High-throughput first-principles computational methods, such as density functional theory (DFT), offer the ability to predict the properties of materials, provided their crystal structures are known. However, there are many compounds for which the structure is unknown and, consequently, many potentially useful materials cannot be assessed by high-throughput DFT searches. Here, we demonstrate an automated tool to solve the structures of materials from powder diffraction patterns based on the first-principles-assisted structure solution (FPASS) method. We validate this tool by using it to solve 95 already-known crystal structures and find that FPASS can determine the correct structure in all cases. We then tuned FPASS to improve its performance on the most-difficult test cases, which include structures with larger numbers of symmetrically unique atoms. We also used FPASS to solve the structures of 10 materials and found, using DFT, several are interesting candidates for semiconductor applications.
ASJC Scopus subject areas
- Materials Science(all)
- Physics and Astronomy (miscellaneous)