Research Topics of the Department of Theoretical Solid State Physics

The Dreßler group investigates condensed matter systems using molecular dynamics simulations and develops multiscale models to describe ion transport in energy materials.

Molecular dynamics simulations of condensed matter.

The Dreßler group has a focus on the investigation of the structure and dynamics of condensed matter systems using ab initio molecular dynamics and classical molecular dynamics simulations. In particular, we are interested in the description of chemical charge transport in energy materials. For example, we have elucidated the effect of anion rotation on proton conductivity in the solid acid family [1] or identified lithium ion transport pathways in lithium silicides [2].

 

[1] Dreßler, Sebastiani, Effect of anion reorientation on proton mobility in the solid acids family CsHyHXO4 (x = S, P, Se; y= 1, 2) from ab initio molecular dynamics simulations, Physical Chemistry Chemical Physics, 22, 10738–10752, 2020.

[2] Kirsch, Dreßler, Sebastiani. Atomistic Diffusion Pathways of Lithium Ions in Crystalline Lithium Silicides from ab Initio Molecular Dynamics Simulations, The Journal of Physical Chemistry C, 126, 29, 12136-12149, 2022.

Christian Dreßler

Multiscale approaches for the simulation of long-range proton transfer

Bild MultiskalenansatzChristian Dreßler

The Dressler group has developed a multiscale simulation approach for describing proton long range transfer on the micrometer length and millisecond time scales.[1] We have shown that our approach can be used to calculate the proton conductivity of nanoporous CsH2PO4 systems as a function of porosity.[2] The multiscale method is based on a combination of molecular dynamics simulation and probabilistic propagation of protons by a Monte Carlo approach. Utilizing this method, we are able to condense the information concerning the proton dynamics of an entire molecular dynamics trajectory into a single transition matrix, which allows for the simulation of much larger systems.[3] Through careful mathematical analysis of this matrix, qualitative properties of the model and information about the mechanism of proton conduction can be derived. In the future, we plan to extend the multiscale approach to the transport of other types of ions. In general, we are interested in developing Markov models for the description of any microscopic dynamical processes.

Why do we need multiscale approaches?

Ab initio molecular dynamics simulations can be used to simulate proton transfer in bulk-phase homogeneous materials, but their application is limited to small system sizes of several hundred atoms and simulation times of less than a nanosecond. These accessible time and length scales are far too small for describing realistic, non-ideal, inhomogeneous, and nanostructured proton conducting materials.

[1] Dreßler, Kabbe, Brehm, Sebastiani. Exploring non-equilibrium molecular dynamics of mobile protons in the solid acid CsH2PO4 at the micrometer and microsecond scale. The Journal of Chemical Physics, 152, 164110, 2020.

[2] Wagner, Dreßler, Lohmann-Richters, Hanus, Sebastiani, Varga, Abel. Mechanism of ion conductivity through polymer-stabilized CsH2PO4 nanoparticular layers from experiment and theory. Journal of Materials Chemistry A , 7, 27367–27376, 2019.

[3] Dreßler, Kabbe, Brehm, Sebastiani. Dynamical matrix propagator scheme for large-scale proton dynamics simulations, The Journal of Chemical Physics, 152, 114114, 2020.

 

Efficient representations of the linear density-density response function

The static linear density-density response function and, in particular, its frequency-dependent pendant are complex and theoretically rich objects that have applications in many fields. The Dreßler group is investigating low-dimensional representations of the static linear density-density response function for the efficient calculation of intermolecular electrostatic polarization interactions.[1,2] If the response function is known, molecular density responses to arbitrary perturbations can be calculated at a fraction of the computational cost of a first principle calculation.[3] In the future, we plan to develop a polarizable force field based on the efficient representation of the static linear density-density response function. We also plan to extend the efficient representation to the dynamical variant of the response function.

[1] Dreßler, Scherrer, Ahlert, Sebastiani. Efficient representation of the linear density-density response function, Journal of Computational Chemistry, 40, 2712–2721, 2019.

[2] Dreßler, Sebastiani, Reduced eigensystem representation of the linear density-density response function, International Journal of Quantum Chemistry, 120, e26085, 2020.

[3] Dreßler, Sebastiani, Polarization Energies from Efficient Representation of the Linear Density-Density Response Function, Advanced Theory and Simulation, 4, 2000260, 2021.

 
Densityresponce_1Christian Dreßler