Fabrication Error Modeling and Analysis of an <i>E</i>-Band MHMIC Balanced Power Detector
Bibliographic record
Abstract
This study models and analyses the fabrication errors of an ultra-wideband (UWB) Schottky diode power detector using miniature hybrid-microwave integrated-circuit (MHMIC) technology. The fabricated balanced power detector is composed of two zero-bias GaAs Schottky diodes, a 90°-hybrid coupler, and two pairs of broadband butterfly open stub reflectors. The circuit is designed on a thin film ceramic substrate having a thickness of$127~\mu \text{m}$with a$1~\mu \text{m}$gold conductive layer, and a 20 nm Titanium Oxide ($TiO_{2}$) resistive layer. The simulations use a computer model of the broadband coupler from on-wafer measurements to obtain an authentic fabrication error analysis. Moreover, the trade-off between the maximum efficiency and the fabrication error tolerance of the balanced power detectors is discussed. It is shown that the performance of the balanced power detector is dependent on different fabrication errors. Based on the measurement results, one of the fabricated detectors with minimum fabrication errors demonstrates a return loss of better than 10 dB over the entire frequency band of 60 to 90 GHz.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".