Cost-Effective 3-D-Printable Image Dielectric Guides Based 3-dB Coupler for Millimeter-Wave Applications
Bibliographic record
Abstract
Low-cost 3-D-printing techniques are proposed to fabricate image-dielectric guides (IDGs) for millimeter-wave (mm-wave) applications in the Ka band. The 3-D-printed IDG is fabricated by the stereolithography (SLA) process using a polymer resin. An open-ended coaxial probe technique has been employed to characterize the electrical properties of the 3-D material from 26 to 40 GHz. The conventional IDG design is modified by introducing a thinner dielectric layer between the dielectric guides (DGs) and the ground plane. This layer improves the fabrication and measurement accuracy without affecting the IDG performance. Furthermore, the two-line transmission lines technique is used to characterize the propagation constant. The measurement shows an insertion loss of 0.025 dB/mm. Taking advantage of the low-cost and low-loss attributes of IDGs, a 3-dB IDG-based coupler has been designed. The proposed techniques allow the customization of the IDG-coupler for different coupling levels just by varying the slot width and rotation. Due to structure simplicity, the proposed coupler prototypes are fabricated using just copper tape and a 3-D printer. The 3-dB coupler reveals a bandwidth of 5 GHz with ±0.7 dB of power equality and 20 dB of isolation. The simplest structure, high isolation and matching, control over coupling ratio, and much lower fabrication cost emphasize the use of the proposed coupler in mm-wave 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".