MétaCan
Menu
Back to cohort
Record W2154353687 · doi:10.1103/physrevb.61.r2389

Tunable two-dimensional photonic crystals using liquid crystal infiltration

2000· article· en· W2154353687 on OpenAlexaff
S. W. Leonard, Jessica P. Mondia, H. M. van Driel, Ovidiu Toader, Sajeev John, Kurt Busch, A. Birner, U. Gösele, V. Lehmann

Bibliographic record

VenuePhysical review. B, Condensed matter · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLiquid crystalMaterials sciencePhotonic crystalBirefringenceBand gapOpticsRefractive indexCondensed matter physicsWavelengthIsotropyMolecular physicsOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

The photonic band gap of a two-dimensional photonic crystal is continuously tuned using the temperature dependent refractive index of a liquid crystal. Liquid crystal $E7$ was infiltrated into the air pores of a macroporous silicon photonic crystal with a triangular lattice pitch of 1.58 $\ensuremath{\mu}$m and a band gap wavelength range of 3.3--5.7 \ensuremath{\mu}m. After infiltration, the band gap for the H polarized field shifted dramatically to 4.4--6.0 \ensuremath{\mu}m while that of the E-polarized field collapsed. As the sample was heated to the nematic-isotropic phase transition temperature of the liquid crystal $(59\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}),$ the short-wavelength band edge of the H gap shifted by as much as 70 nm while the long-wavelength edge was constant within experimental error. Band structure calculations incorporating the temperature dependence of the liquid crystal birefringence can account for our results and also point to an escaped-radial alignment of the liquid crystal in the nematic 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.015
GPT teacher head0.314
Teacher spread0.299 · 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

Citations378
Published2000
Admission routes1
Has abstractyes

Explore more

Same venuePhysical review. B, Condensed matterSame topicPhotonic Crystals and ApplicationsFrench-language works237,207