Vat photopolymerization of Ka-band Luneburg lenses: design, fabrication methods, and characterization
Bibliographic record
Abstract
This study investigates the performance of 3D-printed Luneburg lenses using various printable dielectric materials, including commercial resins such as Radix from Rogers Corporation and Rigid 4000 from Formlabs, as well as what we believe to be a new in-house formulated liquid crystal polymer (LCP) resin. Three Luneburg lenses were successfully designed and fabricated using these materials. Step-by-step design processes of 3D printed Luneburg lenses are fully described along with their electrical characterization in the frequency range of 26.5 to 38 GHz. The measurement results reveal that the Luneburg lens fabricated with Radix exhibits the best performance thanks to its low loss. Improvement of gain performance in excess of 14 dB is achieved using a Radix-made in the fabrication process. On the other hand, the Luneburg lens from in-house-formulated LCP demonstrates a similar superior gain improvement up to 13.5 dB. In contrast, the lens fabricated with standard Formlabs resin exhibits inferior performance due to higher loss of the material, which renders it a lower grade candidate for the fabrication of microwave lenses. The paper also offers a comprehensive comparison of the physical properties of the materials in terms of the complexity of the specialized printing process.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".