Designing complex architectured materials with generative adversarial networks.

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 generativ

SUBMITTER: Mao Y 

PROVIDER: S-EPMC7182413 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature