TY - CONF A1 - George, Janine T1 - Data-driven chemical understanding N2 - Chemical heuristics are essential to understanding molecules and materials in chemistry. The periodic table, atomic radii, and electronegativities are only a few examples. Initially, they have been developed by a combination of physical insight and a limited amount of data. It is now possible to test these heuristics and generate new ones using automation based on Materials Informatic tools like pymatgen and greater amounts of data from databases such as a Materials Project. In this session, I'll speak about heuristics and design rules based on coordination environments and the concept of chemical bonding. For example, we have tested the Pauling rules which describe the stability of materials based on coordination environments and their connections on 5000 oxides from the Materials Project. In addition, we have created automated processes for analyzing the chemical bonding situation in crystalline materials with Lobster (www.cohp.de) in order to discover new heuristics and design rules. T2 - Materials Project Seminar Series CY - Online meeting DA - 18.05.2022 KW - DFT KW - Chemical heuristics KW - Crystal Orbital Hamilton Populations KW - Machine learning KW - Phonons PY - 2022 UR - https://www.youtube.com/watch?v=e7zYrz6fgog UR - https://next-gen.materialsproject.org/community/seminar AN - OPUS4-55008 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -