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Record W2115756331 · doi:10.1139/cjp-2013-0558

Control of growth process for obtaining high-quality a-SiO:H

2014· article· en· W2115756331 on OpenAlexvenueno aff
Yasushi Sobajima, Shota Kinoshita, Shinnosuke Kakimoto, Ryoji Okumoto, Chitose Sada, Akihisa Matsuda, Hiroaki Okamoto

Bibliographic record

VenueCanadian Journal of Physics · 2014
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsDangling bondPlasmaDissociation (chemistry)OxygenMoleculeAnalytical Chemistry (journal)Growth rateAmorphous siliconSiliconPhysicsPhysical chemistryChemistryOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

Film-growth process of hydrogenated amorphous silicon–oxygen alloys (a-SiO:H) from CO 2 /(CO 2 + SiH 4 ) plasma has been investigated to control the optoelectronic properties in the resulting materials. Optical emission spectroscopy results and simple simulation results for steady-state density of chemical species in the plasma indicate that main film-growth precursors for a-SiO:H are SiH 3 , OH, and O. Si dangling-bond defect density is drastically increased in a-SiO:H when increasing the CO 2 gas ratio in CO 2 /(CO 2 + SiH 4 ) plasma, being caused by the increase in the contribution ratio of Si-related short-lifetime species (SiH x , x < 2) to film growth owing to a severe SiH 4 -molecule depletion because of high-rate consumption reaction of SiH 4 with O produced from CO 2 in the plasma. Considering the primary electron impact dissociation reactions of source gas molecules and several secondary chemical reactions in the plasma, the guiding principle for obtaining high quality a-SiO:H has been proposed.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.426

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.224
Teacher spread0.208 · 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 designTheoretical or conceptual
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

Citations2
Published2014
Admission routes1
Has abstractyes

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