3D打印定制硬度匹配的超生物材料,具有接近零的auxecity,用于承重组织修复

Pub Date : 2023-09-01 Epub Date: 2023-06-19 DOI:10.1016/j.bprint.2023.e00292
Chameekara T. Wanniarachchi , Arun Arjunan , Ahmad Baroutaji , Manpreet Singh
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引用次数: 1

摘要

元生物材料的发展为生物医学设备的大规模个性化开辟了令人兴奋的新机会。这篇研究论文详细介绍了CoCrMo元生物材料结构的发展,该结构促进了个性化的刚度匹配,同时也表现出接近零的弹性。利用激光粉末床融合,表征了元生物材料的多孔结构,显示出接近零泊松比的潜力。研究还引入了一种新的替代模型,该模型可以预测元生物材料的孔隙率(φ)、屈服强度(σy)、弹性模量(E)和负泊松比(−υ),并通过原型试验和数值模拟实现。然后使用该模型来通知多标准理想目标,显示最佳的近零- υ为- 0.037,目标刚度为17.21 GPa。参数分析表明,meta-生物材料的- υ、φ、σy和E值分别为- 0.02 ~ - 0.08、73.63 ~ 81.38%、41 ~ 64 MPa和9.46 ~ 20.6 GPa。在这项研究中,开发了一个替代模型,目的是为骨支架的生产产生个性化的场景。通过利用该模型,可以实现接近零的- υ和有针对性的刚度个性化。这一突破对骨组织工程领域具有重要意义,并可能为改善患者预后铺平道路。所提出的方法是开发生物材料和生物医学设备的有力工具,可以根据需要进行3D打印,用于承重组织重建。它有可能促进针对各种疾病和损伤的高度定制和有效治疗的创造,最终提高患者的治疗效果。
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3D printing customised stiffness-matched meta-biomaterial with near-zero auxeticity for load-bearing tissue repair

The evolution of meta-biomaterials has opened up exciting new opportunities for mass personalisation of biomedical devices. This research paper details the development of a CoCrMo meta-biomaterial structure that facilitates personalised stiffness-matching while also exhibiting near-zero auxeticity. Using laser powder bed fusion, the porous architecture of the meta-biomaterial was characterised, showing potential for near-zero Poisson's ratio. The study also introduces a novel surrogate model that can predict the porosity (φ), yield strength (σy), elastic modulus (E), and negative Poisson's ratio (υ) of the meta-biomaterial, which was achieved through prototype testing and numerical modelling. The model was then used to inform a multi-criteria desirability objective, revealing an optimum near-zero υ of −0.037, with a targeted stiffness of 17.21 GPa. Parametric analysis of the meta-biomaterial showed that it exhibited υ, φ, σy and E values ranging from −0.02 to −0.08, 73.63–81.38%, 41–64 MPa, and 9.46–20.6 GPa, respectively. In this study, a surrogate model was developed for the purpose of generating personalised scenarios for the production of bone scaffolds. By utilising this model, it was possible to achieve near-zero υ and targeted stiffness personalisation. This breakthrough has significant implications for the field of bone tissue engineering and could pave the way for improved patient outcomes. The presented methodology is a powerful tool for the development of biomaterials and biomedical devices that can be 3D printed on demand for load-bearing tissue reconstruction. It has the potential to facilitate the creation of highly tailored and effective treatments for various conditions and injuries, ultimately enhancing patient outcomes.

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