SGER: Automated Reflection Laue and Serial Sectioning Characterization of Magnetic and Martensitic Materials

SGER：磁性和马氏体材料的自动反射劳厄和连续切片表征

• 批准号: 0809048
• 负责人: Marc De Graef
• 金额: $ 20万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0809048&HistoricalAwards=false
• 关键词: SGER; Automated; Reflection; Laue; Serial

TECHNICAL: The microstructure of materials is intimately connected to multiple material properties (mechanical, electrical, magnetic, etc.). To fully understand the important aspects of a microstructure, it is often necessary to obtain three-dimensional structural and chemical information about grain boundaries, second phase particles, large scale defects, and so on. One of the primary ways of obtaining this kind of information is through the process of serial sectioning. Recent advances in robot technology now make it possible to completely transfer the human tasks of metallography to a robotized setup, which is more precise and can work around the clock. In the PIs laboratory, a robotized metallography instrument will be installed in the early Spring of 2008; this device generates optical serial section images or montages for material volumes of around a cubic millimeter, far larger than any of the more conventional serial sectioning methods, such as focused ion beam milling. In this high-risk, high payoff, and transformative SGER program, PI will augment this instrument with a refection Laue camera, develop automated indexing software, and integrate the diffractometer into the RoboMet.3D control hardware. In the first year of the program, PI will implement the indexing algorithms, and in the second year PI will apply the technique to determine the 3D microstructures of magnetic materials and materials that exhibit martensitic transformations. There is very little 3D information available on either of these material classes, and PI will acquire data sets that will enable subsequent numerical analysis of their macroscopic material properties. Material systems investigated will include Fe-3% Si transformer steel (in which the problem of abnormal grain growth is still poorly understood), Cu-Al-based martensitic alloys (which exhibit the shape memory, etc.), and also the Ni2MnGa system, which is a ferromagnetic shape memory alloy (i.e., it exhibits both magnetism and a martensitic transformation). The simultaneous acquisition of optical images and orientation data (through the indexing of Laue patterns) for material volumes of the order of cubic millimeters will enable the detailed study of materials that thus far have not been studied in 3D. The research will create the tools to routinely obtain this kind of microstructural information, and will also apply the method to several important engineering materials. In the long run, this instrument has the capability to transform the way we look at materials; it will help us change our usual 2D view of a microstructure (from optical or electron micrographs) to a truly 3D understanding of real-world microstructures. NON-TECHNICAL: The development of a fully automated device capable of both serial section imaging and orientational data acquisition has the potential to impact a large portion of the materials community. In the short term, the program may lead to a more widespread commercial availability of this new instrument. This will have an immediate effect on materials education, since the 3D visualizations of microstructures acquired on this instrument can be incorporated directly into courses and textbooks, thereby making 3D metallography for the future generation of materials engineers as basic a tool as 2D metallography has been in the past.

技术：材料的微观结构与多种材料特性（机械、电、磁等）密切相关。为了充分了解微观结构的重要方面，通常需要获得有关晶界、第二相颗粒、大尺度缺陷等的三维结构和化学信息。获得此类信息的主要方法之一是通过连续切片过程。机器人技术的最新进展现在可以将金相学的人类任务完全转移到机器人化的设置中，这更精确，可以全天候工作。在PIs实验室中，将于2008年早春安装一台机器人金相仪器;该设备为大约一立方毫米的材料体积生成光学连续切片图像或蒙太奇，远远大于任何传统的连续切片方法，例如聚焦离子束铣削。在这个高风险、高回报和变革性的SGER项目中，PI将用反射劳厄相机增强该仪器，开发自动化索引软件，并将衍射仪集成到RoboMet.3D控制硬件中。在该计划的第一年，PI将实施索引算法，并在第二年PI将应用该技术来确定磁性材料和表现出马氏体相变的材料的3D微观结构。这两种材料的3D信息都非常少，PI将获取数据集，以便随后对其宏观材料特性进行数值分析。研究的材料系统将包括Fe-3% Si Transformer钢（其中异常晶粒生长的问题仍然知之甚少）、Cu-Al基马氏体合金（其表现出形状记忆等）、以及Ni 2 MnGa系统，其是铁磁形状记忆合金（即，它表现出磁性和马氏体转变）。同时采集立方毫米量级材料体积的光学图像和取向数据（通过劳厄图案的索引）将使迄今为止尚未在3D中研究的材料的详细研究成为可能。该研究将创建常规获取这种微观结构信息的工具，并将该方法应用于几种重要的工程材料。从长远来看，该仪器有能力改变我们看待材料的方式;它将帮助我们将通常的微观结构的2D视图（从光学或电子显微镜）转变为对真实世界微观结构的真正3D理解。非技术性：开发一种能够同时进行连续切片成像和定向数据采集的全自动设备，有可能影响材料界的很大一部分。在短期内，该计划可能会导致这种新仪器的更广泛的商业可用性。这将对材料教育产生直接影响，因为在该仪器上获得的微观结构的3D可视化可以直接纳入课程和教科书中，从而使未来一代材料工程师的3D金相学成为过去2D金相学的基本工具。