Metamaterial Unit

Metamaterial unit design focuses on creating artificial structures with tailored properties exceeding those of natural materials, primarily achieved by optimizing their internal geometries and material compositions. Current research heavily utilizes machine learning, particularly deep learning models like neural networks (including graph neural networks and diffusion models), Bayesian optimization, and reinforcement learning, to efficiently explore the vast design space and predict material responses, often bypassing computationally expensive simulations. This field is significant because it enables the creation of materials with precisely controlled mechanical, acoustic, and optical properties for applications ranging from advanced robotics and protective equipment to novel photonic devices and computational substrates.