Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation

Abstract

Abstract Mechanical metamaterials represent a distinct category of engineered materials characterized by their tailored density distributions to have unique properties. It is challenging to create continuous density distributions to design a smooth mechanical metamaterial sequence in which each metamaterial possesses stiffness close to the theoretical limit in all directions. This study proposes three near‐isotropic, extreme‐stiffness, and continuous 3D mechanical metamaterial sequences by combining topology optimization and data‐driven design. Through innovative structural design, the sequences achieve over 98% of the Hashin–Shtrikman upper bounds in the most unfavorable direction. This performance spans a relative density range of 0.2–1, surpassing previous designs, which fall short at medium and higher densities. Moreover, the metamaterial sequence is innovatively represented by the implicit neural function; thus, it is resolution‐free to exhibit continuously varying densities. Experimental validation demonstrates the manufacturability and high stiffness of the three sequences.

Keywords

• extreme stiffness
• implicit neural representation
• isotropic metamaterials
• metamaterial sequences