Computer Simulations and Coarse-Grained Molecular Models Predicting the Equation of State of Polymer Solutions

Monte Carlo and molecular dynamics simulations are, in principle, powerful tools for carrying out the basic task of statistical thermodynamics, namely the prediction of macroscopic properties of matter from suitable models of effective interactions between atoms and molecules. The state of the art of this approach is reviewed, with an emphasis on solutions of rather short polymer chains (such as alkanes) in various solvents. Several methods of constructing coarse-grained models of the simple bead–spring type will be mentioned, using input either from atomistic models (considering polybutadiene as an example) or from experiment. Also, the need to have corresponding coarse-grained models of the solvent molecules is emphasized, and examples for various dipolar and quadrupolar fluids and their mixtures with short alkanes are given. Finally, we mention even more simplified models, such as the bond fluctuation model on the simple cubic lattice, treating applications like micelle formation in block copolymer solutions or isotropic–nematic phase transitions in solutions of stiff polymers as case studies. Comparisons with pertinent predictions from approximate analytical theories will be briefly mentioned, as well as applications, to understand experimental results.