Integrated silicon photonics transduction of even nanomechanical modes in a doubly clamped beam
Bibliographic record
Abstract
Nanomechanical devices have significant potential as mass sensors because small changes in vibrational resonance frequency can be translated to mass of an analyte for single-molecule detection. By observing multiple vibrational modes simultaneously, the mass and position of the adsorbed analyte can be determined more accurately. Additionally, by using optomechanical actuation and detection of nanomechanical devices, the displacement sensitivity can be improved significantly, which is highly beneficial for mass sensing applications. In particular, optomechanical transduction can be achieved using integrated photonics, which is a compact approach that greatly simplifies the optomechanical measurement. However, even vibrational modes are difficult to detect with integrated photonics, since with even modes there is a zero effective index shift over the vibrating beam. In this work, we demonstrate the measurement of even nanomechanical modes. We fabricated a doubly clamped beam by releasing a straight section of an optical racetrack resonator from the silicon dioxide underneath. By performing this process twice, a step is fabricated in the substrate beneath the beam. The step permits the excitation and detection of even modes of vibration due to a nonzero effective index shift. Transduction of odd modes is retained. The displacement sensitivities of the first through third modes are obtained from measurements of the thermomechanical noise floor, and are 228 fm Hz-1/2, 153 fm Hz-1/2, and 112 fm Hz-1/2, respectively. The devices are actuated by the optical force, by modulating a pump laser with an electro-optic modulator. With the addition of the driving force, up to the fifth vibrational mode is observed. The driving force for the first through third modes is compared and modeled based on integration over the mode shapes. Since the step length is approximately 38% of the beam length, the optical force on each mode is approximately 0.4 pN μm-1mW-1for an applied optical power of 0.07 mW.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".