Miniaturized 6-Bit Phase-Change Capacitor Bank with Improved Self-Resonance Frequency and $Q$
Bibliographic record
Abstract
This paper reports a 6-bit capacitor bank developed using metal-insulator-metal (MIM) capacitors with enhanced self-resonance frequency (SRF) and$Q$-factor. An easy to implement design optimization technique is discussed to improve the SRF and$Q$of high frequency MIM capacitors. Experimental data is shown for two MIM capacitors fabricated on high resistivity silicon substrate with silicon nitride as a dielectric layer. The optimized capacitors exhibit up to 45% improved SRF and up to 22% enhanced Q-factor in comparison with standards MIM designs. The capacitor bank utilizes six latching phase change material (PCM) germanium telluride (GeTe)-based RF series switches, monolithically integrated with six MIM capacitors having improved SRF. The capacitor bank measures only$0.23\ \text{mm}\times 0.27\ \text{mm}$in size, making it a highly miniaturized and versatile switched capacitor bank for integrating with numerous RF circuits. Experimental data is compared with that of standard MIM capacitor-based capacitor bank. The optimized MIM based capacitor bank provides additional 3 GHz operating bandwidth compared to the standard MIM based capacitor bank.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".