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Abstract Mechanical metamaterials are architected manmade materials that allow for unique behaviors not observed in nature, making them promising candidates for a wide range of applications. Existing metamaterials lack tunability as their properties can only be changed to a limited extent after the fabrication. Herein, a new magneto‐mechanical metamaterial is presented that allows great tunability through a novel concept of deformation mode branching. The architecture of this new metamaterial employs an asymmetric joint design using hard‐magnetic soft active materials that permits two distinct actuation modes (bending and folding) under opposite‐direction magnetic fields. The subsequent application of mechanical compression leads to the deformation mode branching where the metamaterial architecture transforms into two distinctly different shapes, which exhibit very different deformations and enable great tunability in properties such as mechanical stiffness and acoustic bandgaps. Furthermore, this metamaterial design can be incorporated with magnetic shape memory polymers with global stiffness tunability, which also allows for the global shift of the acoustic behaviors. The combination of magnetic and mechanical actuations, as well as shape memory effects, impart wide tunable properties to a new paradigm of metamaterials.
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This content will become publicly available on November 5, 2025
Strain learning in protein-based mechanical metamaterials
Mechanical deformation of polymer networks causes molecular-level motion and bond scission that ultimately lead to material failure. Mitigating this strain-induced loss in mechanical integrity is a significant challenge, especially in the development of active and shape-memory materials. We report the additive manufacturing of mechanical metamaterials made with a protein-based polymer that undergo a unique stiffening and strengthening behavior after shape recovery cycles. We utilize a bovine serum albumin-based polymer and show that cyclic tension and recovery experiments on the neat resin lead to a ~60% increase in the strength and stiffness of the material. This is attributed to the release of stored length in the protein mechanophores during plastic deformation that is preserved after the recovery cycle, thereby leading to a “strain learning” behavior. We perform compression experiments on three-dimensionally printed lattice metamaterials made from this protein-based polymer and find that, in certain lattices, the strain learning effect is not only preserved but amplified, causing up to a 2.5× increase in the stiffness of the recovered metamaterial. These protein–polymer strain learning metamaterials offer a unique platform for materials that can autonomously remodel after being deformed, mimicking the remodeling processes that occur in natural materials.
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- PAR ID:
- 10579177
- Publisher / Repository:
- PNAS
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 121
- Issue:
- 45
- ISSN:
- 0027-8424
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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