This 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.
This 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.
