Composition d'équilibre des plasmas de H<sub>2</sub>, O<sub>2</sub> et N<sub>2</sub> hors équilibre thermique
Bibliographic record
Abstract
We study the evolution of the chemical species in off-thermal equilibrium H2, O2, and N2 plasmas, using both methods of maximisation of entropy and minimisation of Gibbs free energy. These gases are simple and used in electric arc cutting techniques in oil, air, or compressed air and in the arc lamination cutting technique. The study of the plasmas from these gases is an important step in understanding the complex physical processes in the CxHyOzNt type of plasmas. Our numerical calculations cover cases from 5000 to 30 000 K at pressure from 0.1-1 MPa. Comparing the results from the two methods shows that the composition of the equilibrium plasma is strongly influenced by the choice of the hypotheses on the internal temperatures. In the light of experimental measures of internal temperatures reported in the literature, we carry out an analysis of the theoretical hypothesis used herein. [Journal translation]
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".