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Record W2114557271 · doi:10.1109/cjece.2010.5783383

A photonic crystal technology compatible with integrated circuit technologies

2010· article· en· W2114557271 on OpenAlexafffundvenue
Khadijeh Bayat, Mahdi Farrokh Baroughi, Sujeet K. Chaudhuri, Safieddin Safavi‐Naeini

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsMaterials scienceElectron-beam lithographyAnalytical Chemistry (journal)OptoelectronicsNanotechnologyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Amorphous silicon oxy-nitride (a-SixOyN1-x-y) films with refractive indices in a wide range of 1.43-1.75 were obtained by plasma-enhanced chemical vapour deposition of silane, nitrous oxide, and ammonia gases at 30°C. Photonic crystal slabs based on a-SixOyN1-x-ymaterial systems were simulated and fabricated. Low-contrast photonic crystal structures for which the refractive index difference between the cladding and the core is small are implemented using this technology. It is shown that even low-contrast photonic crystals can provide fairly wide bandgap. The films were patterned by electron-beam lithography and etched by reactive ion etching. The device fabrication is carried out at low temperature and is independent of the substrate type. Therefore, this technology can be used to integrate photonic crystal-based optical integrated circuits within silicon- and GaAs-based integrated circuits.

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)0.001
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.007

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 head0.003
GPT teacher head0.164
Teacher spread0.161 · 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

Citations2
Published2010
Admission routes3
Has abstractyes

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