EAGER: Exploratory Research in Automated Computational Analysis of Inorganic Materials Libraries

Cornell University, Ithaca NY

Investigators

Abstract

Combinatorial Materials Science represents a potentially powerful approach to identifying new and unexpected materials. This involves the rapid, high-throughput synthesis, measurement, and analysis of a large number of different materials. Understanding the functional behavior of the materials requires a characterization of the structure-property relations. Crystalline structure information can be obtained through X-ray diffraction studies. An unsolved challenge is to develop automated techniques for identification of unique diffraction patterns and to cluster the resulting patterns into contiguous phase fields corresponding to regions with different material composite structures. Intellectual Merit: This exploratory project is aimed at establishing the feasibility of a unique interdisciplinary approach, involving a team of materials scientists and computer scientists, to address the challenge of structure (crystalline phase) identification of the composite materials. Specifically, the PIs propose to extract the key diffraction pattern features from the raw experimental data as a first step towards the development of computational methods for the identification of crystalline phases. Broader Impacts: The project, if successful, will establish the feasibility of a key first step in an overall methodology to significantly speed the materials scientific discovery process in general, and in the search for new materials for the next generation fuel-cell technology in particular. The project brings together faculty and students, providing training in materials science, engineering, and computer science.