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Regensburg 2022 – wissenschaftliches Programm

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MM: Fachverband Metall- und Materialphysik

MM 25: Data Driven Materials Science: Computational Frameworks / Chemical Complexity

Mittwoch, 7. September 2022, 15:45–18:30, H46

15:45 MM 25.1 Topical Talk: Automated atomistic calculation of thermodynamic and thermophysical data — •Jan Janssen, Tilmann Hickel, and Jörg Neugebauer
16:15 MM 25.2 Efficient parameterization of the atomic cluster expansion — •Anton Bochkarev, Yury Lysogorskiy, Matous Mrovec, and Ralf Drautz
16:30 MM 25.3 Atomic cluster expansion: a universal machine learning potential for magnesium — •Eslam Ibrahim, Yury Lysogorskiy, Matous Mrovec, and Ralf Drautz
16:45 MM 25.4 Learning design rules for selective oxidation catalysts from high-throughput experimentation and artificial intelligence — •Lucas Foppa, Christopher Sutton, Luca M. Ghiringhelli, Sandip De, Patricia Löser, Stephan Schunk, Ansgar Schäfer, and Matthias Scheffler
  17:00 15 min. break
17:15 MM 25.5 Topical Talk: Understanding Dislocation Flow and Avalanches in High Entropy Alloys by Machine Learning-based Data Mining of In-Situ TEM Experiments — •Stefan Sandfeld
17:45 MM 25.6 Phase stability and short range order in CrCoNi medium entropy alloy — •Sheuly Ghosh, Vadim Sotskov, Alexander Shapeev, Fritz Koermann, and Joerg Neugebauer
  18:00 MM 25.7 The contribution has been withdrawn.
18:15 MM 25.8 Databases for Machine Learning of Grain Boundary Segregation — •Alexander Reichmann, Christoph Dösinger, Daniel Scheiber, Oleg Peil, Vsevolod Razumovskiy, and Lorenz Romaner
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