Optical attenuation by vertically bending a rib waveguide through electrostatic zipping actuation
Bibliographic record
Abstract
In this paper we present a variable optical attenuator (VOA) that is based on microbending of a silicon-on-insulator (SOI) rib waveguide. Optical attenuation is achieved by etching away the underlying SiO2 layer in a section of the waveguide and using electrostatic deflection to introduce vertical bending. When a single-mode rib waveguide is bent, the light traveling through it will undergo mode conversion. The amount of energy transferred to lossy modes depends on the curvature of the bending section. This mechanism is studied with the help of beam propagation method (BPM) simulations. In order to achieve a substantial amount of attenuation by bending, voltages in excess of the pull-in threshold are used, bringing a portion of the waveguide into contact with the underlying silicon substrate. An electrostatic zipping action determines the bending radii and the length of the contact region. The equation for the relationship between the bending radius of the waveguide and the controlling voltage is established through the energy method, and is numerically solved. FEM modeling is also performed to validate the result from the energy model. The device is fabricated by conventional silicon processing steps, plus steps to solve the stiction problem. The test setup for the device consists of a home-made interference microscope to monitor the vertical movement of the waveguide under test and align the input fiber to the waveguide, and other instruments to monitor the output from the device and perform the attenuation measurement. The experimental data agree well with both the BPM simulations and the calculations for the zipping actuation. The tested devices show that we can achieve 14dB attenuation over a 1mm span of a bent waveguide.
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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".