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Record W2136915055 · doi:10.1109/plasma.2000.855051

Nonlinear skin effect in inductive discharge

2002· article· en· W2136915055 on OpenAlexaff
Valery Godyak, R. B. Piejak, B. M. Alexandrovich, A. I. Smolyakov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsLangmuir probePlasmaAtomic physicsLorentz forceRadio frequencyArgonSkin effectMagnetic fieldInductively coupled plasmaMaterials scienceCapacitive sensingCapacitive couplingCapacitively coupled plasmaInductive couplingPlasma diagnosticsPhysicsVoltageElectrical engineering

Abstract

fetched live from OpenAlex

Summary form only given. Reduction of capacitive coupling and transmission line effects and simplification of RF driving means with reduction of their cost have promoted the utilization of relatively low RF frequency in industrial ICP. RF frequencies between 0.4-2 MHz have become more and more preferable to traditional 13.56 MHz. Transition to ICP at a low driving frequency brings about a variety of non-linear phenomena associated with the RF magnetic field acting in the skin layer of an ICP. We report on a comparative study of a near-collisionless ICP driven over a wide range of frequencies between 13.56-0.45 MHz. The experiments were conducted in a cylindrical discharge chamber with a flat induction coil. The working gas was argon at 1m Torr and RF power dissipated in plasma was 200 W. Space distribution of the basic plasma parameters electron density, electron temperature, plasma potential and EEDF were measured with a Langmuir probe while the electromagnetic field and current density distribution were measured with a magnetic probe. Our measurements at low driving frequencies show that the RF Lorentz force in the skin layer is much larger than the force acting on electrons in the discharge maintaining RF electric field.

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)0.001
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.002

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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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
Published2002
Admission routes1
Has abstractyes

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