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Inverse design of nonlinear mechanical metamaterials via video denoising diffusion models - Nature Machine Intelligence
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The accelerated inverse design of complex material properties—such as identifying a material with a given stress–strain response over a nonlinear deformation path—holds great potential for addressing challenges from soft robotics to biomedical implants and impact mitigation. Although machine learning models have provided such inverse mappings, they are typically restricted to linear target properties such as stiffness.
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