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Record W4392906832 · doi:10.1088/1402-4896/ad350d

Hybrid Si-Au plasmonic sensor on the end-facet of a dual-core optical fiber enhanced by hotspots: a theoretical study

2024· article· en· W4392906832 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysica Scripta · 2024
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMaterials scienceDecoupling (probability)Surface plasmon polaritonPlasmonGratingCore (optical fiber)OptoelectronicsOptical fiberOpticsFacet (psychology)WaveguideSurface plasmonSingle-mode optical fiberPhysics

Abstract

fetched live from OpenAlex

Abstract We propose an efficient hybrid Si-Au sensor on the end-facet of a dual-core single-mode optical fiber. The design incorporates slanted Si grating couplers on the two cores, interconnected by a plasmonic waveguide bearing subwavelength corrugations. The corrugations enhance the surface sensitivity by creating regions of strongly enhanced fields - plasmonic hotspots. Unlike conventional Si waveguide grating couplers, we employ slanted slits for unidirectional coupling/decoupling between TM-polarized core light and surface plasmon polaritons. Our structure results in about 3% core-to-core (TM-to-TM) coupling efficiency, while also providing high bulk and surface sensitivities of about 1000 nm RIU −1 and 1.66 nm nm −1 , respectively. The sensor can be interrogated remotely in a transmission arrangement. The sensing medium can be probed by dipping the fiber tip directly therein. Potential applications include remote sensing, brain studies, or in-vivo biosensing.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.770

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)0.0000.001

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 head0.012
GPT teacher head0.235
Teacher spread0.224 · 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