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CPP 18: Topical Session: Data Driven Materials Science - Materials Design II (joint session MM/CPP)
Monday, March 16, 2020, 11:45–13:00, BAR 205
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11:45 |
CPP 18.1 |
Versatile Bayesian deep-learning framework for crystal-structure recognition in single- and polycrystalline materials — •Andreas Leitherer, Angelo Ziletti, Matthias Scheffler, and Luca M. Ghiringhelli
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12:00 |
CPP 18.2 |
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
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12:15 |
CPP 18.3 |
Combining ab-initio and data-guided approaches for refractory multi-principal element alloys design — •Yury Lysogorskiy, Alberto Ferrari, and Ralf Drautz
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12:30 |
CPP 18.4 |
Data-Efficient Machine Learning for Crystal Structure Prediction — •Simon Wengert, Gábor Csányi, Karsten Reuter, and Johannes T. Margraf
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12:45 |
CPP 18.5 |
Uncovering Anharmonicity in Material Space — •Thomas Purcell, Florian Knoop, Chuanqi Xu, Matthias Scheffler, Luca Ghiringhelli, and Christian Carbogno
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