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Record W2197618443 · doi:10.1002/ppap.201500182

Hydrogenated Silicon Nitride SiN<i><sub>x</sub></i>:H Deposited by Dielectric Barrier Discharge for Photovoltaics

2015· article· en· W2197618443 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePlasma Processes and Polymers · 2015
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversité Laval
FundersAgence de l'Environnement et de la Maîtrise de l'EnergieAir Liquide
KeywordsPlasma-enhanced chemical vapor depositionMaterials scienceSilicon nitridePassivationPhotovoltaicsChemical vapor depositionOptoelectronicsDielectric barrier dischargeThin filmSiliconPlasmaNitrideNanotechnologyDielectricLayer (electronics)Photovoltaic systemElectrical engineering

Abstract

fetched live from OpenAlex

Dense hydrogenated silicon nitride (SiN x :H) layers for photovoltaics are made by Atmospheric Pressure Plasma Enhanced Chemical Vapor Deposition (AP‐PECVD). The dependence of morphology, chemical, optical and passivation properties of the thin films on the plasma reactor configuration, the mode of homogeneous DBD (glow, Townsend, RF, nano pulsed) and the SiH 4 /NH 3 gas flow ratio are investigated. Avoiding gas recirculation, improving thin film homogeneity through the electrode length and the plasma modulation appear as key points. Silicon solar cells made with AP‐PECVD SiN antireflective coating have the same efficiency as standard low pressure PECVD cells, showing the great potential of AP‐PECVD.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.017
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.009
GPT teacher head0.192
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