MM 44: Developement of Calculation Methods II
Mittwoch, 20. März 2024, 15:45–18:00, C 264
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15:45 |
MM 44.1 |
FAIR Data Quality Metrics in NOMAD — •Nathan Daelman, Joseph F. Rudzinski, José M. Pizarro, Luca M. Ghiringhelli, and Silvana Botti
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16:00 |
MM 44.2 |
Machine-learning interatomic potentials with beyond-DFT accuracy: application to covalent-organic frameworks — •Yuji Ikeda, Axel Forslund, and Blazej Grabowski
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16:15 |
MM 44.3 |
Kinetic Modeling of Stripes, Surfaces, and Solids Using the kmos3 Framework — •Martin Deimel, Aditya Savara, Karsten Reuter, and Sebastian Matera
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16:30 |
MM 44.4 |
Extracting Gibbs free energies from local composition fluctuations in atom probe data — Jianshu Zheng, Rüya Duran, Marvin Poul, Guido Schmitz, and •Sebastian Eich
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16:45 |
MM 44.5 |
Improving the Diversity of Transition State Searches with On-the-fly Learned Biasing Potentials — •Nils Gönnheimer, King Chun Lai, Karsten Reuter, and Johannes T. Margraf
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17:00 |
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15 min. break
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17:15 |
MM 44.6 |
Kernel Charge Equilibration: Machine Learned Interatomic Potentials With Full Long-Range Electrostatics — •Martin Vondrak, Johannes T. Margraf, and Karsten Reuter
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17:30 |
MM 44.7 |
Sampling-free computation of finite temperature material properties in isochoric and isobaric ensembles using the mean-field anharmonic bond model — •Raynol Dsouza, Marvin Poul, Liam Huber, Thomas D. Swinburne, and Jörg Neugebauer
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17:45 |
MM 44.8 |
Exploring Alternative Dispersion Corrections for the BEEF-vdW Functional — •Elisabeth Keller, Johannes T. Margraf, Volker Blum, and Karsten Reuter
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