Photo-ionized neon plasmas induced by radiation pulses of a laser-plasma EUV source and a free electron laser FLASH
Bibliographic record
Abstract
Abstract In this work, a laser-produced plasma extreme ultraviolet source and a free electron laser were used to create Ne photo-ionized plasmas. In both cases, a radiation beam was focused onto a gas stream injected into a vacuum chamber synchronously with the radiation pulse. Extreme ultraviolet radiation from the plasma spanned a wide spectral range with pronounced maximum centered at λ = 11 ± 1 nm while the free electron laser pulses were emitted at a wavelength of 32 nm. The power density of the focused plasma radiation was approximately 2 × 107 W/cm2 and was seven orders of magnitude lower compared with the focused free electron laser beam. Radiation fluences in both experimental conditions were comparable. Despite quite different spectral characteristics and extremely different power densities, emission spectra of both photo-ionized plasmas consist of the same spectral lines within a wavelength range of 20 to 50 nm, however, with different relative intensities of the corresponding lines. The dominating spectral lines originated from singly charged ions (Ne II); however, Ne III lines were also detected. Additionally, computer simulations of the emission spectra, obtained for photo-ionized plasmas, driven by the plasma extreme ultraviolet source, were performed. The corresponding measured and calculated spectra are presented. An electron temperature and ionic composition were estimated. Differences between the experimental spectra, obtained for both irradiation conditions, were analyzed. The differences were attributed mainly to different energies of driving photons.
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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".