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Record W3021458884 · doi:10.1002/andp.202000157

Saturable Absorption and Bistable Switching of Single Mode Fiber Core‐Guided Light by a 6 nm‐thick, Few Layers Graphene Coating on the Cladding Surface

2020· article· en· W3021458884 on OpenAlexaff
Fu Liu, Mei Qi, Tuan Guo

Bibliographic record

VenueAnnalen der Physik · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsCarleton University
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceGrapheneOpticsCladding (metalworking)Saturable absorptionOptoelectronicsWavelengthFiber laserComposite materialNanotechnology

Abstract

fetched live from OpenAlex

Abstract The coupling of less than 80 µW of in‐plane polarized near‐infrared light in a 6 nm‐thick graphene layer deposited on an optical fiber produces important permittivity changes leading to bistability and self‐starting 50% modulation of over 1 W of continuous wave light in the core. These features arise from resonant coupling of core‐guided light into the cladding by a 12‐degree tilted, 1 cm long fiber Bragg grating via narrowband, polarization‐dependent resonances that allow the selection of cladding modes with electric fields polarized in the plane of the graphene. The pulse repetition rate of the modulation increases from 10 to 269 Hz for input powers ranging from 0.3 to 1.33 W in the core, with no evidence of saturation. Investigations into the origin of these effects through physical modelling and different experimental conditions point to photo‐induced Joule heating in the graphene layer giving rise to temperature increases of the order of 60 °C and corresponding permittivity changes in the graphene and underlying silica fiber. Those changes lead to shifts in the resonance positions which result in the equivalent of saturable absorption for light guided in the core without direct contact with the absorbing graphene layer.

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 score0.006
Threshold uncertainty score0.716

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 head0.037
GPT teacher head0.261
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

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

Citations6
Published2020
Admission routes1
Has abstractyes

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