Morphogenetic mechanical metamaterials: Emerging tensor properties from self-organized structures
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866916947472416768 |
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| author | Fromentèze, Thomas Michaud, Philippe Hassny, Ali Pateloup, Vincent |
| author_facet | Fromentèze, Thomas Michaud, Philippe Hassny, Ali Pateloup, Vincent |
| contents | Understanding how living organisms spontaneously develop complex functional structures inspires innovative approaches in engineering design. Here, we introduce a decentralized generative model based on morphogenesis to autonomously grow mechanical structures with controlled tensorial properties. By adapting Turing's reaction-diffusion concept through anisotropic diffusion, our approach enables the local emergence of microstructures exhibiting tailored stiffness and anisotropy, achieving target orthotropic tensors without adjoint or topology optimization loops. The synthesis of these structures relies on a database linking morphogenetic parameters to effective elastic tensors obtained through homogenization techniques. We experimentally demonstrate this concept through a mechanical cloaking example, validating our method's capability to independently control local anisotropy and rigidity, and effectively conceal structural defects from mechanical fields. This approach not only addresses key limitations of traditional topology optimization methods but also opens new bio-inspired pathways for scalable and robust mechanical metamaterial design. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_10277 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Morphogenetic mechanical metamaterials: Emerging tensor properties from self-organized structures Fromentèze, Thomas Michaud, Philippe Hassny, Ali Pateloup, Vincent Applied Physics Computational Physics Understanding how living organisms spontaneously develop complex functional structures inspires innovative approaches in engineering design. Here, we introduce a decentralized generative model based on morphogenesis to autonomously grow mechanical structures with controlled tensorial properties. By adapting Turing's reaction-diffusion concept through anisotropic diffusion, our approach enables the local emergence of microstructures exhibiting tailored stiffness and anisotropy, achieving target orthotropic tensors without adjoint or topology optimization loops. The synthesis of these structures relies on a database linking morphogenetic parameters to effective elastic tensors obtained through homogenization techniques. We experimentally demonstrate this concept through a mechanical cloaking example, validating our method's capability to independently control local anisotropy and rigidity, and effectively conceal structural defects from mechanical fields. This approach not only addresses key limitations of traditional topology optimization methods but also opens new bio-inspired pathways for scalable and robust mechanical metamaterial design. |
| title | Morphogenetic mechanical metamaterials: Emerging tensor properties from self-organized structures |
| topic | Applied Physics Computational Physics |
| url | https://arxiv.org/abs/2509.10277 |