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Record W2034453128 · doi:10.1139/v07-054

Condensation of silicon nanowires from silicon monoxide by thermal evaporation — An X-ray absorption spectroscopy investigation

2007· article· en· W2034453128 on OpenAlexvenueno aff
P -SG Kim, T. K. Sham, S. T. Lee

Bibliographic record

VenueCanadian Journal of Chemistry · 2007
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsnot available
Fundersnot available
KeywordsSilicon monoxideSiliconLuminescencePorous siliconNanowireX-ray absorption fine structureSubstrate (aquarium)Thermal oxidationPhotoluminescenceChemistryMaterials scienceAnalytical Chemistry (journal)SpectroscopyNanotechnologyOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

We report a Si K-edge X-ray absorption fine structures (XAFS) study of silicon monoxide (SiO), the starting material for silicon nanowire preparation, its silicon nanowires, and the residue after the preparation of the starting material. The silicon nanowires were condensed onto three different substrates, (i) the wall of the furnace quartz tube, (ii) a porous silicon substrate, and (iii) a Si(100) silicon wafer. It was found that the Si K-edge XAFS of SiO exhibits identifiable spectral features characteristic of Si in 0 and 4 oxidation states as well as in intermediate oxidation states, while the SiO residue primarily shows features of Si(0) and Si(4). The XAFS suggest that SiO is not exactly a simple mixture of Si and SiO 2 . The silicon nanowires produced by the process exhibit morphology and luminescence property variations that depend on the nature of the substrate. X-ray excited optical luminescence (XEOL) at the O K-edge suggests an efficient energy transfer to the optical decay channel. The results and their implications are discussed.Key words: silicon nanowires, thermal evaporation, silicon monoxide, X-ray absorption fine structures, X-ray excited optical luminescence.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.878

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)0.0010.000

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 head0.009
GPT teacher head0.223
Teacher spread0.213 · 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

Citations9
Published2007
Admission routes1
Has abstractyes

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