(708f) Prediction of Interaction Parameters for Coarse-Grained Models Using Ab Initio Calculations | AIChE

(708f) Prediction of Interaction Parameters for Coarse-Grained Models Using Ab Initio Calculations

Authors 

Santiso, E., NC State University
Coarse Grained (CG) models enable the simulation of larger systems, and phenomena occurring on longer time scales, than traditional atomistic simulation methods. However, determining CG model parameters is usually a time-consuming task, which involves carrying out atomistic-level simulations and fitting CG parameters to the results. An alternative approach is top-down coarse graining, which obtains CG parameters by fitting directly to experimental data. The SAFT-γ-Mie force field, where the parameters of a Mie potential representing interactions between coarse-grained beads are fit to phase-equilibrium data, is an example of this approach1,2. A challenge in developing such CG models is the determination of unlike-pair interaction parameters. If the number of beads in the force field is large, it becomes impractical to fit all the unlike interactions due to the combinatorial explosion in the number of parameters. The commonly used Lorentz-Berthelot mixing rules work well for systems where the main interactions are dispersion forces, but they do not account for electrostatics or molecular polarizability. In this work, we derive these mixing rules for the SAFT-γ-Mie force field to include these interactions. In the resulting model, the unlike-pair interactions account for the effect of charges, dipole moments, quadrupole moments, and polarization. We then show how, by estimating these properties for the CG molecular fragments using ab initio calculations, it is possible to obtain realistic cross-interaction energies without the need to use extensive experimental data.

  1. Dufal, S. et al. Prediction of Thermodynamic Properties and Phase Behavior of Fluids and Mixtures with the SAFT-γ-Mie Group-Contribution Equation of State. Journal of Chemical & Engineering Data 59, 3272–3288 (2014).
  2. Papaioannou, V. et al. Group contribution methodology based on the statistical associating fluid theory for heteronuclear molecules formed from Mie segments. The Journal of Chemical Physics 140, 054107 (2014).