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Record W4412412687 · doi:10.1002/lpor.202402114

Polarization‐Independent Complex Bragg Grating Filters on Silicon Nitride

2025· article· en· W4412412687 on OpenAlexafffund
Alejandro Fernández‐Hinestrosa, José Manuel Luque‐González, Pavel Cheben, Jens H. Schmid, Alejandro Sánchez‐Postigo, J. Gonzalo Wangüemert‐Pérez, Íñigo Molina‐Fernández, Alejandro Ortega‐Moñux

Bibliographic record

VenueLaser & Photonics Review · 2025
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsNational Research Council Canada
FundersNational Research Council CanadaMinisterio de Economía y CompetitividadMinisterio de Ciencia, Innovación y UniversidadesUniversidad de Málaga
KeywordsMaterials scienceFiber Bragg gratingPolarization (electrochemistry)Silicon nitrideGratingOpticsOptoelectronicsNitrideSiliconNanotechnologyPhysicsChemistryWavelength

Abstract

fetched live from OpenAlex

Abstract Integrated optical filters are essential components of on‐chip multiplexers, which play a critical role in enhancing data throughput for high‐demand networks. Since optical multiplexers are typically connected through fiber‐optic links where the polarization state of light fluctuates randomly, polarization insensitivity is an important prerequisite for integrated optical filters. In this work, polarization‐insensitive optical filters are demonstrated on the silicon nitride platform operating in the datacom O‐band. The filters are based on cladding‐modulated Bragg gratings, which offer improved fabrication tolerances and reduced losses compared to conventional sidewall gratings. By judiciously designing grating dimensions, filters are demonstrated with single‐band, dual‐band, and four‐band spectral characteristics. The fabricated filters achieve an insertion loss below 1.0 dB and a band rejection greater than 25 dB for spectral bands that are 3 nm wide and 9 nm apart.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.667
Threshold uncertainty score0.925

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 head0.016
GPT teacher head0.263
Teacher spread0.247 · 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 designNot applicable
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

Citations4
Published2025
Admission routes2
Has abstractyes

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