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Record W4252044848 · doi:10.1109/qels.1999.807654

Dependence of transmission on number of rows of 2D macroporous silicon photonic band gap material

2003· article· en· W4252044848 on OpenAlexaff
S.W. Leonard, K. Busch, S. John, H.M. van Driel, A. Birner, U. Gosele

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhotonic crystalPhotonicsMaterials scienceAttenuationBand gapOptoelectronicsSiliconTransmission (telecommunications)WavelengthOpticsTelecommunicationsPhysicsComputer science

Abstract

fetched live from OpenAlex

Summary form only given. Although it is well known that photonic band gap (PBG) materials can provide a high degree of attenuation within the photonic band gap, relatively little work has been done on visible or near-infrared gap materials to investigate exactly how this attenuation depends on the material thickness. This is an important issue because it is the attenuating property of photonic band gap materials that makes them so attractive as photonic circuit elements. We report on the band-gap transmission properties of 2D silicon PBG materials as a function of material thickness and wavelength with transmissivity as low as 3/spl times/10/sup -4/ being observed for only 4 unit cell thickness. The results indicate that large attenuation can be achieved with a very small volume of PBG material. This will be of central importance in the design of the coming generation of PBG devices such as waveguides and filters.

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.001

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 head0.011
GPT teacher head0.265
Teacher spread0.254 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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