Scalable Active Metamaterials for Shape-Morphing

@misc{cui2026scalable,
  title = {{Scalable Active Metamaterials for Shape-Morphing}},
  author = {Jipeng Cui and Wei "Wayne" Chen},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2605.07030},
  eprint = {2605.07030},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.07030},
}

TY  - UNPB
TI  - Scalable Active Metamaterials for Shape-Morphing
AU  - Jipeng Cui
AU  - Wei "Wayne" Chen
PY  - 2026
DA  - 2026/10/21
PB  - arXiv
DO  - 10.48550/arxiv.2605.07030
UR  - https://arxiv.org/abs/2605.07030
AB  - Shape-morphing materials allow structures such as morphing wings, soft robots, and deployable devices to change their shape on demand without mechanical joints or motors. Aperiodic active metamaterials, in which every unit is designed individually, can realize complex programmed shape changes, but their design by structural optimization requires repeated analyses of the full structure, at a cost that grows rapidly with the number of units. This paper presents a scalable active metamaterial (SAM) framework that designs such structures without simulating the assembled structure. The design domain is discretized into unit cells composed of a stiff frame with compliant hinges and a soft, thermally active infill. The stiff frame limits the interaction between neighboring unit cells, which approximately decouples the design problem into two scales. At the macroscale, the deformation required for each unit cell is obtained by a constrained Laplacian mesh-editing formulation with soft data-driven feasibility constraints. At the microscale, the infill geometry of every unit cell is generated by a conditional diffusion model trained on finite-strain finite element simulations of unit cells. All designs are verified by geometrically nonlinear finite element simulations of the assembled structures. The design cost grows approximately linearly with the number of unit cells. The framework is demonstrated on single-point actuation, multi-point control, and shape matching tasks. We further analyze the sources of the remaining error and discuss possible ways to mitigate it. This work establishes a foundation for the systematic, scalable design of highly complex shape-morphing active metamaterials and for understanding the mechanisms governing their target-matching accuracy.
ER  -