Voxel-based additive manufacturing of biomimetic functionally graded materials

Voxel-based additive manufacturing of biomimetic functionally graded materials

Herranz de la Nava, Alba (TU Delft Mechanical, Maritime and Materials Engineering)

Mirzaali Mazandarani, Mohammad (mentor)
Zadpoor, Amir (mentor)

Delft University of Technology

Biomedical Engineering

2018-11-30

Nature has evolved materials with outstanding mechanical properties, which attain high values of both strength and toughness. The key to their success lies in the combination of hard and soft constituents in a intricate pattern. The design of natural materials allows for the development of toughening mechanisms that increase the overall fracture energy of the sample while keeping the stiffness provided by the hard constituents, as it is demonstrated in the brick-and-mortar pattern of nacre. In addition, the development of graded material transitions avoids failure at material interfaces with a high mismatch in stiffness. This is crucial for the success of certain structures in the human body, such as the connections of ligaments and tendons to bone. Due to their marvellous design and superior mechanical properties, natural materials are a source of inspiration for the development of biomimetic advanced materials. The advancement of multi-material additive manufacturing (AM) has eased the production of structures that combine materials with different properties.
Voxel-based 3D printing is an innovative technique that allows for the strategic placement of voxels of different materials at a high resolution using PolyJet technology. Several studies have attempted to produce brick-and-mortar or graded patterns. However, the production of functionally graded structures by voxel-based additive manufacturing is still a novelty, and the effects of the graded pattern and material ratio have not been assessed. In addition, the performance of brick-and-mortar patterns and graded transitions in the same structure have not been evaluated.
In this project, several patterns for material graded transitions have been designed, produced by voxel-based AM and assessed by fracture mechanics and tensile tests. The effect of different material ratio distributions on the mechanical properties of the specimen have also been evaluated. Digital image correlation techniques provided insightful information about the strain distribution in certain patterns, and how they influence the fracture toughness of samples. A biomimetic model of a human knee was developed in order to compare the performance of sharp and graded interfaces in real-like scenarios. Furthermore, brick-andmortar patterns with different designs, hierarchy levels and platelet aspect ratio have been created, and the patterns’ single and combined effect with a gradient pattern have been assessed. The results outlined that the function that determines the pattern formaterial change does not contribute significantly to an improvement of the mechanical properties, specially when the transition reaches points of pure material concentration. By contrast, when complementary material ratios are located at both sides of an
interface, the fracture toughness of the samples is enhanced. Thus, it was demonstrated that the distribution of material ratio in a complementary manner but avoiding sites of pure hard material presents the most optimal boost of toughness in the specimens. The biomimetic human knee model proved the efficacy of graded material transitions over sharp material interfaces in withstanding higher tensile loads. Finally, the addition
of graded transitions to brick-and-mortar patterns contributes to an increase of the fracture toughness of the samples, followed by a slight decrease of the overall stiffness. The increase of fracture energy is linked to the increased plasticity region in front of the crack tip that was revealed in DIC tests. Changing the placement of the crack tip and increasing the percentage of hard material that conforms the gradient could increase the overall stiffness as well.

Additive Manufacturing
Biomimetic
Gradients

http://resolver.tudelft.nl/uuid:119cf85d-4359-4fab-8fe8-1ced1ea6224b

2019-11-30

Student theses

master thesis

© 2018 Alba Herranz de la Nava