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Mechanical Neural-Network-Based Metamaterial That Learns Its Properties (Case No. 2022-317)

Summary: UCLA researchers in the Department of Mechanical and Aerospace Engineering have developed a new type of meta-material that can actively adapt its mechanical properties from exposure to external stimuli. Background: As technologies have evolved, humans developed new methods to produce unique materials, such as plastics, steels and composites,...

Published: 10/29/2024 | Inventor(s): Jonathan Hopkins, Erwin Mulder, Ryan Hansen Lee

Keywords(s): active actuators, additive manufacturing, Artificial Neural Network, artificial-intelligent materials, Composite Material, Composite Materials, Construction Materials, deep physical neural network, Flexible Electronics, Functional Materials, lattice structures, Materials, Medical Devices and Materials, meta materials, microarchitectured materials, Nanomaterials, Smart Material, stiffness tunability

Category(s): Materials, Mechanical, Electrical, Electrical > Signal Processing, Software & Algorithms