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Record W2064082583 · doi:10.1063/1.3574658

Characterization of a low-pressure chlorine plasma column sustained by propagating surface waves using phase-sensitive microwave interferometry and trace-rare-gas optical emission spectroscopy

2011· article· en· W2064082583 on OpenAlexaff
S. Mattei, Olivier Boudreault, Rohit Khare, Luc Stafford, Vincent M. Donnelly

Bibliographic record

VenueJournal of Applied Physics · 2011
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPlasmaPlasma diagnosticsAtomic physicsTorrAnalytical Chemistry (journal)Electron densityChemistrySpectroscopyElectron temperatureMicrowaveMaterials scienceIonPhysics

Abstract

fetched live from OpenAlex

Phase-sensitive microwave interferometry and trace-rare-gas optical emission spectroscopy were used to measure the line-integrated electron density, ne, and electron temperature, Te, in a high-density chlorine plasma sustained in a quartz discharge tube (inner diameter = 6 mm) by an electromagnetic surface wave at 2.45 GHz. For pressures in the 0.1–1 Torr range, ne decreased nearly linearly along the tube’s z-axis down to the critical density for surface wave propagation, where the plasma decayed abruptly. At lower pressures (< 50 mTorr), however, the plasma extended well beyond this critical point, after which ne decreased quasiexponentially toward the end of the plasma column. The length of this expansion region increased with decreasing pressure, going from ∼8 cm at 5 mTorr to ∼1 cm at 50 mTorr. Te was nearly independent of the axial position in the main plasma region and strongly decreased in the expansion region at lower pressures. The Cl2 percent dissociation, τD, obtained from the calibrated Cl2 (306 nm)-to-Xe (828 nm) emission ratio, displayed behavior similar to that of ne and Te. For example, at 5 mTorr, τD was close to 100% near the wave launcher and ∼70% at 0.5 cm from the end of the plasma column.

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 score0.109
Threshold uncertainty score0.682

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 head0.012
GPT teacher head0.221
Teacher spread0.210 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

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