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Diamond Growth on a Si Substrate With Ceramic Interlayers

2007· article· en· W2034726531 on OpenAlexaff
Y. S. Li, C. Xiao, Akira Hirose, Q. Yang, Shiro Shimada

Bibliographic record

VenueJournal of the American Ceramic Society · 2007
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDiamondNucleationMaterials scienceChemical vapor depositionPlasma-enhanced chemical vapor depositionCeramicMicrocrystallineWaferChemical engineeringAmorphous solidSubstrate (aquarium)Carbon filmMineralogyComposite materialNanotechnologyThin filmCrystallographyChemistry

Abstract

fetched live from OpenAlex

Deposition of diamond films on Si substrates precoated with a series of ceramic intermediate layers was examined. The interlayers containing SiC, SiN x , SiCN, TiSiN, and TiAlSiN were prepared by a liquid injection plasma‐enhanced chemical vapor deposition (PECVD) method using alkoxide solution precursors. The subsequent diamond synthesis on these coatings was carried out by microwave plasma‐assisted CVD (MPCVD) using a H 2 –1%CH 4 mixture. A higher nucleation density of diamond was obtained on these intermediate layers than on the as‐polished Si wafer, along with a nonuniform surface distribution of diamond. Diamond powder scratching pretreatment of these interlayers enhanced the nucleation density and promoted the formation of fully uniform diamond films. Particularly, nanocrystalline diamond films were directly generated on TiSiN and TiAlSiN layers under an identical deposition condition that had favored the formation of microcrystalline diamond films on Si wafers and the Si(C,N) interlayers. The mechanism for this difference is attributed primarily to a higher amount of residual amorphous carbon in TiSiN and TiAlSiN layers than that inside Si(C,N) layers.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.262
Teacher spread0.252 · 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 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

Citations6
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Ceramic SocietySame topicDiamond and Carbon-based Materials ResearchFrench-language works237,207