O 18: New methods: Theory – Poster
Monday, March 9, 2026, 18:00–20:00, P2
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18:00 |
O 18.1 |
Cost-Efficient Approach for Training MACE Potentials — •Antonia Gerstenberg, Thomas Bligaard, and Andreas Lynge Vishart
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18:00 |
O 18.2 |
The application of classical DFT for describing small molecules diffusion in porous materials. — •Mikhail Suetin and Michael te Vrugt
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18:00 |
O 18.3 |
Increasing the Transferability of Machine Learning Potentials by Learning Atomic Properties — •Johann Richard Springborn, Gunnar Schmitz, and Jörg Behler
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18:00 |
O 18.4 |
Radial Dirac-Fock solver using integral equation method — •Ernests Lazdans, Janis Užulis, and Andris Gulans
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18:00 |
O 18.5 |
Towards Efficient Time-Dependent Density-Functional Theory through Hubbard On- and Inter-Site Corrections — •Lydia Fichte, Karsten Reuter, and Matthias Kick
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18:00 |
O 18.6 |
Calculating surface energy using machine learning interatomic potentials — •Friedrich Neumann, Tom Barnowsky, Rico Friedrich, and Jens Kortus
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