3D-printed highly stretchable curvy sandwich metamaterials with superior fracture resistance and energy absorption
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Bibliographic record
Abstract
This paper focuses on the potential of curvy mechanical metamaterials to show how topological design can significantly enhance fracture toughness along the in-plane and out-of-plane (through-depth) directions. The conventional re-entrant unit cell is first reformulated by introducing local curvy ligaments and then additively manufactured by three-dimensional (3D) printing to form a center/edge-notch lattice metamaterial. The new conceptual design provides multi-stiffness unit cells, helping to control stress distribution within a structure under tensile load, specifically in the vicinity of the notches where stress concentrations occur. In other words, curvy unit cells are capable of arresting and blunting the notch under tensile loads and toughening the metamaterials. The crack tip opening displacement (CTOD) method calculates the fracture toughness. Not only can the fracture of lattice metamaterials be controlled along the in-plane direction by replacing unit cells in the sensitive parts of the metamaterials, but a new assembly method is also proposed. This offers that different thin plates of metamaterials with different layouts can be sandwiched to control out-of-plane fracture propagation (through-depth propagation of opening mode fracture) for the first time in fracture mechanics. This novel sandwiching method offers a multi-step fracture and significantly improves the fracture behavior of the lattice metamaterials from brittle to ductile by taking advantage of multiple through-thickness thin plates instead of considering one thick specimen. A detailed analysis of the effects of the ligament curvature value on the fracture behavior is presented. The results reveal that the more curvature, the more extension (ductility) will be realized, but too large curvature design can provide lower energy absorption capacity.
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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 it