Low-Temperature Superconducting DC-Contact RF MEMS Switch for Cryogenic Reconfigurable RF Front-Ends
Bibliographic record
Abstract
A niobium-based superconducting dc-contact RF microelectromechanical systems switch is introduced and is thoroughly analyzed. The switch is amenable to integration with superconducting microelectronics technology. A comparison of the switch's RF performance at room and cryogenic temperatures indicates a significant improvement in the insertion loss of the switch when niobium is superconducting. The mechanical characteristic of the switch at extremely low temperature (4 K) is also investigated. The switch exhibits an increase of 18% on the actuation voltage as the temperature changes from 293 K (room temperature) to 4 K. A niobium superconducting tunable resonator is designed and tested, employing the proposed switch as the tuning element in the form of a switched capacitor bank monolithically integrated with the resonator. The measured results at 4 K clearly indicate the discrete resonance frequency states of the resonator. A three-pole tunable bandstop filter is designed with a center frequency of 1.2 GHz and dimensions of only 5 mm × 1.2 mm. The results demonstrate a tuning range of 12% while maintaining an excellent RF response of the filter.
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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".