Engineered Materials for Acoustics: Metamaterials, Sonic Crystals and Calculated Microstructures
Bibliographic record
Abstract
For two decades, research on acoustic materials (absorbent and insulating) has largely translated into metamaterials and sonic crystals or, more generally, into engineered acoustic materials. A large number of scientific articles on these unconventional materials appear every week, even every day. While research is moving towards a more in-depth knowledge of these materials and new concepts, their applications are already numerous in several sectors of industry such as building and transport. Through all the research, it is sometimes difficult to fully define what acoustic metamaterials, sound crystals, and engineered acoustic materials really are. This presentation presents the author's personal definition of these different classes of materials, adding the class of acoustic materials with calculated microstructure, and grouping them under the family of "engineered acoustic materials". Definitions are proposed for each class and examples of applications are presented.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".