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Record W2953763092 · doi:10.1063/1.5095410

Practical approaches to designing and fabricating flat lenses

2019· article· en· W2953763092 on OpenAlexaff
Morteza Sedaghat, Vahid Nayyeri, Mohammad Soleimani, Omar M. Ramahi

Bibliographic record

VenueJournal of Applied Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsLens (geology)PermittivityOpticsMaterials scienceFocal pointDielectricReflection (computer programming)Point (geometry)MetamaterialRealization (probability)Layer (electronics)OptoelectronicsComputer sciencePhysicsCardinal pointGeometryNanotechnologyMathematics

Abstract

fetched live from OpenAlex

This work presents two approaches to design and implement three-dimensional (3D) graded index (GRIN) flat lenses consisting of concentric annular segments. Generally, the design of GRIN flat lenses calls for segments with very specific tailored permittivity which makes the realization of the lens challenging. To meet this challenge, each segment of the lens is replaced with a three-layer structure consisting of two materials with a high and a low dielectric constant in such a way that the high permittivity layer is sandwiched between two low permittivity layers. By treating the lens segments as transmission lines and taking the effect of multiple reflections into account, the layer thicknesses are adjusted in such a way that the rays passing through different segments interfere constructively at a focal point. To further improve the focusing performance, a practical design approach is introduced in which each segment of the lens is made of a symmetric seven-layer structure using only two materials (alternating in arrangement) with a high and a low dielectric constant. This design provides the following features: (1) almost all of the incident power passes the lens without considerable reflection, (2) the lens provides a constructive interference of the incident wave at a focal point, and (3) the lens has the potential to be manufactured using available material and technology. Numerical examples are provided in which silica and silicon are utilized as low and high permittivity materials, respectively.

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 score0.133
Threshold uncertainty score0.314

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 head0.085
GPT teacher head0.257
Teacher spread0.172 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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