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Record W2996135449 · doi:10.1364/oe.27.038259

Through-the-coating writing of tilted fiber Bragg gratings with the phase mask technique

2019· article· en· W2996135449 on OpenAlexaff
Nurmemet Abdukerim, Dan Grobnic, Cyril Hnatovsky, Stephen J. Mihailov

Bibliographic record

VenueOptics Express · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceOpticsFiber Bragg gratingPHOSFOSLong-period fiber gratingCoatingPolyimideCladding (metalworking)Photonic-crystal fiberFemtosecondRefractive indexLaserPlastic optical fiberFiberOptoelectronicsFiber optic sensorWavelengthComposite materialLayer (electronics)Physics

Abstract

fetched live from OpenAlex

Tilted fiber Bragg gratings are inscribed in non-photosensitized single mode fibers through the polyimide coating using a femtosecond infrared laser and a phase mask. The inscription technique used is based on simultaneously translating the fiber along its axis and the focusing cylindrical lens in the orthogonal direction by means of piezoelectric actuators. The grating plane tilt angles up to 10.3° are achieved with a 1.07 µm-pitch phase mask. The cladding modes reach ∼5 dB in strength in transmission despite the presence of the polyimide coating. The effectiveness of the fabricated tilted fiber Bragg gratings for refractive index sensing through the polyimide coating is also demonstrated. Additionally, we show that the classical approach for the inscription of tilted Bragg gratings, which is based on simply tilting the fiber with respect to the interference fringes, cannot be used in tight focusing geometries that are necessary for through-the-coating inscription.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.112
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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 teacher head, 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

Citations12
Published2019
Admission routes1
Has abstractyes

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