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Record W2766655074 · doi:10.1139/cjp-2017-0478

Comments on the Langmuir probe measurements of radio-frequency capacitive argon–hydrogen mixture discharge at low pressure

2017· article· en· W2766655074 on OpenAlexvenueno aff
Murat Tanışlı, Nesli̇han Şahi̇n, Süleyman Demi̇r

Bibliographic record

VenueCanadian Journal of Physics · 2017
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsLangmuir probeHydrogenArgonPlasma diagnosticsLangmuirPlasmaAtomic physicsElectron densityCapacitive sensingAnalytical Chemistry (journal)Electron temperatureRadio frequencyPhysicsChemistryElectrical engineering

Abstract

fetched live from OpenAlex

In this paper, the current–voltage graphs of discharge in the chamber of capacitive coupled radio frequency (CCRF) at low pressure were presented for Langmuir probe. The Langmuir probe measurements for estimating the electron density and temperature in capacitive coupled discharges at low pressures were presented and the electron temperatures of the Ar–H 2 mixture discharge generated at different conditions were reported using the Langmuir probe. The focus of this study is that the CCRF discharge can be determined and explained using the characteristics of plasma by means of Langmuir probe measurements for the different hydrogen rates in Ar–H 2 mixture discharge. The measurement results of Langmuir probe gave values around 10 15 m −3 for the electron density. The floating potential depended on the electronegative gas amount. It was found that the increase of hydrogen gas amount in the mixture discharge caused the decrease of the floating potential. Also, a decrease in the argon (Ar) metastable with the increase in hydrogen (H 2 ) content was obtained. When the applied radio frequency (RF) power was increased, the thickness and collisionless sheath occurring at lower RF power could transform to thin sheath.

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 score0.693
Threshold uncertainty score0.337

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 head0.026
GPT teacher head0.215
Teacher spread0.189 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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