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Record W1988576217 · doi:10.1063/1.2405717

X-ray absorption studies on cubic boron nitride thin films

2007· article· en· W1988576217 on OpenAlexafffund
X. T. Zhou, Tsun‐Kong Sham, Wenjun Zhang, C. Y. Chan, I. Bello, S. T. Lee, H. Hofsäß

Bibliographic record

VenueJournal of Applied Physics · 2007
Typearticle
Languageen
FieldMaterials Science
TopicBoron and Carbon Nanomaterials Research
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Hong KongCity University of Hong KongUniversity of Wisconsin-Madison
KeywordsBoron nitrideMaterials scienceChemical vapor depositionAmorphous solidCrystallinityDiamondSubstrate (aquarium)Thin filmAnalytical Chemistry (journal)Absorption (acoustics)BoronNitrideAbsorption edgeCrystallographyLayer (electronics)NanotechnologyChemistryComposite materialOptoelectronicsBand gap

Abstract

fetched live from OpenAlex

Cubic boron nitride (c-BN) films synthesized by various energetic species assisted physical vapor deposition and chemical vapor deposition techniques on Si and diamond-coated Si substrates have been investigated by boron and nitrogen K-edge angle-resolved x-ray absorption near-edge structure in both total electron yield and fluorescence yield modes. X-ray absorption spectrum has been developed to study the film structure, the quantity and distribution of the partially ordered turbostratic (t-BN) and amorphous (a-BN) sp2-hybridized BN phases, and the t-BN∕a-BN ratios. The preferred direction of the t-BN basal planes at the interface between c-BN and substrate is found to be normal or nearly normal to the substrate. The content of the sp2-bonded BN in the c-BN films deposited on diamond-coated Si substrates reduces remarkably. The modifications of the electronic structure of the c-BN films with respect to bulk hexagonal BN and c-BN have been investigated and the crystallinity of c-BN films has also been evaluated from the x-ray absorption near edge structure results.

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 score0.006
Threshold uncertainty score0.487

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 studies0.0000.000
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 head0.034
GPT teacher head0.316
Teacher spread0.282 · 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

Citations7
Published2007
Admission routes2
Has abstractyes

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