Poster: Towards Automated Materials Properties Searches Using Large Tight-Binding Databases

Many high-temperature superconducting materials are characterized by high density of states (DOS) near the Fermi level and strong magnetic fluctuations. In this project we developed Python code to fetch tight-binding parameters from the Jarvis materials database (https://jarvis.nist.gov/) and then calculate the DOS and bare magnetic susceptibility. Using these calculations, we hope to identify potential candidate materials, either in their pure or doped forms, having desired properties such as superconductivity or magnetism. The standardized tight-binding format used in the Jarvis database, which is derived from the Wannier-90 project (https://wannier.org), enables rapid searches through the Jarvis database and provides a demonstration for accelerating research in materials physics through standards-based modeling and simulation.