B2: Vielkörpereffekte und optimierte Abbildungs-Verfahren für systematisches Vergröbern

Ultra-coarse-graining of homopolymers in inhomogeneous systems
Fabian Berressem, Christoph Scherer, Denis Andrienko, Arash Nikoubashman
Journal of Physics: Condensed Matter 33 (25), 254002 (2021);
doi:10.1088/1361-648x/abf6e2

Computing inelastic neutron scattering spectra from molecular dynamics trajectories
Thomas F. Harrelson, Makena Dettmann, Christoph Scherer, Denis Andrienko, Adam J. Moulé, Roland Faller
Scientific Reports 11 (1), (2021);
doi:10.1038/s41598-021-86771-5

Ultra-coarse-graining of homopolymers in inhomogeneous systems
F. Berressem, C. Scherer, D. Andrienko and A. Nikoubashman
J. Phys.: Condens. Matter, (2021);

BoltzmaNN: Predicting effective pair potentials and equations of state using neural networks
F. Berressem and A. Nikoubashman
J. Chem. Phys. 154, 124123 (2021);
URL: https://aip.scitation.org/doi/10.1063/5.0045441
doi:10.1063/5.0045441

Kernel-Based Machine Learning for Efficient Simulations of Molecular Liquids
Christoph Scherer, René Scheid, Denis Andrienko, Tristan Bereau
Journal of Chemical Theory and Computation 16 (5), 3194-3204 (2020);
doi:10.1021/acs.jctc.9b01256

Understanding three-body contributions to coarse-grained force fields
Christoph Scherer, Denis Andrienko
Physical Chemistry Chemical Physics 20 (34), 22387-22394 (2018);
URL: http://dx.doi.org/10.1039/C8CP00746B
doi:10.1039/c8cp00746b

The PCPDTBT Family: Correlations between Chemical Structure, Polymorphism, and Device Performance
G. L. Schulz, F. S. U. Fischer, D. Trefz, A. Melnyk, A. Hamidi-Sakr, M. Brinkmann, D. Andrienko, S. Ludwigs
Macromolecules 50 (4), 1402-1414 (2017);
doi:10.1021/acs.macromol.6b01698

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

↓ Abstract anzeigen↑ Abstract ausblenden 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.

Comparison of systematic coarse-graining strategies for soluble conjugated polymers
Christoph Scherer and Denis Andrienko
Eur. Phys. J. Spec. Top. 225, 1441-1461, (2016);
doi:10.1140/epjst/e2016-60154-9

↓ Abstract anzeigen↑ Abstract ausblenden We assess several systematic coarse-graining approaches by coarse-graining poly(3-hexylthiophene-2,5-diyl) (P3HT), a polymer showing π-stacking of the thiophene rings and lamellar ordering of the π-stacked structures. All coarse-grained force fields are ranked according to their ability of preserving the experimentally known crystalline molecular arrangement of P3HT. The coarse-grained force fields parametrized in the amorphous melt turned out to accurately reproduce the structural quantities of the melt, as well as to preserve the lamellar ordering of the P3HT oligomers in π-stacks. However, the exact crystal structure is not reproduced. The combination of Boltzmann inversion for bonded and iterative Boltzmann inversion with pressure correction for nonbonded degrees of freedom gives the best coarse-grained model.