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Record W2243443535 · doi:10.1149/1.3367207

(Invited) Novel Processing for Si-Nanocrystal Based Photonic Materials

2010· article· en· W2243443535 on OpenAlexaff
Matthew P. Halsall, Iain F. Crowe, Nicholas P. Hylton, O. Hulko, Andrew P. Knights, S. Ruffell, R. Gwilliam, Maciej Wojdak, Anthony J. Kenyon

Bibliographic record

VenueECS Transactions · 2010
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsMcMaster University
FundersEngineering and Physical Sciences Research Council
KeywordsNanocrystalMaterials sciencePhotoluminescenceErbiumSiliconLuminescencePhotonicsOptoelectronicsSapphireTransmission electron microscopyIon implantationRaman scatteringRaman spectroscopyNanotechnologyOpticsIonDopingChemistryLaser

Abstract

fetched live from OpenAlex

We report a study of novel processing approaches for the formation of silicon nanocrystals for photonic devices. A silicon rich oxide was formed using ion implantation into thermally grown oxides on Silicon and transparent sapphire substrates. These layers were then treated with rapid thermal processing to observe the formation of silicon nanocrystals on a one second to ten minute timescale. Transmission electron microscopy and Raman scattering were used to follow the evolution of the nanocrystal mean diameter with anneal time. Identical samples co-implanted with Erbium demonstrated the widely reported non-resonant energy transfer mechanism from the nanocrystals to the internal energy levels of the erbium. We quantified the sensitization efficiency, IEr/Inc as a function of the Si-NC size by correcting the relative visible and IR luminescence intensities for variations in the nanocrystal density and observed photoluminescence lifetime. We find that the sensitizing efficiency increases exponentially with decreasing Si-NC mean diameter.

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 categoriesInsufficient payload (model declined to judge)
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 score0.038
Threshold uncertainty score0.999

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)0.0020.000

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 head0.013
GPT teacher head0.246
Teacher spread0.233 · 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.

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

Citations0
Published2010
Admission routes1
Has abstractyes

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