Neuron-Inspired Steiner Tree Networks for 3D Low-Density Metastructures.

ABSTRACT: Three-dimensional (3D) micro-and nanostructures have played an important role in topological photonics, microfluidics, acoustic, and mechanical engineering. Incorporating biomimetic geometries into the design of metastructures has created low-density metamaterials with extraordinary physical and photonic properties. However, the use of surface-based biomimetic geometries restricts the freedom to tune the relative density, mechanical strength, and topological phase. The Steiner tree method inspired by the feature of the shortest connection distance in biological neural networks is applied, to create 3D metastructures and, through two-photon nanolithography, neuron-inspired 3D structures with nanoscale features are successfully achieved. Two solutions are presented to the 3D Steiner tree pro

SUBMITTER: Yu H 

PROVIDER: S-EPMC8498860 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature