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Record W2043370503 · doi:10.1116/1.4900541

Distribution of ion current density on a rotating spherical cap substrate during ion-assisted deposition

2014· article· en· W2043370503 on OpenAlexaff
В. І. Марушка, O. Zabeida, L. Martinů

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2014
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsIonIon currentIon beamCurrent densityIon beam depositionIon gunIon sourceAnodeSubstrate (aquarium)Deposition (geology)Materials scienceAtomic physicsIon beam mixingCurrent (fluid)ChemistryAnalytical Chemistry (journal)PhysicsElectrodeThermodynamics

Abstract

fetched live from OpenAlex

The uniformity of ion density is critical for applications relying on the ion assisted deposition technique for the fabrication of the high quality thin films. The authors propose and describe here a method allowing one to calculate the ion density distribution on spherical substrate holders under stationary and rotating conditions for different positions of the ion source. The ion beam shape was approximated by a cosn function, and the ion current density was represented by a function inversely proportional to the distance from the ion source in accordance with our experimental results. As an example, a calculation of the current density distribution on the spherical cap substrate was performed for a broad beam ion source operated with an anode current of 3 A. The authors propose an approach for process optimization with respect to the ion source position and its inclination, in terms of uniformity and absolute value of the ion current density.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.222
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 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

Citations3
Published2014
Admission routes1
Has abstractyes

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