MM 29: Data Driven Materials Science: Big Data and Work Flows – Electronic Structure
Mittwoch, 29. März 2023, 11:45–13:00, SCH A 251
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11:45 |
MM 29.1 |
Band Gap and Formation Energy Inference of Solids using Message Passing Neural Networks — •Tim Bechtel, Daniel Speckhard, and Claudia Draxl
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12:00 |
MM 29.2 |
Predicting electron density using a convolutional neural network — •Jae-Mo Lihm, Wanhee Lee, and Cheol-Hwan Park
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12:15 |
MM 29.3 |
Chemical ordering and magnetism in CrCoNi Medium Entropy Alloy — •Sheuly Ghosh, Vadim Sotskov, Alexander Shapeev, Jörg Neugebauer, and Fritz Körmann
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12:30 |
MM 29.4 |
Charge-dependent Atomic Cluster Expansion — •Matteo Rinaldi, Anton Bochkarev, Yury Lysogorskiy, Matous Mrovec, and Ralf Drautz
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12:45 |
MM 29.5 |
A machine-learned interatomic potential for silica and mixed silica-silicon systems — •Linus C. Erhard, Jochen Rohrer, Karsten Albe, and Volker L. Deringer
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