We demonstrate how an iterative method for potential inversion from distribution functions developed for simple liquid systems can be generalized to polymer systems. It uses the differences in the potentials of mean force between the distribution functions generated from a guessed potential and the true distribution functions to improve the effective potential successively. The optimization algorithm is very powerful: convergence is reached for every trial function in few iterations. As an extensive test case we coarse-grained an atomistic all-atom model of polyisoprene (PI) using a 13:1 reduction of the degrees of freedom. This procedure was performed for PI solutions as well as for a PI melt. Comparisons of the obtained force fields are drawn. They prove that it is not possible to use a single force field for different concentration regimes.

A nonequilibrium molecular dynamics method for calculating the thermal conductivity is presented. It reverses the usual cause and effect picture. The “effect,” the heat flux, is imposed on the system and the “cause,” the temperature gradient is obtained from the simulation. Besides being very simple to implement, the scheme offers several advantages such as compatibility with periodic boundary conditions, conservation of total energy and total linear momentum, and the sampling of a rapidly converging quantity (temperature gradient) rather than a slowly converging one (heat flux). The scheme is tested on the Lennard-Jones fluid.

Polymers can be theoretically and computationally described by models pertaining to different length scales and corresponding time scales. These models have traditionally been used independently of each other. Recently, considerable progress has been made in systematically linking models of different scales. This Review focuses on the generation of lattice and off‐lattice coarse‐grained polymer models, whose “monomers” correspond to roughly a chemical repeat unit, from chemically detailed atomistic simulations of the same polymers. Computational methods are described as well as applications to polymers in the melt and in solution. The success of multiscale simulations in solving real‐world polymer problems that could not be solved in any other way suggests that they will have an important role to play in the future.

In this article, we present coarse-grained potentials of ethylbenzene developed at 298 K and of amorphous polystyrene developed at 500 K by the pressure-corrected iterative Boltzmann inversion method. The potentials are optimized against the fully atomistic simulations until the radial distribution functions generated from coarse-grained simulations are consistent with atomistic simulations. In the coarse-grained polystyrene melts of different chain lengths, the Flory exponent of 0.58 is obtained for chain statistics. Both potentials of polystyrene and ethylbenzene are transferable over a broad range of temperature. The thermal expansion coefficients of the fully atomistic simulations are well reproduced in the coarse-grained models for both systems. However, for the case of ethylbenzene, the coarse-grained potential is temperature-dependent. The potential needs to be modified by a temperature factor of T / T 0 when it is transferred to other temperatures; T 0 = 298 K is the temperature at which the coarse-grained potential has been developed. For the case of polystyrene, the coarse-grained potential is temperature-independent. An optimum geometrical combination rule is proposed with the combination constant x = 0.4 for mutual interactions between the polystyrene monomer and ethylbenzene molecules in their mixtures at different composition and different temperature.