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Record W4205723077 · doi:10.1364/oe.446758

SiN half-etch horizontal slot waveguides for integrated photonics: numerical modeling, fabrication, and characterization of passive components

2022· article· en· W4205723077 on OpenAlexaff
Eva Kempf, Pédro Rojo Romeo, Alban Gassenq, Arnaud Taute, Paul Chantraine, Jimmy John, Ali Belarouci, S. Monfray, F. Bœuf, Paul G. Charette, Régis Orobtchouk

Bibliographic record

VenueOptics Express · 2022
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
Fundersnot available
KeywordsFabricationMaterials scienceResonatorOpticsWaveguidePhotonicsOptoelectronicsWavelengthLayer (electronics)Photonic crystalCharacterization (materials science)Coupled mode theoryRefractive indexPhysicsNanotechnology

Abstract

fetched live from OpenAlex

This work presents a "half-etch" horizontal slot waveguide design based on SiN, where only the upper SiN layer is etched to form a strip that confines the mode laterally. The numerical modeling, fabrication, and characterization of passive waveguiding components are described. This novel slot waveguide structure was designed with on-chip light amplification in mind, for example with an Er-doped oxide spacer layer. Proof-of-concept racetrack resonators were fabricated and characterized, showing quality factors up to 50,000 at critical coupling and residual losses of 4 dB/cm at wavelengths away from the N-H bond absorption peak in SiN, demonstrating the high potential of these horizontal slot waveguides for use in active integrated photonics.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.015
GPT teacher head0.223
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2022
Admission routes1
Has abstractyes

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