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Record W4379522501 · doi:10.21203/rs.3.rs-3011018/v1

Pulsed-aerosol assisted low-pressure plasma for thin film deposition

2023· preprint· en· W4379522501 on OpenAlexafffund
Guillaume Carnide, Claire Simonnet, Thibault Sadek, Divyesh Parmar, Zaccharoula Zavvou, Adèle Girardeau, Vincent Pozsgay, Thomas Verdier, Christina Villeneuve-Faure, Myrtil L. Kahn, Luc Stafford, Richard Clergereaux

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsUniversité de Montréal
FundersUniversité de MontréalCentre National de la Recherche ScientifiqueUniversité de Toulouse
KeywordsThin filmDeposition (geology)PlasmaAerosolCarbon filmMaterials scienceChemical vapor depositionInertAtmospheric-pressure plasmaChemistryAnalytical Chemistry (journal)Chemical engineeringNanotechnologyChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Plasma-enhanced chemical vapor deposition (PE-CVD) is intensively studied and developed to form (multi-)functional thin films. Generally produced in gases or vapors of thermodynamically stable and chemically inert precursors, aerosol assisted plasma process becomes an alternative as it enables to inject various liquid solutions independently of these characteristics. This study examines the case of pentane aerosols injected in pulsed mode in a low-pressure RF plasma. It produces diamond-like carbon thin films with material balance larger than those obtained in gaseous processes. Here, the deposition process is controlled by the pulsed injection. Indeed, the dynamics of thin film deposition result in time-dependent mechanisms at the pulse scale related to the temporary increase of the working pressure and the presence of liquid droplets in the plasma volume. Hence, thin film deposition is controlled by plasma-surface as well as plasma-droplets interactions. Consequently, aerosol-assisted plasma processes are really relevant for the deposition of (multi-)functional coatings.

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 score0.003
Threshold uncertainty score0.010

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.083
GPT teacher head0.387
Teacher spread0.304 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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