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Record W2282920859 · doi:10.1021/acs.nanolett.5b01727

Achromatic Metasurface Lens at Telecommunication Wavelengths

2015· article· en· W2282920859 on OpenAlexaff
Mohammadreza Khorasaninejad, Francesco Aieta, Pritpal S. Kanhaiya, Mikhail A. Kats, Patrice Genevet, D. Rousso, Federico Capasso

Bibliographic record

VenueNano Letters · 2015
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Waterloo
FundersAir Force Office of Scientific ResearchGoogleNational Science Foundation
KeywordsAchromatic lensOpticsWavelengthLens (geology)Monochromatic colorResonatorDielectricAperiodic graphBroadbandOptoelectronicsWavefrontDispersion (optics)PhysicsPhotonicsMaterials science

Abstract

fetched live from OpenAlex

Nanoscale optical resonators enable a new class of flat optical components called metasurfaces. This approach has been used to demonstrate functionalities such as focusing free of monochromatic aberrations (i.e., spherical and coma), anomalous reflection, and large circular dichroism. Recently, dielectric metasurfaces that compensate the phase dispersion responsible for chromatic aberrations have been demonstrated. Here, we utilize an aperiodic array of coupled dielectric nanoresonators to demonstrate a multiwavelength achromatic lens. The focal length remains unchanged for three wavelengths in the near-infrared region (1300, 1550, and 1800 nm). Experimental results are in agreement with full-wave simulations. Our findings are an essential step toward a realization of broadband flat optical elements.

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 score0.002
Threshold uncertainty score0.005

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.055
GPT teacher head0.270
Teacher spread0.215 · 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

Citations457
Published2015
Admission routes1
Has abstractyes

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