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Record W1998024038 · doi:10.1116/1.2902958

Operational regimes of the saddle field plasma enhanced chemical vapor deposition system

2008· article· en· W1998024038 on OpenAlexafffund
Erik Johnson, S. Źükotyński, Nazir P. Kherani

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2008
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPlasma-enhanced chemical vapor depositionSilaneThin filmMaterials scienceSubstrate (aquarium)SiliconChemical vapor depositionMicrocrystalline siliconPlasmaDeposition (geology)MicrocrystallineHydrogenAnalytical Chemistry (journal)OptoelectronicsChemical engineeringCrystalline siliconNanotechnologyChemistryComposite materialPhysicsCrystallographyAmorphous silicon

Abstract

fetched live from OpenAlex

The electrical potential at the substrate surface during the growth of hydrogenated microcrystalline silicon in a direct current saddle field (SF) plasma enhanced chemical vapor deposition (PECVD) system has been previously shown to be a limiting factor for the formation of the microcrystalline phase in the resulting thin films. The authors examine the extension of this concept to large areas under conditions necessary to obtain microcrystalline silicon in a SF-PECVD system—namely the use of hydrogen-diluted silane as a source gas, pressures between 100 and 300 mTorr, and substrate electrical bias between 100 and 250 V. The response of the SF-PECVD system to electrical substrate bias under these conditions is examined in detail, and four regimes of operation are identified, only one of which is useful for the growth of this particular material system. The delineation of these regimes provides new constraints and guidelines for the application of SF-PECVD technology to large-area deposition of thin films sensitive to ion bombardment during growth, such as microcrystalline silicon.

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 score0.007
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.193
Teacher spread0.186 · 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

Citations1
Published2008
Admission routes2
Has abstractyes

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