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A6: Dynamic heterogeneities in coarse-grained and fine-grained models of liquid crystals and ionic liquids

While the connection between the length scales of simulation models with multiple levels of resolution is provided by the mapping scheme, the link between the different time scales is not known a priori. In this project, we address this problem for two systems exhibiting a range of time scales, namely smectic liquid crystals, and structural and dynamical heterogeneities of ionic liquids. We use dynamic rescaling and Markov state modelling (MSMs) to analyse the kinetic properties of coarse grained (CG) models. A newly developed concept of biasing MSMs helps us to identify sources of kinetic discrepancies and will be used to optimize CG force fields with respect to kinetics and transition barriers.


Effects of Silica Surfaces on the Structure and Dynamics of Room-Temperature Ionic Liquids: A Molecular Dynamics Simulation Study
Tamisra Pal, Constantin Beck, Dominik Lessnich, Michael Vogel
The Journal of Physical Chemistry C 122 (1), 624-634 (2017);
doi:10.1021/acs.jpcc.7b10567

Single molecule translocation in smectics illustrates the challenge for time-mapping in simulations on multiple scales
Biswaroop Mukherjee, Christine Peter, Kurt Kremer
The Journal of Chemical Physics 147 (11), 114501 (2017);
doi:10.1063/1.5001482

Role of Dynamic Heterogeneities in Ionic Liquids: Insights from All-Atom and Coarse-Grained Molecular Dynamics Simulation Studies
Tamisra Pal, Michael Vogel
ChemPhysChem 18 (16), 2233-2242 (2017);
doi:10.1002/cphc.201700504

Computational materials discovery in soft matter
T. Bereau, D. Andrienko, K. Kremer
APL Mat 4, 053101 (2016);
doi:10.1063/1.4943287

Soft matter embodies a wide range of materials, which all share the common characteristics of weak interaction energies determining their supramolecular structure. This complicates structure-property predictions and hampers the direct application of data-driven approaches to their modeling. We present several aspects in which these methods play a role in designing soft-matter materials: drug design as well as information-driven computer simulations, e.g., histogram reweighting. We also discuss recent examples of rational design of soft-matter materials fostered by physical insight and assisted by data-driven approaches. We foresee the combination of data-driven and physical approaches a promising strategy to move the field forward.

Concurrent parametrization against static and kinetic information leads to more robust coarse-grained force fields
J.F. Rudzinski, T. Bereau
The European Physical Journal Special Topics 225 (8-9), 1373-1389 (2016);
doi:10.1140/epjst/e2016-60114-5

Communication: Consistent interpretation of molecular simulation kinetics using Markov state models biased with external information
Joseph F. Rudzinski, Kurt Kremer, Tristan Bereau
The Journal of Chemical Physics 144 (5), 051102 (2016);
doi:10.1063/1.4941455

A molecular dynamics simulations study on the relations between dynamical heterogeneity, structural relaxation, and self-diffusion in viscous liquids
Patrick Henritzi, André Bormuth, Felix Klameth, Michael Vogel
The Journal of Chemical Physics 143 (16), 164502 (2015);
doi:10.1063/1.4933208

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