Dennis M. Kochmann’s KEYNOTE seminar “Breaking with periodicity in architected cellular materials”
Tid: Ti 2021-03-16 kl 16.15
Föreläsare: Professor Dennis M. Kochmann, ETH Zürich, Switzerland
Abstract. Tailoring the architecture of cellular materials – from random foams to periodic truss, plate and shell structures – has resulted in lightweight architected materials (or mechanical metamaterials) with beneficial properties. While periodic networks admit a simple prediction of their effective properties, they also come with significant disadvantages including the sensitivity to symmetry-breaking defects, limitations in spatially varying the unit cell design, and non-scalable fabrication. By contrast, nature is rich of non-periodic microstructures. So-called spinodal architectures are such examples, which evolve naturally during diffusion-driven self-assembly processes. Inspired by spinodal architectures, we introduce spinodoid topologies as an efficient theoretical description of “spinodal-like” structures. Following a simple mathematical parametrization, spinodoids have intriguing mechanical properties such as optimal stiffness scaling with density and a superb resilience due to their curvature distribution. They further cover an enormous property space in a seamless fashion, which enables multiscale topology optimization and spatially graded structures with locally optimized mechanical properties. To address the inverse challenge of identifying a microstructural architecture from the huge design space to achieve target effective properties, we demonstrate how a data-driven approach based on the integration of two neural networks can reliably and accurately generate foam-type cellular metamaterials with as-designed 3D anisotropy and density in a spatially uniform or functionally graded fashion. As an example, we highlight the suitability of this approach for the generation of bio-mimetic bone replacements. Finally, we present experimental prototypes of spinodoid architectures and discuss their extreme mechanical resilience at small scales.