Ultra-high-resolution optical absorption spectroscopy of DC plasmas at low pressure using a supercontinuum laser combined with a laser line tunable filter and a HyperFine spectrometer
Bibliographic record
Abstract
Abstract Optical absorption spectroscopy of non-equilibrium plasmas using a supercontinuum laser combined with a laser line tunable filter and a HyperFine spectrometer is examined. Owing to the <2 pm spectral resolution of the HyperFine system, details on the absorption line intensity, position and width can be obtained with very high precision using a broadband light emission source. As an example, absorption spectroscopy measurements were recorded in a reduced-pressure, nominally pure argon DC plasma column and allowed for the determination of the neutral gas temperature and the Ar 1s 2 and Ar 1s 4 (Paschen notation) number densities. At a pressure of 1 Torr, a discharge current of 20 mA, and an absorption length of 18 cm, the analysis of the Ar 2p 3 -1s 2 and Ar 2p 8 -1s 4 absorption lines at respectively 840.8 nm and 842.5 nm resulted in number densities of n 1 s 2 = 5.5 × 10 15 m −3 and n 1 s 4 = 1.1 × 10 16 m −3 and a neutral gas temperature of T g = 340 K. These values are typical of DC discharges operated under similar experimental conditions. While the fractional absorption of both lines decreased with decreasing optical absorption path, the number densities remained the same, as expected. Finally, the number densities increased with increasing discharge current, a result also coherent with the literature.
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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 | 0.001 | 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".