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Record W4392353748 · doi:10.1016/j.nme.2024.101629

Deuterium reclamation from C-Si codeposits using thermo-oxidation

2024· article· en· W4392353748 on OpenAlexafffund
Adam W. Cruse, J.W. Davis

Bibliographic record

VenueNuclear Materials and Energy · 2024
Typearticle
Languageen
FieldMaterials Science
TopicFusion materials and technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDeuteriumHydrogenMaterials scienceTokamakCarbon fibersOxideFusion powerSputteringNeutronPlasmaWork (physics)Analytical Chemistry (journal)RadiochemistryChemical engineeringChemistryMetallurgyThin filmAtomic physicsNanotechnologyNuclear physicsThermodynamicsComposite materialComposite number

Abstract

fetched live from OpenAlex

SiC exhibits a remarkable resistance to neutron irradiation damage and, being a low-Z material, is seen as a potential material candidate for plasma-facing components in magnetic confinement fusion reactors. The current work investigates the reclamation of deuterium from C-Si codeposits produced by sputter-deposition at temperatures from 300 K to 700 K using thermo-oxidation at 350 °C and 400 °C (623 or 673 K). While initial D content was found to be close to that of similarly-produced pure carbon codeposits, hydrogen removal from the investigated C-Si codeposits was significantly reduced comparatively. This reduced removal behaviour was found to follow closely with that observed for B-C codeposits from the DIII-D tokamak. This suggests that hydrogen removal via thermo-oxidation, where a non-carbon inclusion is known to form a stable oxide, is unlikely to be effective.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.220
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2024
Admission routes2
Has abstractyes

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