Assessing the transferability of common top-down and bottom-up coarse-grained molecular models for molecular mixtures

The performance of three methods for developing new coarse-grained models for molecular simulation is critically assessed. Two bottom-up approaches are employed: iterative Boltzmann inversion (IBI) and the multiscale coarse-graining method (MS-CG), using an atomistic n-octane-benzene reference system. Results are compared to a top-down coarse-graining approach employing the SAFT-γ Mie equation of state. The performance of each methodology is assessed against the twin criteria of local structure prediction and accurate free energy representation. In addition, the transferability of the generated potentials is compared across state points. We examine the extent to which the IBI methodology can be improved by using a multi-reference approach (MS-IBI), and demonstrate how a pressure correction can be employed to improve the results for the MS-CG approach. Additionally, we look at the effect of including angle-terms in the SAFT-γ Mie model. Finally, we discuss in detail the strengths and weaknesses of each method and suggest possible ways forward for coarse-graining, which may eventually address the problems of structure prediction, thermodynamic consistency and improved transferability within a single model.