Smart Manufacturing of Hybrid Materials with an Exceptional Combination of Strength and Toughness

具有卓越强度和韧性的混合材料的智能制造

• 批准号: 1537021
• 负责人: Xiaodong Li
• 金额: $ 34.87万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1537021&HistoricalAwards=false
• 关键词: Smart; Manufacturing; Hybrid; Materials; Exceptional

Traditional engineering materials frequently compromise strength for toughness, limiting the reliability and safety of many materials. A material that could break this paradigm would find applications in critical high loading environments where failure from either mode is not an option. Such a novel material could be used for medical implants with a smaller form factor, smaller and more precise surgical instrumentation, and even strengthen automotive and aircraft structures.  By combining high strength and high toughness properties, this material would fit into many existing applications and enable new engineering advances to across the medical, aerospace, automotive, and many other industries.  This award will support research to develop high strength, high toughness metallic materials, which mimic structures found in nature. This research has the potential to establish a new area of materials engineering and processing devoted to the discovery of similar hybrid materials and foster interest in related fields among university students and industry engineers.The objective of this research is to investigate smart manufacturing processes that employ shape memory alloys to transcribe the "J-curve" mechanical response and uniform molecular/atomic level deformation of the organic biopolymer in bio-inspired hybrid materials. The research approaches are to: (1) replicate nacre's architecture in engineering composites with shape memory alloy and intermetallic lamellae through eutectic solidification, (2) unveil the deformation mechanisms of individual lamellae by in-situ synchrotron high-energy X-ray diffraction and high resolution transmission electron microscopy mechanical testing, (3) uncover the load transfer mechanisms between shape memory alloy and intermetallic lamellae by mapping local strain fields with digital image correlation, and (4) establish a smart manufacturing strategy for a new class of high-performance, bio-inspired hybrid materials of exceptional mechanical prowess. The anticipated outcome will be the coupling of bio-inspired materials design strategies with smart manufacturing techniques to enable the discovery of material systems with exceptional properties and to enable their rapid insertion into existing manufacturing processes. This transformative research has the potential (1) to generate new paradigms of design, development, and implementation of smart manufacturing processes and (2) to accelerate the development and use of high performance, bio-inspired materials.

传统的工程材料经常为了韧性而牺牲强度，限制了许多材料的可靠性和安全性。可以打破这种范例的材料将在关键的高负载环境中找到应用，在这些环境中，任何一种模式的故障都是不可能的。这种新型材料可用于尺寸更小的医疗植入物、更小、更精确的手术器械，甚至可以增强汽车和飞机结构。  通过结合高强度和高韧性特性，这种材料将适合许多现有应用，并为医疗、航空航天、汽车和许多其他行业带来新的工程进步。  该奖项将支持开发高强度、高韧性金属材料的研究，这些材料模仿自然界中发现的结构。这项研究有可能建立一个新的材料工程和加工领域，致力于发现类似的混合材料，并培养大学生和行业工程师对相关领域的兴趣。这项研究的目的是研究智能制造工艺，利用形状记忆合金来记录仿生混合材料中有机生物聚合物的“J曲线”机械响应和均匀的分子/原子级变形。研究方法是：（1）通过共晶凝固在具有形状记忆合金和金属间薄片的工程复合材料中复制珍珠层的结构，（2）通过原位同步加速器高能X射线衍射和高分辨率透射电子显微镜机械测试揭示单个薄片的变形机制，（3）揭示形状记忆合金之间的载荷传递机制 通过数字图像相关映射局部应变场来绘制金属间层和金属间层，(4) 为具有卓越机械能力的新型高性能、仿生混合材料建立智能制造策略。预期的结果是将仿生材料设计策略与智能制造技术相结合，以发现具有特殊性能的材料系统，并使其能够快速插入现有的制造工艺中。这项变革性研究具有以下潜力：(1) 产生智能制造流程的设计、开发和实施的新范例；(2) 加速高性能仿生材料的开发和使用。