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Record W3172850354 · doi:10.1063/5.0049457

Restructuring of rotating spokes in response to changes in the radial electric field and the neutral pressure of a cylindrical magnetron plasma

2021· article· en· W3172850354 on OpenAlexafffund
M. Sengupta, A. I. Smolyakov, Yevgeny Raitses

Bibliographic record

VenueJournal of Applied Physics · 2021
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversity of Saskatchewan
FundersAir Force Office of Scientific ResearchNatural Sciences and Engineering Research Council of Canada
KeywordsAtomic physicsPlasmaElectric fieldPhysicsInstabilityElectronTwo-stream instabilityIonizationEquipotentialCollision frequencyIonMechanics

Abstract

fetched live from OpenAlex

Nonlinear plasma structures in the partially magnetized E×B plasma of a cylindrical magnetron are investigated using 2D3V particle-in-cell Monte Carlo collision simulations. In the early phase of the discharge, plasma gradients and radial electric fields excite a lower hybrid type instability that forms long wavelength rotating density spokes. As the discharge grows in density by ionization and the cathode gets shielded by the formation of an ion sheath, radial electric fields diminish in the quasineutral region of the discharge. This induces a transition of the spokes into short-scale spoke-on-spoke modes. The short wavelength structures can be reversed back into a long spiral spoke by lowering the neutral pressure, which revives the radial electric fields via a turbulent plasma expansion. Plasma phenomena connected to the rotating spoke include the anomalous radial transport and loss of electrons through the spoke, azimuthal dragging of ions by the spoke’s field, plasma temperature modulations by the spoke structure, and formation of electron vortices around equipotential islands, in some cases with opposing rotations to the underlying E×B drift. Electron scattering from non-ionizing collisions with neutrals also has a minor influence on the instability.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score0.177

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 communication0.0000.000
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 head0.209
Teacher spread0.203 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

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