Mechanical Metamaterials with Discontinuous and Tension/Compression‐Dependent Positive/Negative Poisson's Ratio
Bibliographic record
Abstract
Ordinary materials have positive Poisson's ratios (PRs), and the currently known mechanical metamaterials possess negative PRs both under tension and compression. Herein, two types of novel cellular structure units with tension/compression‐dependent positive/negative PRs are demonstrated. For type I structure, the unit exhibits a positive PR during tension and a negative PR during compression, while for type II structure, the unit shows a negative PR during tension and a positive PR during compression. The deformation behaviors of the new metamaterials are first predicted by a simple analytical model and finite‐element method calculations, and the predicted results are then confirmed experimentally. Numerical and experimental studies show that for the plane angle , the unit of the new metamaterial switches its PR under compression and exhibits a discontinuous change in the PR. The deformation law does not depend on either the Young's modulus or the hardness of the material. The geometrically determined deformation behaviors of the proposed metamaterials are observed in 2D and 3D cellular structures and are proven to be robust through numerical and experimental studies. The proposed mechanical metamaterials can be applied as new deformation‐protected materials in energy‐absorbing devices, soft robotics, and tissue engineering scaffolds and as thermal deformation materials.
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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 | 0.000 |
| 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 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".