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MM: Fachverband Metall- und Materialphysik

MM 43: Data Driven Material Science: Big Data and Workflows V

Wednesday, March 20, 2024, 15:45–18:00, C 243

15:45 MM 43.1 The MALA Package - Transferable and Scalable Electronic Structure Simulations Powered by Machine Learning — •Lenz Fiedler and Attila Cangi
16:00 MM 43.2 A robust, simple and efficient algorithm to converge GW calculations — •Max Großmann, Malte Grunert, and Erich Runge
16:15 MM 43.3 FAIR Data Management for Computational Materials Science using NOMAD — •Luca M. Ghiringhelli, Joseph F. Rudzinski, José M. Pizarro, Nathan Daelman, and Silvana Botti
16:30 MM 43.4 A many-body framework for long-range interactions in atomistic machine learning — •Kevin Kazuki Huguenin-Dumittan, Philip Robin Loche, and Michele Ceriotti
16:45 MM 43.5 Automated prediction of Fermi surfaces from first principles — •Nataliya Paulish, Junfeng Qiao, and Giovanni Pizzi
  17:00 15 min. break
17:15 MM 43.6 Accurate and Efficient Protocols for High-Throughput Computational Materials Science — •Gabriel M. Nascimento, Flaviano José dos Santos, Marnik Bercx, Davide Grassano, Giovanni Pizzi, and Nicola Marzari
17:30 MM 43.7 Defect Phase Diagrams for Grain Boundaries in Mg: Automized workflows for chemical trends — •Prince Mathews, Rebecca Janisch, Jörg Neugebauer, and Tilmann Hickel
  17:45 MM 43.8 The contribution has been withdrawn.
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