Molecular simulation of polymers with a SAFT-γ Mie approach

We review the group contribution Statistical Associating Fluid Theory with Mie interaction potentials (SAFT-γ Mie) approach for building coarse-grained models for molecular simulation of polymeric systems. In this top-down method, force field parameters for coarse-grained polymer models can be derived from thermodynamic information on constituent monomer units using the SAFT-γ Mie equation of state (EoS). This strategy can facilitate high-throughput computational screening of polymeric materials, with a corresponding states correlation expediting the force field fitting. Accurate and transferable non-bonded parameters linked to macroscopic thermodynamic data allow for calculation of properties beyond those obtainable from the EoS alone. To overcome limitations of SAFT-γ Mie regarding polymer chain stiffness and branching, hybrid top-down/bottom-up approaches have combined non-bonded parameters from SAFT-γ Mie with bond-stretching and angle-bending potentials from higher-resolution force fields. Our review critically evaluates the performance of recent SAFT-γ Mie polymer models, highlighting the strengths and weaknesses in the context of other equation of state and coarse-graining methods.