This award, with support from the Division of Materials Research, the Division of Mathematical Sciences and the Office of Multidisciplinary Activities, sponsors the organization of a "data science hackathon" for researchers in the fields of solid-state materials chemistry and data science. This event, SSMCDAT2020, bring together members from these fields to further science through data-intensive research in order to make advances toward solving challenging problems relevant to solid-state materials chemistry. Teams work together for a three-day event, working both as teams and as a large cohort on a set of research projects. The hackathon lays a foundation for long-lasting collaborations between materials and data scientists.
The Materials Genome Initiative (MGI) was introduced in 2011 with the goal of developing and deploying new materials at twice the speed and a fraction of the cost. Key tenets of the initiative are the ideas that (a) materials "genes" exist and skilled manipulation of the materials "genome" will lead to rapid discovery and deployment of advanced materials, and (b) experimental materials research has been far too costly and slow to be the primary vehicle for exploration and discovery. For these reasons, the MGI proposes that investigations should be minimized by judicious use of computational materials science. The development of such computational techniques has transformed the field, but unlocking the materials genome still faces major challenges. To address these challenges, this solid-state materials chemistry-focused "hackathon" is designed to broaden the approach laid out in the MGI to encompass the rapidly evolving field of data science. Indeed, early adopters of this approach have amassed numerous impressive proofs of concept. With strong partnerships between solid-state materials chemistry and data science researchers, significant advances toward accomplishing the goals of the MGI can be achieved.
This "data science hackathon" is a fundamentally interdisciplinary endeavor. Solid-state materials chemistry researchers are trained in the application of data science tools, becoming informed of the advantages and limitations of various approaches. Data scientists are exposed to the breadth of materials data available, as well as the most pressing solid-state materials research challenges. Special attention is paid to have participation from promising graduate students and postdocs, as well as under-represented groups.
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.
