Personal web page : https://iramis.cea.fr/Pisp/2/daniel.bonamy.html
Laboratory link : https://iramis.cea.fr/spec/SPHYNX/
The quest toward high-performance materials combining lightness and mechanical strength gave rise to a flurry of activity: desire to reduce CO2 emissions and develop fuel-efficient vehicles in the transport industries for instance. A promising solution in this context is to replace solid materials by cellular materials of well-chosen architecture, manufactured via 3D printing. These novel materials of a new type, referred to as metamaterials, actually consume little material, meet the challenges of the circular economy and can finally be compacted at the end of their life.
Significant progress has been made recently: microlattices formed by hollow metal tubes arranged periodically into octahedron cells can have densities comparable to those of aerogels, but rigidities more than 1000 times higher (e.g. microlattice materials invented at Caltech, produced by Boeing [1])! The rules that dictate stiffness for such periodic architectures are now well understood: They are fixed by Maxwell’s criterion and the connectivity of the lattice (number of struts per node). Conversely, these periodic microlattices have the drawback of being mechanically anisotropic at the macroscopic scale: they are softer, more brittle, and more prone to damage, when stressed along certain preferred directions.
Inspired by the observation of natural architectural materials (bone structure, alveolar structure of bark...) we will seek to develop disordered architectures in order to obtain a new class of metamaterials/microlattices that are ultralight, mechanically resistant (to deformation and fracture), while remaining fully isotropic. We will use artificial intelligence (AI) tools to elucidate the optimization rules to follow, without presupposing them. This PhD project is mainly numerical and theoretical, but will be conducted in close collaboration with experimentalists.
The first step will be to implement an AI algorithm to predict density, elasticity, fracture resistance and compressive strength as a function of the input architecture geometry, via tools to be defined: cost function and associated weights, gradient descent for minimization, neural network, etc... The second step will be to define optimal architectures in terms of mechanical stiffness, crack resistance and compressive strength under prescribed constraints in terms of density and architecture isotropy. Finally, the architectures obtained will be qualified through fracture and compression experiments carried out on microlattice samples obtained by additive manufacturing with different materials (polymers, composites, and even ceramics or metallic alloys).
[1] T. A. Schaedler et al., Ultralight Metallic Microlattices, Science 334, 962-965 (2011)