Spectroscopic Characterization and Simulation of Chemical Sputtering Using the DiMES Porous Plug Injector in DIII-D
Bibliographic record
Abstract
A self-contained gas injection system for the Divertor Material Evaluation System (DiMES) on DIII-D has been employed for in-situ study of chemical erosion in the tokamak divertor environment. The Porous Plug Injector (PPI) releases methane, a major component of molecular influx due to chemical sputtering of graphite, from the tile surface into the plasma at a controlled rate through a porous graphite surface. Perturbation to local plasma is minimized, while also simulating the immediate environment of methane molecules released from a solid graphite surface. The release rate was chosen to be of the same order of magnitude as natural sputtering. Photon efficiencies of CH{sub 4} for measured local plasma conditions are reported. The contribution of chemical versus physical sputtering to the source of C{sup +} at the target is assessed through measurement of CII and CD/CH band emissions during release of CH{sub 4} from the PPI, and due to intrinsic emission.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".