Search Results

Project A3: Coarse-graining frequency-dependent phenomena and memory in colloidal systems The purpose of this project is to develop numerical strategies for dynamic coarse-graining in situations where the separation of time scales is incomplete and memory effects are important. This entails the reconstruction of coarse-grained dynamical equations that include memory (generalized Langevin equations, GLE), the efficient simulation of coarse-grained models with memory and the application to colloidal dispersions at equilibrium and non-equilibrium. This project is complementary to project A2, where related problems are addressed in the context of dynamic coarse-graining of molecular liquids. In the second funding period, we have extended our previous work on iterative memory reconstruction for single colloids (first funding period) to systems containing multiple colloids, where pair memory effects must be taken into account. A benchmark simulation of 125 colloids in solution showed that a speedup of at least three orders of magnitude can be obtained by […]

Project A4 (Completed): Understanding Water Relaxation Dynamics at Interfaces The aim of the project is to develop multiscale approaches to understand the mechanisms of vibrational energy relaxation in water at interfaces and in confined environment. In the first funding period, we have developed an efficient method to describe molecular vibrational relaxation based on single molecule excitations and the use of new descriptors. In the second funding period, we plan to include nuclear quantum effects (NQEs), which may be important in water. We aim to develop a multi resolution scheme where the electronic structure is included with an effective force field, which accurately reproduces high-level ab initio calculations, while the NQEs are explicitly addressed with the path integral formalism. This project has ended in June 2022.

Project A6: Coarse-grained models for dynamically asymmetric liquid mixtures under non-equilibrium conditions he main goal of this project is to gain better insight into the mapping of time-dependent properties of complex molecular systems, when studied using multiscale simulations. While the mapping of length scales is inherently defined by the coarse-graining procedure, the mapping of dynamic processes involves a complex combination of factors due to both the removal of degrees of freedom as well as approximations made in determining the coarse-grained (CG) interactions based on a reference all-atom (AA) model. As a consequence, the development of dynamically-consistent CG models is particularly challenging when various dynamic processes on different time scales coexist. To investigate these issues, we have focused on two important classes of systems, liquid crystals (LCs) and ionic liquids (ILs), which pair technological relevance with appropriate dynamics, and still show well defined modes of motion despite their significant complexity. In […]

Project A7: Dynamical coarse-graining for non-equilibrium steady states with stochastic dynamics Preserving dynamic information such as diffusion coefficients and transition rates in coarse-grained models is a persistent challenge in multi-scale simulations. This task becomes even more daunting when the original microscopic dynamics breaks detailed balance, corresponding to the system being driven away from thermal equilibrium. The aim of this project is to develop a comprehensive computational method to coarse-grain models from atomistic resolution to a few discrete states while preserving the statistics of the energetic exchange with their environment. In complex macro and biomolecules, these discrete states are identified with long-lived molecular conformations. In the second funding period, we are addressing the question how to model transitions that go beyond simple conformational transitions and involve a chemical transformation. To this end, we study a molecular rotor that is driven by light and performs asymmetric photoisomerization steps to achieve directional rotation. […]

Project B1: Inverse problems in coarse-grained particle simulations Coarse-graining (CG) methods are an indispensable tool in computational materials science, but the associated upscaling and downscaling processes have to be designed with great care to allow for a proper interpretation of the computed results. Each of these interscale transfers comes along with important inverse problems to be resolved, most of which are ill-posed, or ill-conditioned at the very least. The purpose of this project is to apply rigorous techniques from the mathematical field of inverse and ill-posed problems to attack these fundamental problems in the multiscale simulation of soft matter, and to provide a mathematically rigorous foundation of existing and/or new upscaling processes. n the first two funding phases we have developed the mathematical foundation for a rigorous analysis of iterative methods that are currently being used for the computation of effective pair potentials of sophisticated CG models. We have used […]

Integrated research training group (IRTG) The integrated research training group (IRTG) of the TRR 146 provides a joint structured graduate education in the area of Computational Materials Science for the graduate students and young postdocs in the TRR 146 as well as other interested candidates working in related areas. The goals of the IRTG are threefold: 1) to provide students with the interdisciplinary background required for the research activities in the TRR 146, and to prepare them for a possible career in the area of theoretical Materials Sciences 2) to ensure common standards in the education of all graduate students in the TRR 146 by means of a well structured supervision and management program, 3) to establish and strengthen links within the TRR 146 already at the level of graduate students and young postdoctoral researchers. Special emphasis is placed on promoting exchange between groups within and outside of the TRR […]

Scientific Coordinator of the TRR 146 Niklas Litzenberger Staudingerweg 9 D-55128 Mainz trr146@uni-mainz.de +49 6131 39 28480