CDI-Type II: Dimensionality-Reduction and Reconstruction Tools for Atom Probe Tomography

CDI-Type II：原子探针断层扫描的降维和重建工具

• 批准号: 0941576
• 负责人: Krishna Rajan
• 金额: $ 95.29万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0941576&HistoricalAwards=false
• 关键词: CDI; Type; II; Dimensionality; Reduction

This award supports a project to establish a new computational paradigm and infrastructure that will enhance three-dimensional (3-D) atomic reconstruction for an emerging new instrumentation technology; atom probe tomography (APT). The project will significantly advance research in parallel computing, computational geometry and graph-theoretic applications of extremely large and noisy data sets. APT is a powerful microscopy tool that enables spatial resolution of hundreds of millions of atoms at the sub-nanoscale. The APT is the only instrument capable of mapping the 3-D composition of a metal, semiconductor, or an insulator with atomic resolution. The 3-D reconstruction of this direct space information provides unprecedented capabilities for characterizing materials at the atomic level. The quantitative analysis of APT images could provide the ability to directly observe and interpret atomistic scale solid state phenomena that until now, have only been visualized via modeling and computer simulation. The unique APT images, transformed as cloud data points, provide an ideal template for developing graphtheoretic and differential geometric techniques that allow (1) assimilation of dynamic, noisy and/or incomplete data during reconstruction, (2) development of parallel algorithms for 3D reconstruction, and (3) extraction of multi-scale geometric features and statistics from the 3D data. This research will yield new computational tools and algorithms that can effectively utilize computing platforms for noise insensitive reconstruction, which can significantly improve our abilities to quantitatively analyze APT data. These advancements will be possible due to developments in uncertainty quantification, model reduction of complex systems, and scalable algorithms. Data-driven model reduction strategies that dynamically account for the noisy data during the 3D reconstruction and efficiently extract atomic coordination and radial distribution functions will be developed to directly link atomic-scale structure and chemical data with materials properties and behavior.A virtual organization (VO) will be established, targeting the rapidly growing global community of APT users and the computational sciences community that is involved in modeling and applications of very large data sets. The VO will be initially hosted at Iowa State University (ISU) and later linked to the NSF TeraGrid to ensure a sustainable and accessible cyberinfrastructure. Educational and outreach activities will include (1) interdepartmental graduate courses on computational nanosciences, (2) summer research programs on data mining and parallel computing for undergraduate students , (3) development of novel teaching materials for high school and first-year courses that demonstrate the connections between data mining and materials science --- this will be class tested through ISU's Science Bound program, which actively engages students from underrepresented groups; (4) workshops on quantitative APT that will be linked to ISU's NSF-ADVANCE program to promote participation by women faculty and other under-represented groups; and (5) leverage international collaborations based on our NSF International Materials Institute.

该奖项支持建立新的计算范式和基础设施的项目，该项目将增强新兴仪器技术的三维（3-D）原子重建；原子探针断层扫描（APT）。该项目将显著推进并行计算、计算几何和超大噪声数据集的图论应用研究。APT是一个强大的显微镜工具，可以在亚纳米尺度上实现数亿个原子的空间分辨率。APT是唯一能够以原子分辨率绘制金属、半导体或绝缘体的三维成分的仪器。这种直接空间信息的三维重建为在原子水平上表征材料提供了前所未有的能力。APT图像的定量分析可以提供直接观察和解释原子尺度固体现象的能力，到目前为止，这些现象只能通过建模和计算机模拟进行可视化。独特的APT图像转换为云数据点，为开发图论和微分几何技术提供了理想的模板，这些技术允许(1)在重建过程中同化动态、噪声和/或不完整的数据，(2)开发用于3D重建的并行算法，以及(3)从3D数据中提取多尺度几何特征和统计数据。本研究将产生新的计算工具和算法，可以有效地利用计算平台进行噪声不敏感重建，这将显著提高我们定量分析APT数据的能力。由于不确定性量化、复杂系统模型简化和可扩展算法的发展，这些进步将成为可能。将开发数据驱动的模型约简策略，动态地解释三维重建过程中的噪声数据，并有效地提取原子配位和径向分布函数，将原子尺度结构和化学数据与材料的性质和行为直接联系起来。将建立一个虚拟组织（VO），目标是快速增长的全球APT用户社区和涉及超大型数据集建模和应用的计算科学社区。VO最初将在爱荷华州立大学（ISU）托管，随后与NSF TeraGrid连接，以确保可持续和可访问的网络基础设施。教育和推广活动将包括(1)计算纳米科学的跨部门研究生课程，(2)面向本科生的数据挖掘和并行计算暑期研究项目，(3)为高中和一年级课程开发新颖的教材，展示数据挖掘和材料科学之间的联系——这将通过ISU的科学绑定项目进行课堂测试。积极吸引来自弱势群体的学生；(4)定量APT研讨会，将与ISU的NSF-ADVANCE计划联系起来，以促进女性教师和其他代表性不足的群体的参与；(5)利用我们的NSF国际材料研究所的国际合作。