Biomimetic bi-material designs for additive manufacturing

Superior material properties have been recently exhibited under the concept of biomimetic designs, where the material architectures are inspired by nature. In this study, a computational framework is developed to present novel architectured bi-material structures with tunable stiffness, strength, and toughness to be used for additive manufacturing (AM). The structure of natural nacre is mimicked to design robust multilayered structures constructed from hexagonal brittle and hard building blocks bonded with soft materials and supports. A set of computational models consisting of fully bonded zones, while allowing for interlayer interactions are created to accurately mimic the interplay between the hard and soft organic phases. As required for such complex designs, the numerical constraints are properly set to run quasi-static non-linear explicit analysis, which allow for a 3× faster analysis with higher efficiency and 2× lower computational cost, when compared to static analysis. The models are used to assess the stiffness, strength and toughness of bi-material beams when subjected to a flexural three-point bending load. The influence of structural features like the soft-to-hard volume ratio (i.e. the distance between each building block, its aspect ratio, and overlap length), material features (e.g. the stiffness ratio of the hard-to-soft phases), the plastic strain failure of soft phase, and AM features (e.g. different types of within-layer/sandwiched supports) are systematically investigated. The results revealed that the toughness of the architectured beams was enhanced by up to 25% when compared to a monolithic structure. This improvement is due to the frictional tile sliding in the brittle phase and the extensive shear plastic deformation of the soft interfaces. This work provides compatible designs to facilitate the AM of nacre-based bi-martial structures with balanced/tailored mechanical performance and to understand the influence of the architectural parameters.