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Disordered mechanical metamaterials with programmable properties
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AI
DOI：10.1016/j.actamat.2024.120700.png)
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Abstract
En 中文
Natural materials usually display irregular and diverse structures, endowing them with excellent properties such as compression resistance, impact resistance, and fatigue resistance. These properties inspire people to simulate natural materials, which currently focus on reconstructing their structural morphologies and splicing their microstructures. However, natural materials undergo self-organized generation on the basis of nodes, and there is no fixed pattern to their structural morphology and microstructures. Understanding the role of unfixed patterns in determining natural material properties provides a way to design new structures. We propose a node-based self-organized generation method to generate new structures. The method starts with a single node and constructs bonds to adjacent nodes under the guidance of logical constraints and probability combinations. Disordered mechanical metamaterials are generated by integrating all the bonds. We characterize these morphologically variable metamaterials using 34 structural descriptors and explore the relationship between descriptors and metamaterial properties. Research indicates that volume fraction and average node connectivity have the greatest influences on Young's modulus and Poisson's ratio of these metamaterials. Our method can precisely control the disorder and average node connectivity in local regions of the disordered mechanical metamaterials. In such cases, we show its application in local stress relief. This approach, which simulates the natural material generation process, can promote the sustainable development of artificial structures with superior properties.
Keywords:
Node-based self-organized generation method
Disordered mechanical metamaterials
Structural descriptors
Local stress relief