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Additively manufactured auxetics (structures exhibiting a negative Poisson’s ratio) offer a unique combination of enhanced mechanical strength and energy absorption. These properties can be further improved through strategic material placement and architectural design. This study investigates the feasibility of fabricating bi-material rotating-square auxetic structures composed of flexible and rigid constituents in their squares and hinges. Rotating-square auxetic structures are manufactured via material extrusion using rigid polylactic acid (PLA) and flexible thermoplastic polyurethane (TPU) to explore the effects of material distribution on mechanical performance and failure characteristics at the macro (i.e., component) and meso (i.e., cell) scales. Baseline tests are conducted to quantify single- and bi-material interfacial strength and failure modes under normal, shear, and combined loading conditions. Upon validation of interface integrity, single- and bi-material auxetic structures are fabricated and tested in uniaxial compression. Relative to the TPU single-material structure, the PLA square-TPU hinge structure provides a 33% increase in structural stiffness, increases energy absorption, delays the global densification strain by 10%, yields a structural Poisson’s ratio at least 0.3 lower than its single-material counterpart through global axial strains of 20%, and demonstrates partial shape recovery. Multiscale experimental analyses supplemented by a kinematic model reveal the rotation-dependent stiffening mechanisms of these structures, highlighting the benefits of flexible hinge materials. Bi-material structures with flexible hinges are shown to have bilinear trends in structural stiffness and energy absorption, not intrinsic to their single-material counterparts. These findings highlight the potential of bi-material design strategies in advancing the functionality and tunability of auxetic structures for the next generation of mechanical metamaterials.
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This content will become publicly available on December 1, 2025
An autonomous design algorithm to experimentally realize three-dimensionally isotropic auxetic network structures without compromising density
Abstract Auxetic materials have a negative Poisson’s ratio and are of significant interest in applications that include impact mitigation, membrane separations and biomedical engineering. While there are numerous examples of structured materials that exhibit auxetic behavior, the examples of engineered auxetic structures is largely limited to periodic lattice structures that are limited to directional or anisotropic auxetic response. Structures that exhibit a three-dimensionally isotropic auxetic response have been, unfortunately, slow to evolve. Here we introduce an inverse design algorithm based on global node optimization to design three-dimensional auxetic metamaterial structures from disordered networks. After specifying the target Poisson’s ratio for a structure, an inverse design algorithm is used to adjust the positions of all nodes in a disordered network structure until the desired mechanical response is achieved. The proposed algorithm allows independent control of shear and bulk moduli, while preserving the density and connectivity of the networks. When the angle bending stiffness in the network is kept low, it is possible to realize optimized structures with a Poisson’s ratios as low as −0.6. During the optimization, the bulk modulus of these networks decreases by almost two orders of magnitude, but the shear modulus remains largely unaltered. The materials designed in this manner are fabricated by dual-material 3D-printing, and are found to exhibit the mechanical responses that were originally encoded in the computational design engine. The approach proposed here provides a materials-by-design platform that could be extended for engineering of optical, acoustic, and electrical properties, beyond the design of auxetic metamaterials.
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- Award ID(s):
- 2011854
- PAR ID:
- 10590200
- Publisher / Repository:
- Springer Nature
- Date Published:
- Journal Name:
- npj Computational Materials
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 2057-3960
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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