Researchers at Delft University of Technology introduce Deep-DRAM, an AI tool poised to transform metamaterial development. By transcending traditional material limitations, Deep-DRAM promises customizable materials with unparalleled functionalities. Metamaterials, engineered to defy natural properties, find applications in telecommunications, acoustics, and aerospace technology.
Conventional metamaterial design faces challenges in solving the inverse problem, hindering practical applications. Deep-DRAM addresses this hurdle by employing deep learning models and finite element simulations. Its modular framework enables the creation of durable metamaterials tailored to specific needs, a departure from previous designs prone to failure.
The innovation lies in Deep-DRAM’s ability to generate microarchitectures resistant to fatigue and fracture, ensuring practical usability. Its modular design streamlines the computational process, making it cost-effective and versatile for various industries.
“Traditionally, designers use the materials available to them to design a new device or a machine. The problem with that is that the range of available material properties is limited. Some properties that we would like to have just don’t exist in nature,” said researcher Dr. Amir Zadpoor.
“Our approach is: tell us what you want to have as properties and we engineer an appropriate material with those properties. What you will then get is not really a material but something in-between a structure and a material, a metamaterial.”
Beyond laboratory confines, Deep-DRAM offers tangible solutions for healthcare, aerospace, and beyond. By marrying AI with material science, it opens avenues for orthopedic implants, soft robotics, and adaptive mirrors. With Deep-DRAM’s transformative potential, industries can harness previously untapped benefits, marking a significant leap forward in material innovation.
Source: thedebrief.org
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