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Record W2032532518 · doi:10.7567/jjap.52.11na08

Flux Control of Carbon Nanoparticles Generated due to Interactions between Hydrogen Plasmas and Graphite Using DC-Biased Substrates

2013· article· en· W2032532518 on OpenAlexfundno aff
Kazunori Koga, M. Tateishi, Katsushi Nishiyama, Giichiro Uchida, Kunihiro Kamataki, Daisuke Yamashita, Hyunwoong Seo, Naho Itagaki, Masaharu Shiratani, N. Ashikawa, S. Masuzaki, K. Nishimura, A. Sagara, the LHD Experimental Group

Bibliographic record

VenueJapanese Journal of Applied Physics · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDust and Plasma Wave Phenomena
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsHeliconBiasingFlux (metallurgy)PlasmaHydrogenGraphiteRange (aeronautics)Materials scienceEtching (microfabrication)DivertorAtomic physicsAnalytical Chemistry (journal)VoltageChemistryNanotechnologyPhysicsComposite materialNuclear physicsEnvironmental chemistry

Abstract

fetched live from OpenAlex

Flux control of dust particles in a nanometer size range using dc bias voltage is discussed based on dust collection in a divertor simulator employed helicon hydrogen discharges. To discuss mechanisms of flux control, we have estimated etching rate of deposited dust particles due to hydrogen plasma irradiation and have measured current density toward the dc biased substrates. We have found the contribution of the etching can be negligible in a dc bias voltage V bias range between -50 and 70 V. Clear correlation between V bias dependence of current density and that of dust flux shows electrostatic force is one of important forces for controlling flux of dust particles.

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 score0.015
Threshold uncertainty score0.616

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 head0.017
GPT teacher head0.229
Teacher spread0.212 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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