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Record W1994575712 · doi:10.1088/0022-3727/39/7/012

3D numerical simulation of gas heating effects in a magnetron sputter deposition system

2006· article· en· W1994575712 on OpenAlexaff
Samuel D. Ekpe, S. K. Dew

Bibliographic record

VenueJournal of Physics D Applied Physics · 2006
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSputter depositionDeposition (geology)Cavity magnetronMaterials scienceNuclear engineeringSputteringEngineering physicsMetallurgyEngineeringNanotechnologyThin filmGeology

Abstract

fetched live from OpenAlex

3D numerical simulation of gas heating in a magnetron sputtering system is performed. Pressure, magnetron power density and location of the substrate plane in front of the target are shown to affect the gas temperature profile. For the pressure range under study, maximum gas temperature is shown to increase with pressure. By increasing the separation between the target and the substrate, the maximum gas temperature is shown to increase up to the point when most of the particles are assumed thermalized. Cu shows more gas heating than does Al due to its higher sputtering yield and energy transfer efficiency. Sputtered particles are shown to be the major source of gas heating.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.638

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 head0.005
GPT teacher head0.188
Teacher spread0.183 · 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 designSimulation or modeling
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

Citations25
Published2006
Admission routes1
Has abstractyes

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