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Record W2571591483 · doi:10.1139/cjp-2016-0300

Study the optimum dimensions and operating parameters of Penning ion source

2017· article· en· W2571591483 on OpenAlexvenueno aff
A.G. Helal, H. El‐Khabeary, S.I. Radwan

Bibliographic record

VenueCanadian Journal of Physics · 2017
Typearticle
Languageen
FieldEngineering
TopicIon-surface interactions and analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCathodeAnodeArgonAtomic physicsIon sourceIonIon gunPhysicsAperture (computer memory)Ion beamBeam (structure)Ion beam depositionFaraday cupMaterials scienceAnalytical Chemistry (journal)OpticsChemistryElectrode

Abstract

fetched live from OpenAlex

In this work, design and construction of a DC cold cathode Penning ion source is described. It consists of cylindrical hollow anode and two movable disc cathodes that are placed symmetrically at two ends of the anode. The electrical discharge and the output ion beam characteristics of the ion source are measured using argon gas. It is found that the optimum dimensions of anode–cathode distance, ion exit aperture diameter, and ion exit aperture – Faraday cup distance are equal to 8, 1.5, and 30 mm, respectively. The ion source efficiency was calculated at discharge current equal to 1.2 mA, different anode–cathode distances and pressures using argon gas. It is found that at anode–cathode distance equal to 8 mm and pressure equal to 7 × 10 −4 mmHg, a maximum ion source efficiency equal to 27.1% can be obtained. The surface hardness of molybdenum specimen is measured after exposure to argon ion beam for two hours at pressure equal to 7 × 10 −4 mmHg, discharge voltage equal to 3.5 kV, discharge current equal to 0.6 mA, and output ion beam current equal to 165 μA using argon gas. It is found that the surface hardness of molybdenum specimen is decreased by a factor of 24.2%.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.246
Teacher spread0.224 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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