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Record W4200591220 · doi:10.1039/d1nr05733b

High-directionality spin-selective routing of photons in plasmonic nanocircuits

2021· article· en· W4200591220 on OpenAlexaff
Youqiao Ma, Bo Liu, Zhiqin Huang, Jinhua Li, Zhanghua Han, Di Wu, Jun Zhou, Yuan Ma, Qiang Wu, Hiroshi Maeda

Bibliographic record

VenueNanoscale · 2021
Typearticle
Languageen
FieldEngineering
TopicPlasmonic and Surface Plasmon Research
Canadian institutionsDalhousie University
FundersStartup Foundation for Introducing Talent of Nanjing University of Information Science and TechnologyNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsDirectionalityPhotonPlasmonSpin (aerodynamics)OptoelectronicsPhysicsMaterials scienceOpticsBiology

Abstract

fetched live from OpenAlex

Efficient on-chip manipulation of photon spin is of crucial importance in developing future integrated nanophotonics as is electron spin in spintronics. The unidirectionality induced by the interaction between spin and orbital angular momenta suffers low efficiency in classical macroscopic optics, while it can be highly enhanced on subwavelength scales with suitable architectures. Here we propose and demonstrate a spin-sorting achiral split-ring coupler to unidirectionally excite dielectric-loaded plasmonic modes in two independent waveguides. We found experimentally that the impinging light with different spin can be selectively directed into one of two branching plasmonic waveguides with a directionality contrast up to 15.1 dB. A circular-helicity-independent compact beam splitter is also realized demonstrating great potential in designing complex interconnect nanocircuits. The illustrated approach is believed to open new avenues for developing advanced optical functionalities with a flexible degree of freedom in manipulation of on-chip chirality within chiral optics.

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 score0.138
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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