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Record W2116143228 · doi:10.1364/ol.31.003495

Femtosecond laser direct writing of multiwavelength Bragg grating waveguides in glass

2006· article· en· W2116143228 on OpenAlexaff
Haibin Zhang, Shane M. Eaton, Jianzhao Li, Peter R. Herman

Bibliographic record

VenueOptics Letters · 2006
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOpticsFiber Bragg gratingMaterials scienceLaserFemtosecondGratingWaveguideLaser linewidthWavelengthPHOSFOSOptoelectronicsBorosilicate glassPhysicsOptical fiber

Abstract

fetched live from OpenAlex

Novel Bragg grating waveguide structures have been fabricated in bulk borosilicate glass through a type II photosensitivity mechanism driven by single femtosecond laser pulses. Low-loss single-mode waveguides and narrow-linewidth Bragg gratings were generated simultaneously by forming an array of refractive index voxels in a single laser scan. Laser pulse duration is shown to significantly affect the grating strength and waveguide loss. Bragg wavelengths, defined by the periodicity of laser-modified volumes, were fully controlled by the sample scan speed to provide resonances anywhere in the 1200-1620 nm telecommunication bands. Four linear Bragg filters with distinct resonant wavelengths are presented that define the first demonstration of laser writing of multiple-wavelength and cascaded Bragg grating waveguides in a single process step.

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 score0.002

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)0.0010.000

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 head0.005
GPT teacher head0.196
Teacher spread0.190 · 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

Citations58
Published2006
Admission routes1
Has abstractyes

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