A Biomimetic Titanium Scaffold With and Without Magnesium Filled for Adjustable Patient-Specific Elastic Modulus

材料科学 脚手架 弹性模量 刚度 模数 骨整合 多孔性 复合材料 均质化(气候) 有限元法 格子(音乐) 生物医学工程 植入 结构工程 冶金 医学 生物多样性 生态学 物理 外科 声学 生物 工程类
作者
Subhodeep Jana,Rajdeep Sarkar,Masud Rana,Samir Das,Agniswar Chakraborty,Apurba K. Das,Amit Roychowdhury,Bidyut Pal,Jyotsna Dutta Majumdar,Santanu Dhara
出处
期刊:Journal of biomechanical engineering [ASM International]
卷期号:147 (9)
标识
DOI:10.1115/1.4069210
摘要

Abstract This study focuses on determining the effective Young's modulus (stiffness) of various lattice structures for titanium scaffolds filled with magnesium and without magnesium. For a specific patient implant the success depends on adequate elastic modulus, which helps proper osteointegration. The Mg-filled portion in the Ti scaffold is expected to dissolve with time as the bone growth through the Ti scaffold porous cavity begins. The proposed method is based on a general numerical homogenization scheme to determine the effective elastic properties of the lattice scaffold at the macroscopic scale. A large numerical campaign has been conducted on 18 geometries. The three-dimensional scaffold is conceived based on the model generated from the microcomputed tomography (Micro-CT) data of the prepared sample. The effect of the scaffold's local features, e.g., the distribution of porosity, the presence of the scaffold's surface area to the adjacent bone location, strut diameter of the implant, on the effective elastic properties is investigated. Results show that both the relative density and the geometrical features of the scaffold strongly affect the equivalent macroscopic elastic behavior of the lattice. Six samples are made (three each Mg-filled and three without Mg). The compression test was carried out for each type of sample, and the displacements obtained from the test results were in close match with the simulated results from finite element analysis. To predict the unknown required stiffness what would be the ratio between the Ti scaffold and the filled up Mg has been calculated using the data-driven artificial intelligence (AI) model.
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