Many physical phenomena and properties of soft matter systems such as synthetic or biological materials are governed by interactions and processes on a wide range of length- and time-scales. Computer simulation approaches that are targeted at questions in these systems require models which cover these scales and the respective levels of resolution. Multiscale simulation methods combine and systematically link several simulation hierarchies so that they can address phenomena at multiple levels of resolution. In order to reach the mesoscopic time- and length-scales important for many material properties, methods that bridge from the atomistic (microscopic) to a coarser (mesocopic) level are developed. Here, we review coarse-grained simulation models that are linked to a higher resolution atomistic description. In particular, we focus on structure-based coarse-graining methods which are used for a variety of soft matter problems – ranging from structure-formation in amorphous polymers to biomolecular aggregation. It is shown that by coarse-grained simulation in combination with an efficient backmapping methodology one can obtain well-equilibrated long time- and large length-scale atomistic structures of polymeric melts or biomolecular aggregates which can be used for comparison to experimental data. Methodological aspects are addressed such as the question of the time-scales and dynamics in the different simulation hierarchies and an outlook to future challenges in the area of resolution exchange approaches and adaptive resolution models is presented.

Water and alcohol, such as methanol or ethanol, are miscible and, individually, good solvents for poly(N-isopropylacrylamide) (PNIPAm), but this polymer precipitates in water-alcohol mixtures. The intriguing behaviour of solvent mixtures that cannot dissolve a given polymer or a given protein, while the same macromolecule dissolves well in each of the cosolvents, is called cononsolvency. It is a widespread phenomenon, relevant for many formulation steps in the physicochemical and pharmaceutical industry, that is usually explained by invoking specific chemical details of the mixtures: as such, it has so far eluded any generic explanation. Here, by using a combination of simulations and theory, we present a simple and universal treatment that requires only the preferential interaction of one of the cosolvents with the polymer. The results show striking quantitative agreement with experiments and chemically specific simulations, opening a new perspective towards an operational understanding of macromolecular solubility.

Ring polymers remain a challenge to our understanding of polymer dynamics. Experiments are difficult to interpret because of the uncertainty in the purity and dispersity of the sample. Using both equilibrium and nonequilibrium molecular dynamics simulations we have investigated the structure, dynamics, and rheology of perfectly controlled ring-linear polymer blends of chains of up to about 14 entanglements per chain, comparable to experimental systems. Linear contaminants increase the zero-shear viscosity of a ring polymer melt by about 10% around one-fifth of their overlap concentration. For equal concentrations of linear and ring polymers, the blend viscosity is about twice that of the pure linear melt. The diffusion coefficient of the rings decreases dramatically, while the linear polymers are mostly unaffected. Our results are supported by a primitive path analysis.

Many physical phenomena and properties of soft matter systems are characterized by an interplay of interactions and processes that span a wide range of length- and time scales. Computer simulation approaches require models, which cover these scales. These are typically multiscale models that combine and link different levels of resolution. In order to reach mesoscopic time- and length scales, necessary to access material properties, coarse-grained models are developed. They are based on microscopic, atomistic descriptions of systems and represent these systems on a coarser, mesoscopic level. While the connection between length scales can be established immediately, the link between the different time scales that takes into account the faster dynamics of the coarser system cannot be obtained directly. In this perspective paper we discuss methods that link the time scales in structure based multiscale models. Concepts which try to rigorously map dynamics of related models are limited to simple model systems, while the challenge in soft matter systems is the multitude of fluctuating energy barriers of comparable height. More pragmatic methods to match time scales are applied successfully to quantitatively understand and predict dynamics of one-component soft matter systems. However, there are still open questions. We point out that the link between the dynamics on different resolution levels can be affected by slight changes of the system, as for different tacticities. Furthermore, in two-component systems the dynamics of the host polymer and of additives are accelerated very differently.

This paper gives a short introduction to multiscale simulation approaches in soft matter science. This paper is based on and extended from a previous review.¹ (1. C. Peter and K. Kremer, Soft Matter, 2009, DOI:10.1039/b912027k.) It also includes a discussion of aspects of soft matter in general and a short account of one of the historically underlying concepts, namely renormalization group theory. Some different concepts and several typical problems are shortly addressed, including a (more personal) view on challenges and chances.