Silicon micromachined ka-band cavities with planar line feeds for use in future generation broadband satellite communications
Bibliographic record
Abstract
A micromachining technique involving the wet chemical etching of bulk silicon wafers has been used to fabricate deep three-dimensional cavity resonators at 30 GHz. Previous attempts at forming cavities using silicon micromachining have been inhibited by the shallow depth of the cavities, which were on the order of a single wafer thickness (∼0.5 mm). This seriously degrades the available unloaded Q-factor (Q 0 ) of the cavity, which is proportional to the total cavity volume. In addition, there are added contact resistances and air-gaps due to the bonding of the wafers that are unavoidable for these cavity designs. In contrast, our technique has tried to address these issues, by introducing a two-sided etching process that allows for much deeper cavities, thus increasing the available Q 0 . This procedure also makes the alignment of the etched wafer sections much easier, which was another obstacle of past research efforts. Most importantly though, this process allows the cavity structure to be metallized after the wafers are stacked together to form the 3-dimensional shape. This enables the air-gaps and contact resistances, which appear after the wafer bonding, to be covered up and therefore their effects are reduced.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".