Calculation of the gas temperature in a throughflow atmospheric pressure dielectric barrier discharge torch by spectral line shape analysis
Bibliographic record
Abstract
An analysis of spectral line profiles is used to calculate the gas temperature and to estimate the upper limit of the electron density in an atmospheric pressure dielectric barrier discharge torch. Two transitions are studied, that of helium (He) at 587.5nm and that of hydrogen (Hβ) at 486.1nm, both observed in the spectra of the light emitted from the gap-space region. Relevant broadening mechanisms including the Doppler and Stark effects, as well as the collision processes between an emitter and a neutral particle, are reviewed. It is deduced that the main contribution to the broadened profiles is due to collisions. Through knowledge of the van der Waals interaction potential, a general expression for determining the gas temperature is derived and applied to each transition. The results obtained from both lines are in agreement; i.e., the gas temperature is found to be 460±60K at the highest voltage applied. This value is consistent with the experimental observation that at these conditions the afterglow plasma cannot ignite paper, whose ignition temperature is 507K. Since no signature of the Stark effect can be detected either in He or Hβ transition, the upper limit of the electron density, estimated from the uncertainty on the Hβ linewidth, is 4×1012cm−3. The generality of the method allows one to determine the temperature as a function of other parameters, such as voltage and flow rate. Concerning the applied voltage, the gas temperature increases linearly from 315±30to460±60K, as derived from both lines. Over the same voltage range, a similar behavior is found for the rotational temperature, as deduced from the first negative B(Σu+2,v=0)→X(Σg+2,v=0) transition of the molecular nitrogen ion. However, the temperature varies between 325±30 and 533±15K, indicating an overestimation of the gas temperature. On the other hand, the gas temperature derived from each of the lines does not show a significant variation with the He flow rate in the range of 5–40l∕min.
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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 | 0.001 |
| 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".