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Record W2256472522

Spectroscopic Characterization and Simulation of Chemical Sputtering Using the DiMES Porous Plug Injector in DIII-D

2006· article· en· W2256472522 on OpenAlexaff
A.G. McLean, J.W. Davis, P.C. Stangeby, N.H. Brooks, D.G. Whyte, S. W. Allen, B.D. Bray, S. Brezinsek, J.D. Elder, M.E. Fenstermacher, M. Groth, A.A. Haasz, E.M. Hollmann, R. C. Isler, C.J. Lasnier, D.L. Rudakov, J.G. Watkins, W.P. West, C C Wong

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCharacterization (materials science)InjectorMaterials scienceSpark plugPorosityNuclear engineeringSputteringAnalytical Chemistry (journal)EngineeringNanotechnologyChromatographyChemistryMechanical engineeringComposite materialThin film
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.171
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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