3D-printed multi-functional sinusoidal metamaterials for simultaneous vibration isolation and electricity generation
Bibliographic record
Abstract
This study introduces 3D-printed multi-functional sinusoidal metamaterials designed for simultaneous vibration isolation and electricity generation. The innovative design follows the sinusoidal patterns derived from re-engineered common auxetic re-entrant unit cells, resulting in multi-stiffness lattice structures. Layers of unit cells, with one rotated 90°, are integrated, facilitating local buckling in the vertical beams under compression. A quasi-zero-stiffness (QZS) mechanism, achieved through local buckling-induced nonlinearity, is incorporated to enhance vibration isolation. Two stabilizers are designed to maintain global structural stability under compression and dynamic loads, and the underlying deformation mechanisms are elucidated by finite element analysis (FEA) and experiments. Experimental evaluation reveals effective vibration isolation for frequencies above 15 Hz. For electricity generation, two piezoelectric materials are employed, namely Lead zirconate titanate (PZT) and piezo bender (PB). The flexible lattice structure, made from thermoplastic polyurethane (TPU), can withstand substantial bending deformations under a specific load and simultaneously apply bending forces to the PB. This leads to electricity generation at approximately 3 volts (V) and maximum generated power around 700 microwatts per gravity ( μ W g ) by one PB at a low frequency of 15 Hz, where vibration isolation arises. Meanwhile, one PZT, mounted on a polylactic acid (PLA)-based semi-honeycomb structure, generates energy due to higher dynamic forces caused by high-stiffness property of PLA, leading to electricity generation at around 500 millivolts (mV), and a maximum generated power of 800 μ W g at a high frequency of 90 Hz. The proposed metamaterials exhibit material-independent properties with multi-functional potentials for simultaneous vibration isolation and electricity generation. They support wearable applications, enabling motion tracking and injury prevention in protective gear through self-powered sensing. In civil structures, these hybrid metamaterials can be embedded in bridge joints, isolation pads, or foundations to reduce low-frequency vibrations and power wireless sensors for real-time, self-sustained structural health monitoring.
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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) | 0.000 | 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".