Machine-learning Accelerated Design of Tough, Hierarchically Heterogeneous Ceramic Composites
The intrinsic high strength, light weight, and heat, corrosion, and irradiation resistance of ceramics positions them as nearly ideal structural materials. However, their inability to resist the growth of cracks causes any tiny flaw to grow into a catastrophically large crack; this renders ceramics brittle and impractical as structural materials for automotive, energy, aerospace, and defense applications, to name a few examples.
The overarching goal of this Designing Materials to Revolutionize and Engineer our Future (DMREF) project is to transform the fracture resistance of ceramics by introducing heterogeneous metallic features across multiple length scales into the ceramic material. The fundamental challenges to be overcome in the project are:
how can heterogeneous ceramics be computationally designed when the space of possible designs is massive? and
how can such engineered ceramics be manufactured?
These challenges look to be overcome by leveraging recent advances in machine learning for material modeling in conjunction with advanced low-temperature ceramic processing techniques. The revolutionary new class of materials to look to be designed through the project can be directly implemented in commercial applications, such as satellite structures, low-wear medical devices, armor, and hypersonic vehicles. Insights gained on the design, processing, and fracture of heterogeneous ceramics seek to drive future innovations enabling next-generation structural materials.