A Detailed Study of Carbon Chemical Erosion in L-Mode Plasmas in the DIII-D Divertor
Bibliographic record
Abstract
A series of quiescent L-mode discharges have been used with varying degrees of divertor attachment to study carbon erosion in the DIII-D tokamak divertor. Spectra of atomic and molecular carbon plasma emissions are measured across the divertor. Predictions of carbon emission resulting from chemical and physical sputtering at the outer strikepoint are provided by the WBC transport code. For attached ionizing plasmas ( T e ~ 20 eV and carbon surface T ~ 350 K) the CD and C 2 carbon radical emissions are consistent with a total chemical sputtering yield, Y chem ~ 0.3%. During sweeps of the inner divertor leg, CD and C 2 emissions indicate the main-wall tiles has a six times higher Y chem than the divertor tiles despite identical incident plasma conditions. Emission of atomic (CI) and singly ionized carbon are dominated by physical sputtering with a measured yield Y phys ~ 2% as expected from laboratory data, indicating that chemical sputtering plays a minor role as a divertor carbon source. The Doppler broadening of the CI emission agrees with the physical sputtering model, but the predicted Doppler shift is a factor three larger than the experiment. CD and C 2 emission are reduced below detection during divertor detachment ( T e ~ 1–2 eV), an indication of the suppression of chemical erosion with Y chem < 10 -4 based on expected photon intensity from WBC.
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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".