Broadband, millimeter-wave antireflection coatings for large-format, cryogenic aluminum oxide optics
Bibliographic record
Abstract
We present two prescriptions for broadband ($ {\sim} 77 - 252\;{\rm GHz} $), millimeter-wave antireflection coatings for cryogenic, sintered polycrystalline aluminum oxide optics: one for large-format (700 mm diameter) planar and plano-convex elements, the other for densely packed arrays of quasi-optical elements-in our case, 5 mm diameter half-spheres (called "lenslets"). The coatings comprise three layers of commercially available, polytetrafluoroethylene-based, dielectric sheet material. The lenslet coating is molded to fit the 150 mm diameter arrays directly, while the large-diameter lenses are coated using a tiled approach. We review the fabrication processes for both prescriptions, then discuss laboratory measurements of their transmittance and reflectance. In addition, we present the inferred refractive indices and loss tangents for the coating materials and the aluminum oxide substrate. We find that at 150 GHz and 300 K the large-format coating sample achieves $ (97 \pm 2)\% $ transmittance, and the lenslet coating sample achieves $ (94 \pm 3)\% $ transmittance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".