CDI Type I: Collaborative research: Materials Informatics: Computational tools for discovery and design

University Of Minnesota-Twin Cities, Minneapolis MN

Investigators

Abstract

This award is made on a proposal submitted to the Cyberenabled Discovery and Innovation initiative. The goal of this CDI project is to explore new, transformative strategies that will exploit recent advances in quantum modeling algorithms and software, data mining techniques, and high-performance hardware, for the discovery and design of materials for a wide variety of applications. While the number of experimentally known binary materials is fairly complete, of the roughly 160,000 possible ternary materials only about 5% are known and of the possible 4 million quaternary materials less than 1% are known. The potential for finding a new material in this realm is great, e.g., a superhard material, a new catalytic material, or an efficient photovoltaic material could be residing in this set of unexplored materials. An efficient search for special materials in this myriad of possible combinations is a daunting task. Successful searching procedures combined with effective computational methods to evaluate the properties of a candidate material could have a tremendous impact as theoretical methods for materials discovery challenge experimental ones. Materials scientists would be able to examine postulated materials on a routine basis and predict their properties without resort to experiment. Synthesis of novel materials would be greatly enhanced. The research will implement methods in the category of materials informatics. The focus will be on combining data mining with quantum mechanical methods for computing properties of materials to address "grand challenge" problems such as how to engineer semiconductors with desired electronic properties, thermoelectricity, and catalysis. The cross-disciplinary theme of the proposed work will rely on the expertise of the PIs in three main areas that are vital to its success: materials science, data mining, and high-performance computing. This award supports the PIs' commitment to a vigorous program of attracting underrepresented groups. Owing to the relatively new approach of informatics applied to materials, it is imperative to train students and researchers in both data mining and quantum modeling. The PIs' activities will center on the following efforts: Alice in Wonderland Program. This teaching activity will involve an active effort to recruit members of underrepresented groups at the high school level to participate in materials research activities. The Alice in Wonderland program is coordinated at the University of Texas. The goal of this program is to attract female high school students to physics, materials science or chemical engineering by involving them in research over the summer before they make decisions about colleges. The high school students attend a short course given at the start of the program by graduate students and work in research labs under the mentorship of the PIs. Summer Undergraduate Interns. Under prior NSF support, the PIs initiated a program with the Minnesota Supercomputing Institute to recruit undergraduate interns interested in high performance computing for summer internships. The interns will be located at the University of Minnesota and will participate in this project?s research activities. Graduate Education and Training. The number of multidisciplinary efforts which focus on problems in the materials has increased at a rapid pace in recent years. At the same time, the number of students who receive training on the effective use of informatics software for materials is small. To address this issue, the PIs will design new courses, outside of the current curriculum, to meet this need and train graduate students in this new field. Students will exchange mentors between the PIs to ensure that each will have a knowledge of informatics and materials modeling.