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Coherent Visible-Light-Generation Enhancement in Silicon-Based Nanoplasmonic Waveguides via Third-Harmonic Conversion

2015· article· en· W2420213243 on OpenAlexafffund
Shawn Sederberg, A. Y. Elezzabi

Bibliographic record

VenuePhysical Review Letters · 2015
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Health Solutions
KeywordsOptoelectronicsMaterials scienceWaveguideSiliconOpticsEnergy conversion efficiencyPhotonicsNonlinear opticsSecond-harmonic generationSilicon photonicsFemtosecondPlasmonPhysicsLaser

Abstract

fetched live from OpenAlex

We report visible third-harmonic conversion at λ=517 nm in subwavelength silicon-based nanoplasmonic waveguides at an unprecedented conversion efficiency of 2.3×10^{-5}. This marks both the highest third-harmonic conversion efficiency in a silicon-based or nanoplasmonic structure and the smallest silicon waveguide structure demonstrated to date. The high conversion efficiency is attributed to tight electric field confinement and strong light-matter coupling arising from surface plasmon modes in the nanoplasmonic waveguide, enabling efficient nonlinear optical mixing over micrometer length scales. The nonresonant geometry of the waveguide enables the entire λ=1550 nm femtosecond pulse spectrum to be converted to its third harmonic, which may be easily extended to the entire visible spectrum. We envisage that third-harmonic generation in silicon-based nanoplasmonic waveguides could provide a platform for integrated, broadband visible light sources and entangled triplet photons on future hybrid electronic-silicon photonic chips.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.673
Threshold uncertainty score0.790

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)0.0000.000

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 head0.024
GPT teacher head0.260
Teacher spread0.237 · 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

Citations40
Published2015
Admission routes2
Has abstractyes

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