Tunable Fluid-Type Metasurface for Wide-Angle and Multifrequency Water-Air Acoustic Transmission
Bibliographic record
Abstract
Efficient acoustic communication across the water-air interface remains a great challenge owing to the extreme acoustic impedance mismatch. Few present acoustic metamaterials can be constructed on the free air-water interface for enhancing the acoustic transmission because of the interface instability. Previous strategies overcoming this difficulty were limited in practical usage, as well as the wide-angle and multifrequency acoustic transmission. Here, we report a simple and practical way to obtain the wide-angle and multifrequency water-air acoustic transmission with a tunable fluid-type acoustic metasurface (FAM). The FAM has a transmission enhancement of acoustic energy over 200 times, with a thickness less than the wavelength in water by three orders of magnitude. The FAM can work at an almost arbitrary water-to-air incident angle, and the operating frequencies can be flexibly adjusted. Multifrequency transmissions can be obtained with multilayer FAMs. In experiments, the FAM is demonstrated to be stable enough for practical applications and has the transmission enhancement of over 20 dB for wide frequencies. The transmission enhancement of music signal across the water-air interface was performed to demonstrate the applications in acoustic communications. The FAM will benefit various applications in hydroacoustics and oceanography.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".