Modeling and design of heterogeneous hierarchical bioinspired spider web structures using deep learning and additive manufacturing.

ABSTRACT: Spider webs are incredible biological structures, comprising thin but strong silk filament and arranged into complex hierarchical architectures with striking mechanical properties (e.g., lightweight but high strength, achieving diverse mechanical responses). While simple 2D orb webs can easily be mimicked, the modeling and synthesis of 3D-based web structures remain challenging, partly due to the rich set of design features. Here, we provide a detailed analysis of the heterogeneous graph structures of spider webs and use deep learning as a way to model and then synthesize artificial, bioinspired 3D web structures. The generative models are conditioned based on key geometric parameters (including average edge length, number of nodes, average node degree, and others). To identify graph const

SUBMITTER: Lu W 

PROVIDER: S-EPMC10401013 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature