Graphene-based terahertz reconfigurable printed ridge gap waveguide structure
Bibliographic record
Abstract
Graphene-based microwave devices have enabled reconfigurability, thus paving the way to the realization of flexible wireless terahertz systems with featured performances. Despite great progress in the development of graphene-based terahertz devices in the literature, high insertion loss and wide tunable range are still significant challenges at such high frequencies. In this work, we introduce the use of graphene to implement a reconfigurable printed ridge gap waveguide (RPRGW) structure over the terahertz frequency range for the first time. This guiding structure is suitable for both millimeter and terahertz wave applications due to its supporting quasi-TEM mode, which exhibits low dispersion compared to other traditional guiding structures. The presented solution is featured with low loss as the signal propagates in a lossless air gap, which is separated from the lossy graphene elements responsible for the reconfigurable behavior. In addition, this guiding structure is deployed to implement a tunable RPPGW power divider as an application example for the proposed structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.010 | 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 teacher head, 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".