CIF21 DIBBs: EI: Data Laboratory for Materials Engineering

Suny At Buffalo, Amherst NY

Investigators

Abstract

This project directly addresses the goals of the Materials Genome Initiative -- to accelerate the pace of discovery and deployment of advanced material systems. To obtain insights for the discovery of new materials and to study existing materials, scientists and engineers rely heavily on an ever-growing number of materials research databases and scholarly research publications that date back many decades. New materials innovation often takes years, sometimes decades, to develop a new material. The project addresses the challenges through several steps, including automatic extraction of data from relevant electronic publications, storage of the data in formats that support comparison and analysis, development of advanced computational tools to improve the analysis, integration of the tools into a data laboratory to support the discovery of new trends and relationships among materials properties, and to predict new materials with desired properties. The infrastructure building blocks developed under this project enable researchers to (i) use document processing technologies to process scientific publications and data from scientific databases in materials science to create a knowledge base; (ii) use machine learning technologies to learn from the data in this enhanced knowledge base to address a variety of use cases in materials science and engineering; and (iii) use innovative information retrieval and visualization tools for insightful analysis, facilitating faster discovery of new materials. The tools will be hosted and disseminated through a web portal built on the HubZero platform, which will also provide users with the ability to query and visualize data, and run simulations and experiments. The data laboratory portal also provides the ability to run simulations and experiments on high-performance computing clusters using the building blocks. The data laboratory provides a platform for materials informatics, enabling prediction of properties of metal alloys and interaction with the materials discovery and engineering user community. While the primary target is the interdisciplinary field of materials research, the tools are designed to be domain agnostic as the core technologies can be applied to documents and databases across a broad swath of disciplines to enhance the pace of scientific discoveries. This award by the Advanced Cyberinfrastructure Division is jointly supported by the NSF Directorate for Mathematical & Physical Sciences (Division of Materials Research).