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Record W2120784273 · doi:10.5539/jmsr.v3n1p43

Effect of Nitrogen on the Growth of Boron Doped Single Crystal Diamond

2013· article· en· W2120784273 on OpenAlexvenueno aff
Sunil Karna, Yogesh K. Vohra

Bibliographic record

VenueJournal of Materials Science Research · 2013
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsnot available
FundersNational Nuclear Security AdministrationU.S. Department of Energy
KeywordsMaterials scienceRaman spectroscopyDiboraneBoronDiamondChemical vapor depositionDopingAnalytical Chemistry (journal)Material properties of diamondNitrogenCrystal (programming language)NanotechnologyComposite materialOptoelectronicsOptics

Abstract

fetched live from OpenAlex

Boron-doped single crystal diamond films were grown homoepitaxially on synthetic (100) Type Ib diamond substrates using microwave plasma assisted chemical vapor deposition. A modification in surface morphology of the film with increasing boron concentration in the plasma has been observed using atomic force microscopy. Use of nitrogen during boron doping has been found to improve the surface morphology and the growth rate of films but it lowers the electrical conductivity of the film. The Raman spectra indicated a zone center optical phonon mode along with a few additional bands at the lower wavenumber regions. The change in the peak profile of the zone center optical phonon mode and its downshift were observed with the increasing boron content in the film. However, sharpening and upshift of Raman line was observed in the film that was grown in presence of nitrogen along with diborane in process gas.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.035
GPT teacher head0.337
Teacher spread0.302 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2013
Admission routes1
Has abstractyes

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