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Meeting 2022 TMS Annual Meeting & Exhibition
Symposium Advances in Biomaterials for 3D Printing of Scaffolds and Tissues
Presentation Title Effect of Unit Cell Topology on the Mechanical Properties of Co-Cr-Mo Triply Periodic Minimal Surface Lattices Fabricated by Selective Laser Melting
Author(s) So-Yeon Park, Kyu-Sik Kim, Bandar Al-Mangour, *Kee-Ahn Lee
On-Site Speaker (Planned) So-Yeon Park
Abstract Scope Node-free minimal surfaces sheet-based lattices can have high specific strength and stiffness. Their mechanical properties can be controllable by adjusting unit cell parameters (size, topology, etc.). In this study, Co-Cr-Mo alloy sheet lattices were manufactured by using selective laser melting (SLM). Among the minimal surface shape, Neovius and Schoen's I-WP (hereinafter, IWP) were selected with different unit cell sizes (1mm, 2.5mm, 5mm). And their mechanical properties were investigated. In the results of tensile tests, yield strength, stiffness and elongation of Neovius were higher in all unit cell sizes. Moreover, energy absorption properties of Neovius were also superior. EBSD and Digital image correlation analysis was performed to analyze the micro to macro deformation behavior by topology, and to determine the synergetic effect of the microstructure and topology. Based on the results, the deformation behavior of the Co-Cr-Mo sheet lattice produced by the SLM were also discussed.
Proceedings Inclusion? Planned:

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Curcumin and Vitamin D3 enhances osteogenic and chemopreventive properties of 3D printed CaP bone scaffolds
Development and 3D Printing of a Bioabsorbable Composite Material for Orthopaedic Applications
Effect of Unit Cell Topology on the Mechanical Properties of Co-Cr-Mo Triply Periodic Minimal Surface Lattices Fabricated by Selective Laser Melting
Effects of Cell Sedimentation on Droplet Formation Process and Cell Distribution during Inkjet Printing of Cell-Laden Bioink
Effects of Topographic Parameters on a Micropillar Surface on Cell Migration and Morphology
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Prediction of Cell Viability in Dynamic Optical Projection Stereolithography-Based Bioprinting Using Machine Learning
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