Systematic design of Cauchy symmetric structures through Bayesian optimization

Using a new Bayesian Optimization algorithm to guide the design of mechanical metamaterials, we nonhomogeneous 3D structures possessing Cauchy symmetry, which dictates relationship between continuum and atomic deformations. Recent efforts merge optimization techniques with metamaterials has resulted in concentrated effort tailor their elastic post properties. Even though these properties either individual unit cells or homogenized continua can be simulated using multi-physics solvers well established schemes, they are often computationally expensive require many iterations, rendering validation stage significant obstacle metamaterial designs. This study aims provide framework on how utilize miniscule computational cost control such that specific symmetries accomplished. symmetry as objective, engineer through strategic arrangement 5 different × cubic symmetric microlattice structure. lattice design, despite constituting space 10 configurations, converge an effective solution only 69 function calls result efficiency scheme. To validate behavior were fabricated multiphoton lithography mechanically tested, revealing close correlation experiments results regime. Ultimately, similar methodology utilized other material properties, aspiring at length scales, endeavor requires inordinate computation cost. • Architected Symmetry modelled optimized. A novel scheme is developed discretised multi-layered non-monolithic metamaterials. The optimum was obtained for million structures. In-situ SEM microindentation measurements revealed Born rule macroscopically “translated” into