisional-radiative modelling
Bibliographic record
Abstract
Optical emission and absorption spectroscopy of argon 2p-1s transitions (Paschen notation) combined with collisional-radiative (CR) modeling of argon 2p states are developed and used to determine the neutral gas temperature, the Ar 1s number density, and the electron temperature along a microwave argon plasma column at atmospheric pressure. The CR model, designed specifically for atmospheric-pressure and optically thick plasma conditions, is fully detailed and validated by comparing the relative line emission intensities of argon 2p-to-1s transitions measured experimentally with the ones predicted by the CR model using the electron temperature as the only adjustable parameter. Subsequently, the neutral gas temperature (∼1300–1600 K; obtained from the broadening of argon 2p2-1s2 and 2p3-1s2 emission lines), the Ar 1s5 number density (1–2 × 1018 m−3; obtained from absorption spectroscopy of the argon 2p9-1s5 transition using a tunable laser diode), and the electron temperature (∼1.4 eV; obtained from the comparison between the measured and simulated 2p-to-1s emission line intensities) are reported as a function of the axial distance along the microwave plasma column. The values and behaviors reveal a good agreement with those reported in previous experimental and modeling studies.
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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) | 0.001 | 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".