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Multi‐Material 3D Printing of Functionally Graded Hierarchical Soft–Hard Composites
Author(s) -
Mirzaali Mohammad J.,
Cruz Saldívar Mauricio,
Herranz de la Nava Alba,
Gunashekar Deepthishre,
Nouri-Goushki Mahdiyeh,
Doubrovski Eugeni L.,
Zadpoor Amir Abbas
Publication year - 2020
Publication title -
advanced engineering materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 114
eISSN - 1527-2648
pISSN - 1438-1656
DOI - 10.1002/adem.201901142
Subject(s) - materials science , digital image correlation , composite material , fracture (geology) , material properties , 3d printing
Hard biological tissues (e.g., nacre and bone) have evolved for millions of years, enabling them to overcome the conflict between different mechanical properties. The key to their success lies in the combination of limited material ingredients (i.e., hard and soft constituents) and mechanistic ingredients (e.g., functional gradients and building block hierarchical organization). However, the contribution of each material and mechanistic ingredient is still unknown, hindering the development of efficient synthetic composites. Quantitative and systematic studies of hard–soft composites are required to unravel every factor's role in properties outcome. Herein, a voxel‐by‐voxel multi‐material 3D printing technique is used to design and additively manufacture different groups of hard–soft composites. Several combinations of gradients, multilevel hierarchies, and brick‐and‐mortar arrangements are created. Single‐edge notched fracture specimens are mechanically tested and computationally simulated using extended finite element method (XFEM). It is found that functional gradients alone are not sufficient to improve fracture properties. However, up to twice the fracture energy of the hard face is observed when combining functional gradients with hierarchical designs, significantly increasing composite properties. Microscopic analysis, digital image correlation, and strain distributions predicted with XFEM are used to discuss the mechanisms responsible for the observed behaviors.