Terahertz Components by Additive Manufacturing: Material and Fabrication Characterizations Realized Through Bragg Structures
Bibliographic record
Abstract
This work explores Bragg structures and superstructures for the terahertz regime that are 3-D printed with two filament materials, i.e., high-impact polystyrene (HIPS) and cyclic olefin copolymer (COC). We show underlying frequency responses that come about due to the material absorption and chosen 3-D printing resolution. A terahertz time-domain spectroscopy analysis shows the favorable low absorption coefficient of COC filament material compared to that of HIPS filament material. Through a demonstration of terahertz Bragg superstructures for both HIPS and COC filament material, we show the contrast in performance and mitigation of undesired absorption for a terahertz photonic element made from COC filament material. The experimental results show agreement with a finite-difference time-domain simulation of the terahertz Bragg superstructures. Through a demonstration of terahertz Bragg structures for both HIPS and COC filament material, we show the effect of printing resolution (over 50–400 μm range) of the terahertz spectral response. Terahertz Bragg structures and superstructures made from COC filament material show great promise for rapid prototyping of terahertz photonic elements.
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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) | 0.000 | 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".