Berlin 2024 –
wissenschaftliches Programm
CPP 23: Modeling and Simulation of Soft Matter III
Mittwoch, 20. März 2024, 09:30–11:15, H 0107
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09:30 |
CPP 23.1 |
FAIR Data Management for Soft Matter Simulations using NOMAD — •Joseph F. Rudzinski, José M. Pizarro, Nathan Daelman, Luca M. Ghiringhelli, and Silvana Botti
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09:45 |
CPP 23.2 |
Symmetry-adapted polarization learning for vibrational spectroscopy — •David Wilkins
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10:00 |
CPP 23.3 |
Vibrational Spectroscopy from Machine Learning Molecular Dynamics by Accurately Representing the Atomic Polar Tensor — •Philipp Schienbein
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10:15 |
CPP 23.4 |
Efficient construction of high-dimensional neural network potentials for the Strecker synthesis — •Alea Miako Tokita, Timothée Devergne, A Marco Saitta, and Jörg Behler
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10:30 |
CPP 23.5 |
Machine learning of an implicit solvent for dynamic Monte Carlo simulations — Ankush Checkervarty, Jens-Uwe Sommer, and •Marco Werner
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10:45 |
CPP 23.6 |
Long-Range Descriptors in Atomistic Modeling beyond Electrostatics — •Philip Loche, Kevin Kazuki Huguenin-Dumittan, and Michele Ceriotti
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11:00 |
CPP 23.7 |
Encapsulation Of Pt-based Clusters In ZIF-8: Insights From First Principles Simulations — •poonam p, kathrin l. kollmannsberger, waldemar kaiser, julien warnan, roland a. fischer, and alessio gagliardi
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