Towards a Crystalline Organic Superconductor Database

A database of layered organic crystalline materials containing structural information, experimentally determined properties, and electronic band structure is proposed. Layered organic crystals have a rich electronic phase diagram and exhibit numerous electronic ground states including traditional and unconventional superconductivity, charge and spin density waves, Dirac points, and spin liquid states. The proposed database will be a versatile tool for scientists studying quantum materials and will pave the way towards new discoveries and materials via machine learning methods. We will present a computer algorithm for analyzing the crystal structure of layered organic crystals and storing the extracted structure parameters in the database. The algorithm analyzes molecular conformation, dimerization, packing types, and intermolecular interactions of cations that form the conductive layer of these materials. We will discuss the challenges of inputting experimentally determined material properties from scientific articles into the database, and the best methods to do it. We will also show a Python based system for automatically initializing, executing, and analyzing WIEN2k DFT calculations for materials in the database.