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Revolutionizing Antenna Design: Exploring the Frontier of 3D Printed Lens Technologies

2025· article· W4416250105 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicAdvanced optical system design
Canadian institutionsHorizon College and Seminary
Fundersnot available
Keywords3D printingAntenna (radio)Lens (geology)Flexibility (engineering)3d printedRealization (probability)Fabrication

Abstract

fetched live from OpenAlex

The emergence of three-dimensional (3-D) printing technology has brought about a revolution in diverse sectors, including antenna design. This survey paper presents a thorough examination of the advancements and applications of 3-D printed lenses in antenna design technologies. Traditionally, lens-based antennas have relied on conventional production methods, which often limit design flexibility and hinder the realization of complex geometries. Non-uniform or asymmetric lens surfaces was designed to redirect side lobe energy into the main lobe. However, the advent of 3-D printing has expanded horizons for antenna designers, allowing them to fabricate custom-designed lenses with intricate shapes and unique functionalities. In this survey, it assesses the fundamentals of 3-D printing and its suitability for lens fabrication. This paper explores various 3-D printing technologies, materials, and fabrication processes commonly employed in antenna lens manufacturing. Additionally, it discussed the design considerations and optimization techniques specific to 3-D printed lenses for antenna applications.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.054
GPT teacher head0.241
Teacher spread0.187 · 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

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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