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Record W3039955801 · doi:10.1063/5.0011755

Optical detection of the percolation threshold of nanoscale silver coatings with optical fiber gratings

2020· article· en· W3039955801 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

VenueAPL Photonics · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsCarleton University
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceCladding (metalworking)Long-period fiber gratingOptical fiberFiber Bragg gratingOpticsAll-silica fiberCoatingCladding modePercolation thresholdWavelengthFiber optic sensorFiberDispersion-shifted fiberOptoelectronicsPolarization-maintaining optical fiberComposite materialElectrical resistivity and conductivity

Abstract

fetched live from OpenAlex

The metal-to-dielectric transition of silver films deposited on single-mode optical fibers is monitored by measurements of the transmission spectra of tilted fiber Bragg gratings inscribed in the core of the fiber. In situ, real-time measurements of the spectrum at wavelengths near 1550 nm during the wet etching of a 50 nm thick silver coating show a sudden and temporary decrease of more than 90% in the amplitudes of the core-to-cladding mode coupling resonances when the film thickness reaches 18 nm. Confirmation that this observation corresponds to the percolation threshold is obtained from simultaneous measurements of the silver coating conductivity during etching and by simulations of the grating response. The characteristic spectral signature of the percolation threshold is only obtained for cladding modes polarized azimuthally in the fiber cross section, i.e., parallel to the film surface.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.416

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 head0.194
Teacher spread0.185 · 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