MétaCan
Menu
Back to cohort
Record W1976483869 · doi:10.1109/inec.2013.6465984

Stoichiometric amorphous hydrogenated silicon carbide thin film synthesis using DC-saddle plasma enhanced chemical vapour deposition

2013· article· en· W1976483869 on OpenAlexaff
Behzad Karimi, Ali B. Alamin Dow, Nazir P. Kherani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials sciencePlasma-enhanced chemical vapor depositionChemical vapor depositionStoichiometrySilicon carbidePassivationAmorphous siliconAmorphous solidThin filmCarbon filmChemical engineeringSiliconAmorphous carbonSurface roughnessAnalytical Chemistry (journal)OptoelectronicsNanotechnologyCrystalline siliconComposite materialLayer (electronics)Chemistry

Abstract

fetched live from OpenAlex

Silicon carbide is a versatile material amenable to a variety of applications ranging from electrical insulation, surface passivation and diffusion barrier to optical devices. The DC saddle-field plasma enhanced chemical vapour technique is an alternative large area deposition technique. Here we report on the synthesis of stoichiometric hydrogenated amorphous silicon using the dc saddle-field PECVD technique. We also report on the attainment of very smooth surface morphology for the stoichiometric a-SiC:H films in contrast to low carbon content films. Surface roughness of 1 nm rms was demonstrated for films grown at a temperature as low as 225°C.

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 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 score0.256
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
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.191
Teacher spread0.180 · 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.

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

Citations4
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicThin-Film Transistor TechnologiesFrench-language works237,207