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Record W4389232788 · doi:10.1109/lawp.2023.3338511

Cost-Effective Design of a Reflectarray Antenna for 5G and Millimeter-Wave Applications Utilizing 3-D-Printed Components

2023· article· en· W4389232788 on OpenAlexafffund
Behrokh Beiranvand, Ashwin K. Iyer, Rashid Mirzavand

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2023
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Alberta
FundersAlberta InnovatesCMC Microsystems
KeywordsExtremely high frequency3d printedAntenna (radio)Printed circuit boardMicrostrip antennaMaterials scienceElectronic engineeringComputer scienceElectrical engineeringEngineeringTelecommunications

Abstract

fetched live from OpenAlex

A novel low-cost 3-D-printed reflectarray is proposed based on a spatial phase-shifting technique. It consists of a layer of patches and a 3-D-printed underlayer covered by copper tape that acts as a ground plane. As part of this study, a low-cost fabrication technique is used to design a reflectarray for 5G millimeter-wave frequencies. At 35 GHz, far-field patterns for various radiation angles have been observed, alongside the achievement of reflection magnitude and phase characteristics spanning the frequency range from 20 to 42 GHz. A good agreement is observed between the simulated and measured radiation patterns for the fabricated prototypes. The proposed reflectarray structure is more than 70% efficient.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.779

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 head0.057
GPT teacher head0.268
Teacher spread0.211 · 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

Citations12
Published2023
Admission routes2
Has abstractyes

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