RAISE: A Materials Science Gateway for X-ray Imaging and Modeling of Microstructures

RAISE：用于 X 射线成像和微结构建模的材料科学网关

• 批准号: 2037773
• 负责人: Jorge Vinals
• 金额: $ 99.32万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2037773&HistoricalAwards=false
• 关键词: RAISE; Materials; Science; Gateway; ray

Nontechnical SummaryThis award supports the development and deployment of a Science Gateway, a set of tools, computational materials-science models, and x-ray scattering data that are integrated and available through single web-based location. This project will facilitate the synergistic interaction of computational, and experimental research to accelerate progress on developing understanding of how materials deform, and in some cases fail, that will have impact on technological needs. Advances in the development of new structural materials with specified properties require improved diagnostics across a wide range of length and time scales. Examples of technological needs include: the development of high strength, low density metals that can be significantly deformed without rupturing or breaking for light weight applications in a vast variety of aerospace, power generation, and structural materials; the capability to make accurate predictions of residual stress and relaxation and recovery in additive manufacturing and metal forming; and reliability of interconnects in semiconductor chip technology. Advanced x-ray diffraction imaging from synchrotron facilities provides the necessary diagnostic information about the three-dimensional structure of complex materials with unprecedented resolution. Synchrotron facilities produce radiation, and of particular interest here, high energy x-rays, by accelerating electrons very close to the speed of light, capturing radiation that occurs from further acceleration by magnetic fields, and directing it to instrumentation that can perform experiments by scattering high energy x-rays off the atoms in materials. Instrumentation at the Cornell High Energy Synchrotron Source can perform advanced x-ray scattering experiments and provide high resolution data. Key aspects of the technique include being nondestructive in hard materials, and fast enough and of high enough resolution to observe structural changes at length scales below one micron in materials samples as they are subjected to thermal, mechanical, or other types of loading. Such unprecedented resolution results in the creation of very large datasets, uniquely rich in information, but difficult to mine and analyze, except by a very small number of experts. This is a significant bottleneck to progress. The Science Gateway is aimed to facilitate the mining and analysis of extremely large datasets by bringing together software engineers, data scientists, and disciplinary scientists. This is transformational in how Gateways are architected, and equally importantly, in how large experimental facilities are operated. The Gateway is designed to provide seamless access to new data being produced, to data reduction and reconstruction codes, and to modeling tools, all in a curated and user-friendly environment. The Gateway accelerates the feedback loop between data, tool creators, and tool users, and therefore the overall discovery process. It is also empowers investigators, by providing broad community access to data and sophisticated analysis tools no investigators who are not specialists in the techniques and technical areas that created them. The developments supported under this award may prove useful in developing Science Gateways to accelerate progress on other fundamental problems relevant to materials research. Technical SummaryThis award supports the development and deployment of a Science Gateway, a set of tools, computational materials-science models, and x-ray scattering data that are integrated and available through a single web-based location. It is well recognized that advances in the development of new structural materials with specified properties require improved diagnostics across all the relevant length and time scales. Examples of technological needs include: development of high strength, high ductility, low density metals for light weight applications in a vast variety of aerospace, power generation, and structural materials; accurate predictions of residual stress and relaxation and recovery in additive manufacturing and metal forming, for example in the automobile and defense industries; and improved reliability of interconnects in semiconductor chip technology. Advanced x-ray diffraction imaging at leading synchrotron facilities uniquely provides the necessary diagnostic information about the three-dimensional structure of complex materials with unprecedented resolution. Key aspects of the technique include being non-destructive in hard materials, and fast enough and of sufficient resolution to observe structural responses at the sub-micron scale in samples as they are subjected to thermal, mechanical, or other types of loading. Such unprecedented resolution comes with very large datasets, uniquely rich in information, but difficult to mine and analyze, except by a very small number of experts. This is a significant bottleneck to progress.This program develops an open cyberinfrastructure in the form of a public Science Gateway to serve the Cornell High Energy Synchrotron Source. The gateway is based on the Galaxy framework. Raw data is accumulated locally at the beam lines, and ingested into a Galaxy instance using standard web application programming interfaces. Data is typed, metadata is attached, and is made available through a shared data library. The gateway then provides the infrastructure for user defined transformations, including data reduction, image reconstruction, and feature analysis, while retaining metadata and provenance information. The gateway supports data transfer to XSEDE resources, as Galaxy natively orders individual codes according to category, and maps the execution of the designed workflows to the necessary resources without user awareness of their location. Workflows including visualization and modeling are also supported. The gateway is extensible by users of the facility and the broader community as new analysis and modeling tools are developed.The developments supported under this award may prove useful in developing Science Gateways to accelerate progress on other fundamental problems relevant to materials research.This project is jointly supported by the Office of Advanced Cyberinfrastructure in the Computer and Information Sciences Directorate, and the Division of Materials Research in the Mathematical and Physical Sciences Directorate.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该合同支持科学网关的开发和部署，该网关是一套工具、计算材料科学模型和x射线散射数据，可通过单一的网络位置进行集成和使用。该项目将促进计算和实验研究的协同作用，以加速对材料如何变形以及在某些情况下如何失效的理解的进展，这将对技术需求产生影响。在具有特定性能的新结构材料的发展中，需要在大范围的长度和时间尺度上改进诊断。技术需求的例子包括：开发高强度、低密度的金属，这种金属可以在不破裂或断裂的情况下显著变形，用于各种航空航天、发电和结构材料的轻质应用；在增材制造和金属成形中准确预测残余应力、松弛和恢复的能力；以及半导体芯片技术中互连的可靠性。来自同步加速器设施的先进x射线衍射成像以前所未有的分辨率提供了复杂材料三维结构的必要诊断信息。同步加速器设备产生辐射，这里特别有趣的是，高能x射线，通过将电子加速到非常接近光速，捕获由磁场进一步加速产生的辐射，并将其引导到可以通过将高能x射线从材料中的原子上散射出去进行实验的仪器中。康奈尔高能同步加速器源的仪器可以进行先进的x射线散射实验，并提供高分辨率的数据。该技术的关键方面包括对硬材料的无损性，以及足够快和足够高的分辨率，以便在材料样品受到热、机械或其他类型的载荷时，在小于一微米的长度尺度上观察结构变化。这种前所未有的分辨率导致了非常大的数据集的产生，这些数据集的信息非常丰富，但很难挖掘和分析，除非由极少数专家进行。这是进展的重大瓶颈。科学门户旨在通过将软件工程师、数据科学家和学科科学家聚集在一起，促进对超大数据集的挖掘和分析。这将改变网关的架构方式，同样重要的是，也将改变大型实验设施的运作方式。该网关旨在提供对正在生成的新数据、数据简化和重建代码以及建模工具的无缝访问，所有这些都在一个精心策划的用户友好环境中进行。Gateway加速了数据、工具创建者和工具用户之间的反馈循环，从而加速了整个发现过程。它还通过向广大社区提供数据和复杂的分析工具来授权调查人员，即使调查人员不是创建这些数据的技术和技术领域的专家。该奖项支持的发展可能有助于开发科学门户，以加速与材料研究相关的其他基本问题的进展。该合同支持科学网关的开发和部署，该网关是一套工具、计算材料科学模型和x射线散射数据，可通过一个基于web的位置进行集成和使用。众所周知，具有特定性能的新结构材料的发展需要在所有相关长度和时间尺度上改进诊断。技术需求的例子包括：开发高强度、高延展性、低密度的金属，用于各种各样的航空航天、发电和结构材料的轻质应用；准确预测增材制造和金属成形中的残余应力、松弛和恢复，例如在汽车和国防工业中；提高了半导体芯片技术互连的可靠性。先进的x射线衍射成像在领先的同步加速器设施独特地提供必要的诊断信息，以前所未有的分辨率复杂材料的三维结构。该技术的关键方面包括在硬材料中不具有破坏性，并且速度足够快，分辨率足够高，可以在样品受到热、机械或其他类型载荷时观察亚微米尺度的结构响应。这种前所未有的分辨率伴随着非常大的数据集，独特的信息丰富，但很难挖掘和分析，除非由极少数专家。这是进展的重大瓶颈。该计划以公共科学门户的形式开发一个开放的网络基础设施，以服务于康奈尔高能同步加速器源。网关基于Galaxy框架。原始数据在本地光束线上积累，并使用标准的web应用程序编程接口将其吸收到Galaxy实例中。输入数据，附加元数据，并通过共享数据库提供这些数据。然后，网关为用户定义的转换提供基础设施，包括数据缩减、图像重建和特征分析，同时保留元数据和来源信息。网关支持向XSEDE资源的数据传输，因为Galaxy根据类别本地订购单个代码，并将设计工作流的执行映射到必要的资源，而无需用户意识到它们的位置。工作流包括可视化和建模也被支持。随着新的分析和建模工具的开发，该网关可由设施用户和更广泛的社区进行扩展。该奖项支持的发展可能有助于开发科学门户，以加速与材料研究相关的其他基本问题的进展。该项目由计算机和信息科学理事会的先进网络基础设施办公室以及数学和物理科学理事会的材料研究部联合支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。