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Record W2218236855 · doi:10.1364/ao.54.005897

Electro-optical phase-change 2 × 2 switching using three- and four-waveguide directional couplers

2015· article· en· W2218236855 on OpenAlexafffund
Haibo Liang, Richard Soref, Jianwei Mu, Xun Li, Wei‐Ping Huang

Bibliographic record

VenueApplied Optics · 2015
Typearticle
Languageen
FieldMaterials Science
TopicPhase-change materials and chalcogenides
Canadian institutionsMcMaster University
FundersAir Force Office of Scientific ResearchEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsPower dividers and directional couplersWaveguideMaterials scienceOpticsOptical switchSilicon on insulatorOptoelectronicsCoupling (piping)Phase (matter)Crossbar switchSiliconPhysicsTelecommunications

Abstract

fetched live from OpenAlex

Theoretical modeling and numerical simulation have been performed at λ=2100 nm on silicon-on-insulator channel-waveguide directional couplers in which the outer two Si waveguides are passive and the central waveguide(s) are electro-optical (EO) "islands." The EO channel(s) utilize a 10 nm layer of Ge2Sb2Te5 phase-change-material sited at midlevel of a doped Si channel. A voltage-driven phase change produces a large change in the effective index of the TE(o) and TM(o) modes, thereby inducing crossbar 2×2 switching. A mode-matching method is employed to estimate EO switching performance in the limit of strong interguide coupling. Low-loss switching is predicted for cross-to-bar and bar-to-cross coupling lengths. These "self-holding" switches had active lengths of 500-1000 μm, which are shorter than those in couplers relying upon free-carrier injection. The four-waveguide devices had lower cross talk but higher loss than the three-waveguide devices. For the crystalline phase we sometimes used an active length that was smaller than that for the amorphous phase.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

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)0.0020.000

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 head0.180
GPT teacher head0.316
Teacher spread0.135 · 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

Citations42
Published2015
Admission routes2
Has abstractyes

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