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Record W1943156760 · doi:10.1002/lpor.201200106

An ultra‐compact multimode interference coupler with a subwavelength grating slot

2013· article· en· W1943156760 on OpenAlexaff
Alejandro Ortega‐Moñux, Carlos Alonso‐Ramos, Alejandro Maese‐Novo, Robert Halir, L. Zavargo-Peche, Diego Pérez‐Galacho, Íñigo Molina‐Fernández, J. Gonzalo Wangüemert‐Pérez, Pavel Cheben, Jens H. Schmid, J. Lapointe, Dan‐Xia Xu, Siegfried Janz

Bibliographic record

VenueLaser & Photonics Review · 2013
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsCladding (metalworking)Materials scienceSilicon on insulatorGratingExtinction ratioFabricationOptoelectronicsPower dividers and directional couplersPhotonicsOpticsElectronic circuitSiliconPhysicsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Multimode interference couplers (MMIs) are fundamental building blocks in photonic integrated circuits. Here it is experimentally demonstrated, for the first time, a two‐fold length reduction in an MMI coupler without any penalty on device performance. The design is based on a slotted 2 × 2 MMI fabricated on a commercial silicon‐on‐insulator (SOI) substrate. The slot is implemented with a subwavelength grating (SWG) comprising holes fully etched down to the oxide cladding, thereby allowing single etch step fabrication. The device has been designed using an in‐house tool based on the Fourier Eigenmode Expansion Method. It has a footprint of only 3.5 μm x 23 μm and it exhibits a measured extinction ratio better than 15 dB within the full C‐band (1530 nm‒1570 nm). SWG engineered slots thus offer excellent perspectives for the practical realization of MMIs couplers with substantially reduced footprint yet with outstanding performance.

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: Empirical
Teacher disagreement score0.000
Threshold uncertainty score0.002

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)0.0000.000

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 head0.014
GPT teacher head0.247
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 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

Citations39
Published2013
Admission routes1
Has abstractyes

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