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Record W2128521200 · doi:10.1139/p08-063

Determining the <i>sp</i><sup>2</sup>/<i>sp</i><sup>3</sup> bonding concentrations of carbon films using X-ray absorption spectroscopy

2008· article· en· W2128521200 on OpenAlexvenueno aff
T. Hamilton, Regan G. Wilks, M. V. Yablonskikh, Q. Yang, Mikhail Foursa, Akira Hirose, В. Н. Василец, A. Moewes

Bibliographic record

VenueCanadian Journal of Physics · 2008
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsnot available
Fundersnot available
KeywordsNanodiamondAnalytical Chemistry (journal)NitrogenX-ray photoelectron spectroscopyCarbon fibersSiliconCarbon filmChemical vapor depositionAmorphous solidAmorphous carbonAbsorption (acoustics)DopingAbsorption spectroscopyMaterials scienceDiamondNuclear chemistryNanotechnologyThin filmChemistryChemical engineeringCrystallographyComposite numberOrganic chemistryPhysicsComposite material

Abstract

fetched live from OpenAlex

The sp 2 bonding concentrations of nitrogen-doped amorphous carbon samples and nanodiamond films were determined from their soft X-ray absorption spectra. The amorphous carbon (a-C) samples were deposited under atmospheres of varying nitrogen concentrations onto polytetrafluoroethylene (PTFE) polymer and silicon substrates. The nanodiamond films were synthesized on silicon substrates in a CH 4 /H 2 gas mixture by microwave plasma chemical vapour deposition. The sp 2 bonding concentrations in the a-C films (deposited on PTFE substrates) increase from 74% to 93% as nitrogen doping increases, with a step-like increase in sp 2 fraction when nitrogen concentrations in the films exceed 27%. The a-C films on silicon substrates display the same trend of increasing sp 2 concentration as a function of greater nitrogen concentration. Nanodiamond deposition conditions, such as bias voltage and methane concentration, affect the purity of the film. Our analysis reveals sp 2 bonding concentrations in these samples ranging from a few percent to 11%.PACS Nos.: 78.70.Dm, 61.10.Ht, 61.46.+w, 81.05.Uw

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)0.001
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 score0.024
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.029
GPT teacher head0.260
Teacher spread0.231 · 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
Published2008
Admission routes1
Has abstractyes

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