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MM: Fachverband Metall- und Materialphysik

MM 6: Topical Session: Data Driven Materials Science - Materials Design II (joint session MM/CPP)

Montag, 16. März 2020, 11:45–13:00, BAR 205

11:45 MM 6.1 Versatile Bayesian deep-learning framework for crystal-structure recognition in single- and polycrystalline materials — •Andreas Leitherer, Angelo Ziletti, Matthias Scheffler, and Luca M. Ghiringhelli
12:00 MM 6.2 Parametrically Constrained Geometry Relaxations for High-Throughput Materials Science — •Maja-Olivia Lenz, Thomas A. R. Purcell, David Hicks, Stefano Curtarolo, Matthias Scheffler, and Christian Carbogno
12:15 MM 6.3 Combining ab-initio and data-guided approaches for refractory multi-principal element alloys design — •Yury Lysogorskiy, Alberto Ferrari, and Ralf Drautz
12:30 MM 6.4 Data-Efficient Machine Learning for Crystal Structure Prediction — •Simon Wengert, Gábor Csányi, Karsten Reuter, and Johannes T. Margraf
12:45 MM 6.5 Uncovering Anharmonicity in Material Space — •Thomas Purcell, Florian Knoop, Chuanqi Xu, Matthias Scheffler, Luca Ghiringhelli, and Christian Carbogno
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DPG-Physik > DPG-Verhandlungen > 2020 > Dresden