CPP 9: Modeling and Simulation of Soft Matter (joint session CPP/DY)
Montag, 5. September 2022, 15:00–17:45, H39
 |
15:00 |
CPP 9.1 |
Machine Learning of consistent thermodynamic models using automatic differentiation — •David Rosenberger, Kipton Barros, Timothy Germann, and Nicholas Lubbers
|
|
|
|
15:15 |
CPP 9.2 |
Atomistic Machine Learning for Aqueous Ionic Solutions — •Philip Loche, Kevin K. Huguenin-Dumittan, and Michele Ceriotti
|
|
|
|
15:30 |
CPP 9.3 |
Identification of glass transition temperature for polymer melts using data-driven methods — •Atreyee Banerjee, Hsiao-ping Hsu, Oleksandra Kukharenko, and Kurt Kremer
|
|
|
|
15:45 |
CPP 9.4 |
Systematic parametrization of non-Markovian dissipative thermostats for coarse-grained molecular simulations with accurate dynamics — •Viktor Klippenstein and Nico F. A. Van Der Vegt
|
|
|
| |
16:00 |
CPP 9.5 |
The contribution has been withdrawn.
|
|
|
|
16:15 |
CPP 9.6 |
Modulating internal transition kinetics of responsive macromolecules by collective crowding — •Nils Göth, Upayan Baul, Michael Bley, and Joachim Dzubiella
|
|
|
| |
16:30 |
|
15 min. break
|
|
|
|
16:45 |
CPP 9.7 |
Modelling process-structure-properties of polymer nanocomposites — •Janett Prehl, Constantin Huster, and Karl Heinz Hoffmann
|
|
|
|
17:00 |
CPP 9.8 |
A cosolvent surfactant mechanism affects polymer collapse in miscible good solvents — •Swaminath Bharadwaj, Divya Nayar, Cahit Dalgicdir, and Nico van der Vegt
|
|
|
|
17:15 |
CPP 9.9 |
Water transport in soft nanoporous materials: Impact of mechanical response on dynamics, slippage and permeance — •Alexander Schlaich, Matthieu Vandamme, Marie Plazanet, and Benoit Coasne
|
|
|
|
17:30 |
CPP 9.10 |
Solvation structure of polymer cathodes for Li/S batteries — •Diptesh Gayen, Yannik Schuetze, Sebastien Groh, and Joachim Dzubiella
|
|
|
