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Record W3016880865 · doi:10.3390/app10072603

Tunable Fano Resonances in an Ultra-Small Gap

2020· article· en· W3016880865 on OpenAlexfundno aff
Fuqiang Yao, Fang Li, Zhicong He, Yahui Liu, Litu Xu, Xiaobo Han

Bibliographic record

VenueApplied Sciences · 2020
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsnot available
FundersWuhan National Laboratory for OptoelectronicsNational Natural Science Foundation of ChinaCollege of Family Physicians of Canada
KeywordsMaterials scienceRefractive indexDielectricFano resonanceOptoelectronicsFigure of meritQuadrupoleResonance (particle physics)DipolePlasmonChemistryPhysics

Abstract

fetched live from OpenAlex

A Fano resonance is experimentally observed in a single silver nanocube separated from a supporting silver film by a thin aluminum oxide film. The resonance spectrum is modulated by changing the size of the silver nanocube and its distance from the silver film. The system is fabricated by a bottom-up process with an accurately controlled nanogap at the sub-6-nm scale. The simulation result shows that the destructive interference between the dipole mode and the quadrupole mode in this “nanocube on mirror” (NCoM) structure is responsible for the resonance. The spectra red-shifted as the size of the silver nanocube increased and its distance from the silver film decreased. In addition, a refractive index sensitivity of the spectrum of 140 meV/RIU (refractive index unit), with a 2.4 figure of merit, is obtained by changing the dielectric environment around the silver nanocube. This work will enable the development of high-performance tunable optical nanodevices based on NCoM structures.

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.264
Teacher spread0.195 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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