This article in Nature Computational Science discusses recent advancements in computational models for designing metamaterials—artificially structured materials with unique properties. The article emphasizes the limitations of human-guided approaches due to the complexity of metamaterials and the need for advanced computational methods. Physics-based models, while effective, are computationally expensive, leading to the adoption of machine learning techniques. These innovations are particularly relevant for applications in emerging computing technologies, robotics, and optical computing. The article also highlights challenges like data scarcity and calls for collaborative efforts in the field.
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