Coarse-graining of polyisoprene melts using inverse Monte Carlo and local density potentials

Bottom-up coarse-graining of polymers is commonly performed by matching structural order parameters such as pair distribution functions and distribution of bond lengths, bending angles and dihedrals. We introduce the distribution of nearest-neighbors as an additional multi-body order parameter to improve the representability of the coarse-grain model. We develop the force-field using the inverse-Monte Carlo method to overcome the challenges associated with cross-correlation of interaction terms in polymer systems.

The technique is applied on polyisoprene melts as a prototype system. We demonstrate that while different coarse-grain models can be developed that perform equally in terms of matching the structural order parameters, the inclusion of the nearest-neighbors potentials provides a straightforward route to match both thermodynamic and conformational properties. We find that by refining the force-field, several temperature state points can be addressed. We also examine the dynamics of the coarse-grain models, demonstrating that all forcefields present a similar acceleration relative to the atomistic systems.