Machine Learning‐Guided Design of Shell‐Based Multistable Lattices for Superior Energy Absorption and Reusability (Small 45/2025)

Energy-Absorbing Materials In article number 2502789, Yujia Wang, Huajian Gao, and Xiaoyan Li present a new class of straw-inspired shell-based lattices with tunable multistability, guided by machine learning. This design strategy extends to 3D hierarchical metamaterials with multidirectional multistable behavior. These metamaterials exhibit multiple stable states along all three directions and large volume changes, highlighting their potential for highly deformable and reconfigurable materials.