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Ion Implantation Study of Tungsten Alloys as Plasma Facing Components

2020· article· en· W4214522613 on OpenAlexaff
Tahreem Yousaf, Michael P. Bradley

Bibliographic record

Venue2020 IEEE International Conference on Plasma Science (ICOPS) · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced materials and composites
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTungstenMaterials scienceTantalumDivertorPlasmaMetallurgyEmbrittlementFusion powerUltimate tensile strengthHeliumFracture toughnessCopperAtomic physicsTokamak

Abstract

fetched live from OpenAlex

Tungsten-Copper-Nickle (W-Cu-Ni) and Tungsten-Tantalum (W-ta) are considered as Plasma facing components (PFCs) as several adverse effects such as embrittlement, melting, and morphological evolution has been observed in W when it is bombarded by low-energy and high-fluence Helium(He) and Deuterium(D) Plasma. (W-Ta) alloys showed better resistance as compared to pure tungsten under simulated fusion plasma conditions. W-Ni-Cu alloys are machinable grades referred to as heat sink material and selected due to their high fracture toughness and tensile strength compared to pure tungsten.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.791

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 science0.0010.000
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 head0.054
GPT teacher head0.289
Teacher spread0.235 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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