Axial- and radial-resolved electron density and excitation temperature of aluminum plasma induced by nanosecond laser: Effect of the ambient gas composition and pressure
Bibliographic record
Abstract
The spatial variation of the characteristics of an aluminum plasma induced by a pulsed nanosecond XeCl laser is studied in this paper. The electron density and the excitation temperature are deduced from time- and space- resolved Stark broadening of an ion line and from a Boltzmann diagram, respectively. The influence of the gas pressure (from vacuum up to atmospheric pressure) and compositions (argon, nitrogen and helium) on these characteristics is investigated. It is observed that the highest electron density occurs near the laser spot and decreases by moving away both from the target surface and from the plume center to its edge. The electron density increases with the gas pressure, the highest values being occurred at atmospheric pressure when the ambient gas has the highest mass, i.e. in argon. The excitation temperature is determined from the Boltzmann plot of line intensities of iron impurities present in the aluminum target. The highest temperature is observed close to the laser spot location for argon at atmospheric pressure. It decreases by moving away from the target surface in the axial direction. However, no significant variation of temperature occurs along the radial direction. The differences observed between the axial and radial direction are mainly due to the different plasma kinetics in both directions.
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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 | 0.000 | 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".