Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation
Year: 2024
Type: article
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.
Source: Advanced Science
Authors: Yunkai Zhao, Lili Wang, Xiaoya Zhai, Jiacheng Han, Winston Wai Shing Ma, Junhao Ding, Yonggang Gu, Xiao‐Ming Fu
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $6,120
Awards: G3960820589, G790494869
OpenAlex ID: W4404766655
