Deuterium Removal from W-Doped Carbon Films by Thermo-Oxidation
Bibliographic record
Abstract
If both carbon and tungsten were to be part of the plasma-facing armor in a future fusion reactor, it is inevitable that carbon co-deposits containing tungsten impurities will form. This work examines the effectiveness of thermo-oxidation in removing hydrogen from W-containing carbon co-deposits. Amorphous deuterated hydrocarbon (a-C:D) films were created with a CD4/Ar direct-current glow discharge and doped with W sputtered from a W mesh in front of the specimen. The W concentration in the specimens ranged from 0 to 35 at. % W/(W + C). The films were oxidized at 350°C, in 2 Torr pure O2 for time increments totaling 8 h. The D content of the films was measured before and at various stages of the oxidation exposure using laser thermal desorption spectroscopy. Essentially all deuterium was removed from films containing very little or no W doping [<0.1% W/(W + C)]. For films with more W [few percent W/(W + C)], oxidation was less effective at removing D. For two specimens with 2.4% and 35% W/(W + C), oxidation was completely ineffective at removing D.
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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".