Hot-electron influence on<i>L</i>-shell spectra of multicharged Kr ions generated in clusters irradiated by femtosecond laser pulses
Bibliographic record
Abstract
Strong L-shell x-ray emission has been obtained from Kr clusters formed in gas jets and irradiated by 60-500-fs laser pulses. Spectral lines from the F-, Ne- Na-, and Mg-like charge states of Kr have been identified from highly resolved x-ray spectra. Spectral line intensities are used in conjunction with a detailed time-dependent collisional-radiative model to diagnose the electron distribution functions of plasmas formed in various gas jet nozzles with various laser pulse durations. It is shown that L-shell spectra formed by relatively long nanosecond-laser pulses can be well described by a steady-state model without hot electrons when opacity effects are included. In contrast, adequate modeling of L-shell spectra from highly transient and inhomogeneous femtosecond-laser plasmas requires including the influence of hot electrons. It is shown that femtosecond-laser interaction with gas jets from conical nozzles produces plasmas with higher ionization balances than plasmas formed by gas jets from Laval nozzles, in agreement with previous work for femtosecond laser interaction with Ar clusters.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".