Designing complex architectured materials with generative adversarial networks
Name
eaaz4169.full.pdf
Description
Published version
Size
3.23 MB
Format
Adobe PDF
Checksum (MD5)
5777857f4ef3f48eaec0531935132acc
Author(s)
Mao, Yunwei
He, Qi
Zhao, Xuanhe
Date Issued
April 2020
Journal
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Citation
Mao, Yunwei et al., "Designing complex architectured materials with generative adversarial networks." Science Advances 6, 17 (April 2020): eaaz4169 ©2020 Authors
Version
Final published version
Abstract
Architectured materials on length scales from nanometers to meters are desirable for diverse applications. Recent advances in additive manufacturing have made mass production of complex architectured materials technologically and economically feasible. Existing architecture design approaches such as bioinspiration, Edisonian, and optimization, however, generally rely on experienced designers' prior knowledge, limiting broad applications of architectured materials. Particularly challenging is designing architectured materials with extreme properties, such as the Hashin-Shtrikman upper bounds on isotropic elasticity in an experience-free manner without prior knowledge. Here, we present an experience-free and systematic approach for the design of complex architectured materials with generative adversarial networks. The networks are trained using simulation data from millions of randomly generated architectures categorized based on different crystallographic symmetries. We demonstrate modeling and experimental results of more than 400 two-dimensional architectures that approach the Hashin-Shtrikman upper bounds on isotropic elastic stiffness with porosities from 0.05 to 0.75. ©2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution NonCommercial License 4.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1126/SCIADV.AAZ4169
