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Record W2092276082 · doi:10.1002/ppap.201200029

Atmospheric Pressure Low Temperature Direct Plasma Technology: Status and Challenges for Thin Film Deposition

2012· article· en· W2092276082 on OpenAlexaff
F. Massines, Christian Sarra‐Bournet, Fiorenza Fanelli, Nicolas Naudé, Nicolas Ghérardi

Bibliographic record

VenuePlasma Processes and Polymers · 2012
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPlasma-enhanced chemical vapor depositionThin filmAtmospheric-pressure plasmaAtmospheric pressureDeposition (geology)Materials sciencePlasmaChemical vapor depositionNanotechnologyOptoelectronicsEngineering physicsEngineeringMeteorologyPhysicsGeology

Abstract

fetched live from OpenAlex

Abstract Over the last ten years, expansion of atmospheric pressure plasma solutions for surface treatment of materials has been remarkable, however direct plasma technology for thin film deposition needs still great effort. The objective of this paper is to establish the state of the art on scientific and technologic locks, which have to be opened to consider direct atmospheric pressure plasma‐enhanced chemical vapor deposition (AP‐PECVD) a viable option for industrial application. Basic scientific principles to understand and optimize an AP‐PECVD process are summarized. Laboratory reactor configurations are reviewed. Reference points for the design and use of AP‐PECVD reactors according to the desired thin film properties are given. Finally, solutions to avoid powder formation and to increase the thin film growth rate are discussed. magnified image

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations356
Published2012
Admission routes1
Has abstractyes

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