Bibliographic record
Abstract
The possibility to control supersonic acoustic wave propagation is intriguing, but when modeling phononic crystal devices, supersonic surface acoustic waves are mired by radiative attenuation and, hence, eschewed in many device designs. In this paper, we study supersonic surface acoustic wave modes in shallow hole phononic crystals computationally with respect to the three bulk wave sound barriers of cubic (001) GaAs. From a first principles modeling approach of linear elasticity, the finite element method, and with the aid of characterization parameters for systematic modal categorization, detailed nuances are observed for supersonic surface waves propagating along the [110]-direction of GaAs with a periodically patterned surface. Modes of interest are distinguished by possessing both strain energy and squared polarization ratios above defined thresholds. The square array of shallow inclusions imparts a metamaterial surface layer effect that results in marked changes in the dispersion, the bulk wave hybridization, and the modal interactions of the surface modes in the Γ-X direction of the phononic crystal, which are characterized by their modal profiles and attenuation via bulk wave radiation. From these findings, we propose an extended sound cone concept to accommodate supersonic surface acoustic waves with low attenuation. Furthermore, at frequencies above the shear vertical bulk dispersion line, well-bounded surface acoustic wave modes are revealed, and the phenomenon of these supersonic modes with limited bulk wave coupling is explored. From these detailed band structures, the systematic method of mode characterization reveals deeper insights into modes that exist in shallow phononic crystals on cubic GaAs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.777 | 0.695 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".