Design and Validation of Locally Resonant Metaplate with Tunable Bandgaps for Inertial Sensors
Bibliographic record
Abstract
Abstract The design, optimization, and experimental characterization of a tapered lamina emergent torsional (LET) spring architecture-based metaplate are presented. The metaplate is engineered to achieve a low-frequency, broadband elastic bandgap for noise and vibration isolation within a compact, monolithic unit cell. Transmission of elastic waves is passively suppressed in both in-plane and out-of-plane directions, enabling three-dimensional wave attenuation in a planar structure. A prototype metaplate is fabricated using single-material 3D printing for experimental validation. Experimental results demonstrate attenuation levels of approximately − 40 dB for out-of-plane excitation and − 20 dB for in-plane excitation. The bandgap is also experimentally tuned to exhibit a relative bandgap width of approximately 48% in the sub-kHz range. This approach provides an alternative to traditional locally resonant or multilayered metamaterial platforms by validating a planar LET-based bandgap mechanism at the millimetre scale. The resulting geometry framework can be adapted for future microscale implementations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".