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Record W3159765013 · doi:10.1002/lpor.202000542

Breaking the Coupling Efficiency–Bandwidth Trade‐Off in Surface Grating Couplers Using Zero‐Order Radiation

2021· article· en· W3159765013 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLaser & Photonics Review · 2021
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsNational Research Council Canada
FundersNational Research Council CanadaMinisterio de Ciencia, Innovación y UniversidadesUniversidad de Málaga
KeywordsMaterials scienceOpticsGratingPhotonicsOptoelectronicsBandwidth (computing)Silicon photonicsDiffraction gratingBroadbandWaferSiliconDiffractionPhysicsTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

Abstract Silicon photonics provides wafer‐scale fabrication of densely integrated photonic circuits that are enabling breakthrough applications in datacom, artificial intelligence, and healthcare. The sub‐micrometer mode size of silicon waveguides makes efficient coupling to conventional single mode fibers extremely challenging. While advanced surface grating couplers can achieve sub‐decibel coupling efficiencies, their operation relies on diffraction phenomena, which intrinsically limit the operational bandwidth. Here a novel type of surface coupler is experimentally demonstrated that overcomes the efficiency‐bandwidth limitation of conventional diffraction gratings by harnessing zero‐order radiation from a subwavelength metamaterial waveguide to a tilted silicon prism. The device achieves a coupling efficiency above 80% to an SMF‐28 fiber in a record 1‐dB bandwidth beyond 90 nm, opening new venues for highly efficient broadband fiber‐to‐chip surface coupling in silicon 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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.260
Teacher spread0.243 · 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