Revolutionizing Antenna Design: Exploring the Frontier of 3D Printed Lens Technologies
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".