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

该奖项支持一个项目，该项目旨在建立一种新的计算模式和基础设施，为一种新兴的新仪器技术--原子探测断层扫描(APT)--增强三维(3-D)原子重建。该项目将极大地促进并行计算、计算几何和极大噪声数据集的图论应用方面的研究。APT是一种强大的显微镜工具，能够在亚纳米尺度上实现数亿个原子的空间分辨率。APT是唯一一台能够以原子分辨率绘制金属、半导体或绝缘体的三维组成图的仪器。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来可视化。独特的APT图像被转换为云数据点，为开发图论和微分几何技术提供了理想的模板，该技术允许(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。这项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，从而显著提高我们定量分析APT数据的能力。由于不确定性量化、复杂系统的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简化策略，动态考虑三维重建过程中的噪声数据，并高效地提取原子配位和径向分布函数，将原子级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用户社区和参与超大数据集建模和应用的计算科学界。VO最初将在爱荷华州立大学(ISU)托管，后来连接到NSF TeraGrid，以确保可持续和可访问的网络基础设施。教育和外联活动将包括(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计划，(3)为高中和一年级课程开发新型教材，展示数据挖掘和材料科学之间的联系-这将通过ISU的Science Bound计划进行课堂测试，该计划积极吸引来自代表性不足群体的学生；(4)将与ISU的NSF-Advance计划相联系的量化APT研讨会，以促进女性教员和其他代表不足的群体的参与；以及(5)利用基于我们的NSF国际材料研究所的国际合作。

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.