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Record W2408968138 · doi:10.1364/oe.24.012893

Single-etch subwavelength engineered fiber-chip grating couplers for 13 µm datacom wavelength band

2016· article· en· W2408968138 on OpenAlexafffund
Daniel Benedikovič, Carlos Alonso‐Ramos, Pavel Cheben, Jens H. Schmid, Shurui Wang, Robert Halir, Alejandro Ortega‐Moñux, Dan‐Xia Xu, Laurent Vivien, J. Lapointe, Siegfried Janz, Milan Dado

Bibliographic record

VenueOptics Express · 2016
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsNational Research Council Canada
FundersEuropean Research CouncilNational Research Council CanadaAgentúra na Podporu Výskumu a VývojaEuropean Commission
KeywordsMaterials scienceGratingOpticsLithographyPhotolithographyOptoelectronicsWavelengthNanoimprint lithographyChipFabricationTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

We report, for the first time, on the design and experimental demonstration of fiber-chip surface grating couplers based on subwavelength grating engineered nanostructure operating in the low fiber chromatic dispersion window (around 1.3 μm wavelengths), which is of great interest for short-reach data communication applications. Our coupler designs meet the minimum feature size requirements of large-volume deep-ultraviolet stepper lithography processes. The fiber-chip couplers are implemented in a standard 220-nm-thick silicon-on-insulator (SOI) platform and are fabricated by using a single etch process. Several types of couplers are presented, specifically the uniform, the apodized, and the focusing designs. The measured peak coupling efficiency is -2.5 dB (56%) near the central wavelength of 1.3 μm. In addition, by utilizing the technique of the backside substrate metallization underneath the grating couplers, the coupling efficiency of up to -0.5 dB (89%) is predicted by Finite Difference Time Domain (FDTD) calculations.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.632
Threshold uncertainty score1.000

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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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.

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

Citations44
Published2016
Admission routes2
Has abstractyes

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