TY - CONF A1 - George, Janine T1 - High-throughput Computational Screening N2 - I provided a tutorial lecture on high-throughput DFT calculations in combination with heuristics, machine learning and workflows. I started with the introduction of the software infrastructure. Then, I showed applications for phonon predictions, magnetism and synthesizability prediction. T2 - Machine Learning for Materials 2025 CY - Karlsruhe, Germany DA - 08.09.2025 KW - Materials Design KW - Automation KW - High-throughput KW - Magnetism KW - Thermal conductivity PY - 2025 AN - OPUS4-64074 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - George, Janine T1 - DFT-based Phonon-computations for "Considering the Role of Ion Transport in Diffuson-Dominated Thermal Conductivity" N2 - These are the harmonic phonon and Grüneisen parameter computations for the publication "Considering the Role of Ion Transport in Diffuson-Dominated Thermal Conductivity" (https://doi.org/10.1002/aenm.202200717). VASP and Phonopy outputs are included in this data set. KW - Thermal conductivity KW - Phonons PY - 2021 DO - https://doi.org/10.5281/zenodo.5116360 PB - Zenodo CY - Geneva AN - OPUS4-55168 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - Automated Bonding Analysis with LobSTER and ATOMATE2 N2 - The talk introduced automated bonding analysis with the programs LobsterPy and atomate2. I especially emphasized how bonding descriptors can be used for materials design. T2 - Lobster Bonding Analysis School CY - Berlin, Germany DA - 11.06.2025 KW - Automation KW - Bonding Analysis KW - Materials Design KW - High throughput KW - Ab initio KW - Thermal conductivity PY - 2025 AN - OPUS4-63420 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - George, Janine T1 - Lobster workflow and applications N2 - This talk introduced bonding analysis to the participants of the school including several examples of its usefulness. Additionally, I talked in detail about the workflows related to bonding analysis within the atomate2 workflow library. I then showed how the workflow was applied to build a very large bonding data database that can now be used for machine learning of materials properties. T2 - "Automated ab initio workflows with Jobflow and Atomate2" CECAM Flagship school CY - Lausanne, Switzerland DA - 17.03.2025 KW - Automation KW - Materials design KW - Machine learning KW - Thermal conductivity KW - Inorganic materials KW - High-throughput PY - 2025 AN - OPUS4-62948 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -