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Record W2090572776 · doi:10.1364/oe.22.002790

Strong guided mode resonant local field enhanced visible harmonic generation in an azo-polymer resonant waveguide grating

2014· article· en· W2090572776 on OpenAlexaff
Jian Lin, Chun-Yen Tseng, Ching-Ting Lee, Jeff F. Young, Hung‐Chih Kan, Chia‐Chen Hsu

Bibliographic record

VenueOptics Express · 2014
Typearticle
Languageen
FieldMaterials Science
TopicOptical Coatings and Gratings
Canadian institutionsUniversity of British Columbia
FundersNational Science Council
KeywordsMaterials scienceGratingSecond-harmonic generationOpticsOptoelectronicsPlanarWavelengthWaveguidePolymerGuided-mode resonanceLayer (electronics)Nonlinear opticsExcited stateDiffraction gratingLaserNanotechnologyPhysics

Abstract

fetched live from OpenAlex

Guided mode resonance (GMR) enhanced second- and third-harmonic generation (SHG and THG) is demonstrated in an azo-polymer resonant waveguide grating (RWG), comprised of a poled azo-polymer layer on top of a textured SU8 substrate with a thin intervening layer of TiO2. Strong SHG and THG outputs are observed by matching either in-coming fundamental- or out-going harmonic-wavelength to the GMR wavelengths of the azo-polymer RWG. Without the azo-polymer coating, pure TiO2 RWGs, do not generate any detectable SHG using a fundamental beam peak intensity of 2 MW/cm(2). Without the textured TiO2 layer, a planar poled azo-polymer layer results in 3650 times less SHG than the full nonlinear RWG structure under identical excitation conditions. Rigorous coupled-wave analysis calculations confirm that this enhancement of the nonlinear conversion is due to strong local electric fields that are generated at the interfaces of the TiO2 and azo-polymer layers when the RWG is excited at resonant wavelengths associated with both SHG and THG conversion processes.

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 score0.382
Threshold uncertainty score0.941

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 studies0.0000.000
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 head0.030
GPT teacher head0.297
Teacher spread0.267 · 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

Citations18
Published2014
Admission routes1
Has abstractyes

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