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Record W2160030980 · doi:10.1364/oe.16.020206

Surface plasmon resonance-like integrated sensor at terahertz frequencies for gaseous analytes

2008· article· en· W2160030980 on OpenAlexaff
Alireza Hassani, Maksim Skorobogatiy

Bibliographic record

VenueOptics Express · 2008
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceTerahertz radiationAnalyteSurface plasmon polaritonSurface plasmon resonanceOpticsSurface plasmonRefractive indexPlasmonPhotonic-crystal fiberOptical fiberOptoelectronicsLocalized surface plasmonFiber optic sensorDispersion (optics)FiberNanotechnologyWavelengthChemistryNanoparticle

Abstract

fetched live from OpenAlex

Plasmon-like excitation at the interface between fully polymeric fiber sensor and gaseous analyte is demonstrated theoretically in terahertz regime. Such plasmonic excitation occurs on top of a approximately 30 microm ferroelectric PVDF layer wrapped around a subwavelength porous polymer fiber. In a view of designing a fiber-based sensor of analyte refractive index, phase matching of a plasmon-like mode with the fundamental core guided mode of a low loss porous fiber is then demonstrated for the challenging case of a gaseous analyte. We then demonstrate the possibility of designing high sensitivity sensors with amplitude resolution of 3.4 x 10(-4) RIU, and spectral resolution of 1.3 x 10(-4) RIU in THz regime. Finally, novel sensing methodology based on detection of changes in the core mode dispersion is proposed.

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.030
GPT teacher head0.242
Teacher spread0.213 · 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
Published2008
Admission routes1
Has abstractyes

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