Comparison of Langmuir probe and optical emission spectroscopy on a volume-cusp filament ion source using helium
Bibliographic record
Abstract
D-Pace has a Penning ion source that runs with helium for studies of α-particle production. We want to study its plasma properties as a function of varying operational parameters, which results in varied output ion beam characteristics. In order to diagnose the ion source plasma, a collisional-radiative code for helium to be used with optical emission spectroscopy measurements is developed. This has the advantage of being non-invasive, which allows for measurements using the emitted light from the plasma. This collisional-radiative code is shown to compare well with the Yacora on the Web model developed at IPP-Garching, and improves upon it with the addition of radiation trapping. Furthermore, the sensitivity of this model to the inclusion of additional excited state populations and non-Maxwellian electron energy distribution functions is investigated. It is shown that non-Maxwellian distributions can significantly affect spectroscopy measurements. This diagnostic is benchmarked to Langmuir probe measurements on the TRIUMF-licensed volume-cusp ion source to determine whether it can replicate the measured electron density and electron temperature as a function of varied operational parameters. The operational parameters are helium gas flow (10-40 SCCM), arc voltage (100-200 V), and arc current (1-5 A). The measured plasma properties, while different in absolute value, have similar trends for each operational parameter except when varying arc voltage. It is shown that this mismatch as a function of arc voltage is likely due to high energy non-Maxwellian electrons from the cathode sheath, which are not included within the collisional-radiative model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".