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Record W1991307221 · doi:10.1109/jlt.2012.2228466

Characterization of Integrated Planar Photonic Crystal Circuits Fabricated by a CMOS Foundry

2012· article· en· W1991307221 on OpenAlexaff
Ellen Schelew, Georg W. Rieger, Jeff F. Young

Bibliographic record

VenueJournal of Lightwave Technology · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceGratingOpticsOptoelectronicsPhotonic integrated circuitPhotonic crystalPlanarWaveguideIntegrated circuitPhysics

Abstract

fetched live from OpenAlex

Integrated planar photonic crystal circuits in silicon on insulator were fabricated with a single-etch-step process by a foundry using complementary metal-oxide-semiconductor processing techniques. The devices studied integrate three key elements: i) input/output grating couplers consisting of 2D uniform arrays of holes, ii) single transverse electric (TE)/single transverse magnetic (TM) mode channel waveguides, and iii) a photonic crystal linear three hole defect (L3) microcavity. Experimentally measured s- and p-polarized transmission, both from grating-to-grating through a uniform silicon slab region, and through the channel waveguide/L3 cavity circuit, were quantitatively compared with finite-difference time-domain simulations. Excellent agreement is achieved assuming circular, vertical side-wall holes, but this requires accurate post-fabrication characterization of actual versus nominal device parameters, including especially the silicon device layer thickness. While s-polarized incident radiation excites TE modes that exhibit typical resonant cavity (filter-like) transmission, p-polarized incident radiation excites TM modes that non-resonantly propagate through the circuit with comparable transmission efficiency. The dependence of the grating coupler tuning range on hole diameter, and the addition of a photoresist covering is determined.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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 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

Citations15
Published2012
Admission routes1
Has abstractyes

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