Steve O. Nielsen

Coarse grain models and the computer simulation of soft materials

This article presents a topical review of coarse grain simulation techniques. First, we motivate these techniques with illustrative examples from biology and materials science. Next, approaches in the literature for increasing the efficiency of atomistic simulations are mentioned. Considerations related to a specific coarse grain modelling approach are discussed at length, and the consequences arising from the loss of detail are given. Finally, a large number of results are presented to give the reader a feeling for the types of problem which can be addressed.

A coarse grain model for n-alkanes parameterized from surface tension data

Molecular dynamics simulations are carried out in a systematic manner to develop a coarse grain model for multiple-of-three carbon n-alkanes. The procedure involves optimizing harmonic bond and bend parameters, and Lennard-Jones nonbonded parameters, to match observables taken from fully atomistic simulations and from experiment. The experimental values used consist of surface tension and bulk density data. Scaling relations are introduced to allow for the representation of the remaining n-alkanes. As n increases these relations converge to the multiple-of-three carbon values. The model is assessed by comparing it to both fully atomistic simulation and experimental data which was not used in the fitting procedure.

Self-assembly of a phospholipid Langmuir monolayer using coarse-grained molecular dynamics simulations

Molecular dynamics simulations using a coarse-grained (CG) model for dimyristoyl-phosphatidyl-choline and water molecules have been carried out to follow the self-assembly process of a Langmuir monolayer. We expand on a previous study of the characteristics of the CG model where we compare the rotational and translational constants of the present model to those of an all-atom (AA) model, and find that the rotational and translational timescales are up to two orders of magnitude faster than in an AA model. We then apply the model to the self-assembly of a Langmuir monolayer. The initial randomly distributed system, which consists of 80 lipids and 5000 water sites, quickly self-assembles into two Langmuir monolayers and a micelle in the bulk water region. The micelle slowly diffuses towards and fuses with one of the interfacial monolayers, leaving the final equilibrated state with a Langmuir monolayer at each of the two air/water interfaces. The effective speed-up gained from the CG approach gives access to timescales and spatial scales that are much larger than those currently accessible with AA models.

A Coarse Grain Model for Lipid Monolayer and Bilayer Studies

Experimental work on complex condensed matter can address a broad range of temporal and spatial scales, from femtosecond dynamics and atomistic detail to real-time macroscopic phenomena. Simulation methods in which each atom is explicitly represented are well established but have difficulty addressing many cooperative effects of experimental and theoretical interest. There is simply too large a gap between the time and spatial scales that govern typical intramolecular events and those which are relevant for collective motions. One example is the spatial rearrangement of membrane species such as occur in the formation of a lipid raft [1] or membrane fusion. Available simulation techniques for specific time and spatial scales are illustrated schematically in Fig. 2.1. These techniques take a variety of approaches to reduce the level of detail in the representation of the system under study as the time and/or length scales grow. This will be discussed further in Sect. 2.3. Bridging these disparate scales is possible with multiscale modeling [2,3,4] in which the various levels of treatment are coupled and fed back into one another.