DMREF: Design Knowledge Base of Low-Modulus Titanium Alloys for Biomedical Applications

设计材料革新和设计我们的未来(DMREF)项目的研究目标是建立一个基本的知识库，以便能够加速设计用于生物医学假体设备的先进的低模数(20-30 Gpa，与骨骼匹配)钛合金。该小组将：1)使用第一性原理计算来预测Ti-Mo-Nb-Ta-Zr系统的弹性模数和热力学相稳定性；2)使用高通量扩散倍数和微米分辨率的材料性质测量工具来获得大量的材料性质数据；3)建立CALPHAD类型的5组分系统的热力学和弹性模数数据库；以及4)使用直接激光沉积来验证模型预测。与基于单个合金的传统方法相比，这些计算和实验工具的集成将使建立成分-结构-性质关系的效率提高数倍，从而从根本上改变未来材料数据库的建立方式。随着人口老龄化和寿命的延长，需要越来越多的生物医学假体设备，如膝关节和髋关节置换，以维持积极的生活方式。生物相容性钛合金被认为是此类植入物的最佳选择之一。能够定制成分和微观结构以设计合金以满足特定的性能要求是材料基因组倡议(MGI)的总体目标，尤其是本研究的目的。本文开发的方法将大大加快快速建立数字材料属性数据库的数据生成速度，以加速新材料的设计。高性能材料的及时设计对美国制造业的全球竞争力至关重要。这项研究产生的所有数字数据将在MGI信息学基础设施中发布和存档。该项目将培养下一代材料工程师，他们将掌握先进的计算和实验方法，以更好地服务于社会。这项研究的研究和教育还将有助于引入一种新的材料创新范式，即通过预先模拟进行材料设计，然后进行关键的验证实验，而不是目前基于实验迭代然后机械表征的方法。

The research objective of this Designing Materials to Revolutionize and Engineer our Future (DMREF) project is to establish a fundamental knowledge base to enable accelerated design of advanced low-modulus (20-30 GPa to match that of bone) Ti alloys for biomedical prosthetic devices. The team will: 1) employ first-principles calculations to predict elastic modulus and thermodynamic phase stability of the Ti-Mo-Nb-Ta-Zr system; 2) use high-throughput diffusion multiples and micron resolution materials property measurement tools to obtain large amount of materials property data; 3) establish CALPHAD-type databases of thermodynamics and elastic modulus for the 5-component system; and 4) employ direct laser deposition to validate model predictions. Integration of these computational and experimental tools will achieve a multifold increase in the efficiency of establishing composition-structure-property relationships in comparison with traditional methods based on individual alloys, and thus will fundamentally change the way future materials databases are established.An aging population with an extended lifespan is demanding more and more biomedical prosthetic devices, such as knee and hip replacements, to sustain an active lifestyle. Biocompatible Ti alloys are considered to be one of the best options for such implants. The ability to tailor the composition and microstructure to design alloys to meet specific property requirements is the goal of the Materials Genome Initiative (MGI) in general and the purpose of this study in particular. The approach developed here will significantly speed up data generation for rapid establishment of digital materials property databases for accelerated design of new materials. The timely design of high-performance materials is critical to the global competitiveness of US manufacturing. All digital data generated from this study will be published and archived in the MGI informatics infrastructure. This project will educate next-generation materials engineers who will master both advanced computational and experimental approaches to better serve the society. The research and education of this study will also help usher in a new paradigm of materials innovation where materials design is conducted by up-front simulations followed by key validation experiments in contrast to the current approach that is based on experimental iterations followed by mechanistic characterization.