A graph-encoded design framework produces 3D woven metamaterials with anisotropic stiffness tunable by over an order of magnitude and stretchability up to a factor of four, plus programmable failure.
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Direction-aware TDA descriptors, created by embedding the compression axis into filtrations, yield higher accuracy for Young's modulus prediction in porous materials than standard invariant descriptors.
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Design framework for programmable three-dimensional woven metamaterials
A graph-encoded design framework produces 3D woven metamaterials with anisotropic stiffness tunable by over an order of magnitude and stretchability up to a factor of four, plus programmable failure.
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Direction-aware topological descriptors for Young's modulus prediction in porous materials
Direction-aware TDA descriptors, created by embedding the compression axis into filtrations, yield higher accuracy for Young's modulus prediction in porous materials than standard invariant descriptors.