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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 […]

Project B7: Automated model building and representation learning for multiscale simulations Project B7 addresses applications of machine learning techniques to multi-scale simulation of soft-matter systems. Multi-scale methods address the problem that the complexity of high-resolution base-line models grows too quickly for problems at relevant scales. Thus, they assumed that there is a coarser-resolution structure emerging from the details that can be efficiently computed with many fewer operations but that can still inform us about relevant behavioural aspects of the system. Machine learning can help in discovering such simplified surrogate computations by fitting a restricted computational model (such as a parametrized model, a kernel regressor, or a deep feed-forward network) to example results obtained from a full-resolution simulation. Conceptually, this involves two aspects: The first is to build a coarser-grained (CG) model. Learning of a CG model can take the form of just parametrizing a force-field or a mapping procedure motivated […]

Projects – C: Bridging the particle-continuum gap • C1: Using molecular fields to bridge between particle and continuum representations of macromolecular systems • C3: Spinodal decomposition of polymer-solvent systems • C4 (E): Nonlocal electrostatics of biomolecular systems • C5: Adaptive hybrid multiscale simulations of soft matter fluids • C6 (E): Linking hydrodynamics and microscopic models of wet active matter with anisotropic particles • C7: Dense active suspensions in the chaotic regime • C8: Numerical approximation of high-dimensional Fokker-Planck equations

Admission and Qualification Admission Students funded directly by the TRR146 are automatically admitted to the IRTG. External students can apply for admission by presenting a CV and a one-page project plan to the TRR146 Office where they explain how their project fits TRR146 topics. The application will be evaluated by the PIs of the IRTG. We anticipate that workshop and conference travel funding for admitted external students will be limited and accessible only upon application. Qualification plan The most important training element of the IRTG is the research on the project, assisted by efficient supervision . In addition, the integrated training group serves as a mean to provide students and young postdoctoral researchers with the training required for working within the CRC-TR. The training is made necessary by the interdisciplinary nature of the CRC-TR, where chemistry, physics, mathematics and computer science are intertwined in a non-standard combination, which is usually […]

IRTG – Activities The IRTG fosters its objectives through a series of activities (see items below), which the members can attend/exploit in relation to their needs. Participation to the activities of the IRTG should not require more than 15% of a student’s working time. The activities are coordinated by the coordination office of the CRC-TR together with the elected student/postdoc speakers.

IRTG Organization Currently, the student/postdoc speakers are • Rebecca Steiner (further information) • Fabio Frommer (further information) • Niklas Wolf (further information) • Maarten Brems (further information)

2022 – Publications

This section is still under development. A list of all publications until 2021 can be found here.

Project A2: Dynamically consistent coarse-grained models The aim of this project is to develop methods that endow chemically-specific coarse-grained (CG) simulation models with consistent dynamical properties. To this end, CG models with conservative and dissipative interactions are derived from a higher-resolution model using bottom-up coarse-graining methods that retain a highmlevel of chemical specificity. In the first two funding phases, we have developed methods for deriving Markovian and non-Markovian CG models that successfully represent the dynamics of molecular liquids, polymer solutions, and star-polymer melts on diffusive time scales. The Markovian method uses a dissipative particle dynamics (DPD) thermostat that is parameterised by means of a bottom-up approach using the microscopic dynamics. While successful in CG simulations of molecular liquids where only the friction due to the relaxation of atomic vibrations needs to be accounted for, it fails to describe the dynamics of polymer melts and the dynamics of small molecules in […]

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 […]