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Prof. Dr. Kurt Kremer Max Planck-Institut für Polymerforschung Ackermannweg 10 D-55128 Mainz Tel: +49 6131 379140 Fax: +49 6131 379340 Secr: +49 6131 379141 Mail: kremer@mpip-mainz.mpg.de Further information

Project C3: Spinodal decomposition of polymer-solvent systems We consider the phase separation of dynamically asymmetric mixtures, in particular polymer solutions, after a sudden quench. Crucial aspects are (i) hydrodynamic momentum transport and (ii) the lack of time-scale separation between molecular relaxation and coarsening. This gives rise to complex dynamical processes such as the transient formation of network-like structures of the slow-component-rich phase, its volume shrinking, and lack of dynamic self-similarity, which are frequently summarized under the term viscoelastic phase separation. The relevant length and time scales of the physical phenomena are too large for microscopic (all atom) simulations. Alternative mesoscopic models based on a bead-spring description of polymer chains coupled to a hydrodynamic background, i.e., the Navier-Stokes equations for the solvent, allow to capture the basic physical principles but they are still computationally demanding. Therefore, macroscopic (two-fluid) models have been proposed in the literature which involve only averaged field quantities […]

Project B2: Many-body effects and optimized mapping schemes for systematic coarse-graining The first goal of the B2 project is to provide the consortium with a platform for systematic coarse-graining via the open-source software package “Versatile Object-oriented Toolkit for Coarse-graining Applications” (VOTCA). Projects requiring swift parameterizations of coarse-grained models have already benefited from using this toolkit. The second goal is the development of coarse-grained potentials that capture more accurately many-body effects, by going beyond standard pair-wise interactions. To this end, we develop and test various coarse-graining strategies based on short-range three-body, local-density-dependent, and local-conformation-dependent potentials. Further, we devise optimized mapping schemes for coarse-grained representations using machine-learning techniques: In the previous funding period, we trained artificial neural networks for structural coarse-graining, and kernel-based methods to develop a general model for three-body potentials. Building upon our previous research, we will advance our coarse-graining strategies to better reproduce conformational details and dynamics, and also […]

Project B3: Coarse-graining of solvent effects in force-probe molecular dynamics simulations The study of the conformational kinetics of biomolecules and supramolecular complexes using molecular simulations often is complicated by the fact that these processes are very slow. Various simulation techniques have been developed in order to resolve this issue. One very efficient way to investigate the atomistic details of conformational changes is provided by force-probe molecular dynamics (FPMD) simulations. In the most common realization of this technique, one end of the (supra)molecular system under consideration is fixed in space and the other end is pulled apart with a constant velocity via the application of a harmonic potential. From the distributions of the forces needed to unfold the system important information regarding the kinetics and the thermodynamics of the relevant conformational rearrangements can be obtained via a statistical analysis. The direct comparison to the results of experimental realizations of force spectroscopy […]

Project B4: Equilibrium and non-equilibrium processes in open systems via adaptive resolution simulations Computational soft matter constitutes a major application area for simulations, with extraordinary conceptual and practical relevance. Due to the systems’ intrinsic complexity, a considerable effort in this area has focused on investigating somewhat idealised models, e.g., consisting of a few essential molecular species in explicit or implicit solvent. In reality, even the simplest experimentally relevant systems, such as (bio)macromolecules in aqueous mixtures and nanochannels, are far more complex, involving many interacting species, evolving under open-boundary and non-equilibrium conditions. Increasing the complexity and detail of the computational model for these systems poses a significant challenge. Indeed, the interplay of interactions and processes spanning a wide range of length and time scales requires a multiscale approach, including methods resolving quantum, classical, coarse-grained and continuum degrees of resolution. However, it is often the case that a high-resolution method is only […]

Project B5: Multi-resolution methods including quantum chemistry, force fields, and hybrid particle-field schemes Multiscaling techniques that involve a quantum-chemical treatment of the electronic structure for the part with the highest resolution are promising computational tools. They are particularly useful for dealing with problems involving large systems like enzymes, membranes, polymers, etc., where, for example, chemical reactions take place. Having completed in the previous funding period of the TRR (i.e., the first funding period of this project) a corresponding QM/MM implementation that allows to include high-accuracy quantum-chemical methods from either coupled-cluster (CC) theory (i.e., CCSD, CCSD(T), etc.) or of multiconfigurational nature (i.e., CASSCF), we intend to complete the envisioned QM/MM/CG/hPF implementation that extends the QM/MM approach to coarse-grained (CG) treatments. In particular, we plan on using hybrid particle-field (hPF) theory based on its Hamiltonian reformulation, where the latter has been accomplished in the first funding period of this project. This reformulation […]

Project B6: Topological validation of coarse-grained polymer models Computational studies of polymer-based materials on large length and time scales require mesoscopic models: drastically coarse-grained descriptions where non-bonded potentials between interacting particles are on the order of the thermal energy. Such “soft” models are either used as “stand alone” descriptions or as elements of strategies, where the microscopic description of the material is recovered through sequential backmapping in a hierarchy of mesoscopic models. In the previous funding period, we focused on using single-chain topology ─ polymer knots ─ to validate mesoscopic models and hierarchical backmapping schemes for bulk high-molecular-weight polymer melts. We made three important findings: A) We demonstrated that polymer knots are, in general, multiscale objects, i.e. they simultaneously depend on microscopic and medium-scale features. As such, they cannot be always accurately described by mesoscopic models. B) Nevertheless, we identified conditions when mesoscopic models can quantitatively reproduce knotting properties of […]