Engineering and Technologynpj Computational Materials
Machine learning assisted design of shape-programmable 3D kirigami metamaterials
N. A. Alderete, N. Pathak, et al.
This innovative research by Nicolas A. Alderete, Nibir Pathak, and Horacio D. Espinosa presents a cutting-edge machine learning framework tailored for designing and controlling kirigami-based materials. By utilizing clustering, tandem neural networks, and symbolic regression, the framework predicts optimal kirigami cut layouts to meet specific design criteria, showcasing its effectiveness in developing shape-shifting metamaterials.
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