The effect of electron multiplication on the electroluminescence yield of pure xenon and xenon-neon gas proportional scintillation counters: experimental and simulation results
Bibliographic record
Abstract
In applications of the gas proportional scintillation counter to the detection of very low energy X-rays, the addition of the light noble gas neon to the usual xenon filling improves the collection of primary electrons that would have originated near the detector window. However, xenon-neon mixtures produce lower electroluminescence yields than pure xenon. The highest electroluminescence yield that can be achieved without jeopardizing the energy resolution is limited by the additional fluctuations introduced by electron multiplication and, consequently these detectors are usually operated at reduced electric fields below the ionization threshold. In this work, a compromise between electroluminescence output and energy resolution is investigated for xenon-neon mixtures at a total pressure of 800 Torr (with 5%, 10%, 20%, 40%, 70%, 90% and 100%Xe), and for 5.9 keV X-rays. Using experimental and Monte Carlo studies, the effects of introducing a limited amount of charge multiplication on the electroluminescence yield and on the detector energy resolution are analysed and discussed, and the optimum operating conditions for gas proportional scintillation work are established.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".