(500b) Combined Equation of State Modelling and Coarse-Grained Molecular Simulation of Polymers and Polymer Mixtures Via SAFT-? Mie

A framework to self-consistently combine a classical equation of state (EoS) and a molecular force field to model polymers and polymer mixtures is presented. The statistical associating fluid theory (SAFT-γ Mie) [1][2] model is used to correlate the thermophysical properties of oligomers and generate robust and transferrable coarse-grained (CG) molecular parameters which can be used both in particle based molecular simulations and in EoS calculations. A unique aspect of this proposal is the use of the same parameters in both the force field and the theory model, allowing a seamless transition from molecular modelling at the nanoscale and theoretical modelling at the macroscale. Examples are provided for polyethylene, polypropylene, polyisobutylene atactic polystyrene, 1,4-cis-butadiene, polyisoprene, their blends and mixtures with low molecular weight solvents.

By exploiting the EoS in parametrizing cross interactions between two fluid species, robust and transferable binary interaction parameters are obtained between monomeric segments of the polymers and selected solvents. These temperature-independent parameters are used to quantitatively describe different types of liquid-liquid phase behaviour by both the EoS and by direct molecular dynamics simulations. The phase behaviours include systems with either upper or lower critical miscibility limits, with both upper and lower miscibility limits, and with the two miscibility regions merging, forming an hourglass shape.

The use of CG models following this top-down approach extends the time and length scales accessible to molecular simulation while retaining quantitative accuracy as compared to experimental results. On the other hand, the use of the theory which matches an underlying Hamiltonian provides for robustness in the predictions and extrapolations of the EoS.

References:

[1] Müller, E. A., and Jackson, G. (2014). Annual Rev Chem. Biomolec. Eng. , 5: 405-427.

[2] Papaioannou, V., et al. (2014) J. Chem. Phys 140: 054107.