  We demonstrate that hierarchical backmapping strategies incorporating generic
blob-based models can equilibrate melts of high-molecular-weight polymers,
described with chemically specific, atomistic, models. The central idea behind
these strategies, is first to represent polymers by chains of large soft blobs
(spheres) and efficiently equilibrate the melt on mesoscopic scale. Then, the
degrees of freedom of more detailed models are reinserted step by step. The
procedure terminates when the atomistic description is reached. Reinsertions
are feasible computationally because the fine-grained melt must be
re-equilibrated only locally. To develop the method, we choose a polymer with
sufficient complexity. We consider polystyrene (PS), characterized by
stereochemistry and bulky side groups. Our backmapping strategy bridges
mesoscopic and atomistic scales by incorporating a blob-based, a moderately CG,
and a united-atom model of PS. We demonstrate that the generic blob-based model
can be parameterized to reproduce the mesoscale properties of a specific
polymer -- here PS. The moderately CG model captures stereochemistry. To
perform backmapping we improve and adjust several fine-graining techniques. We
prove equilibration of backmapped PS melts by comparing their structural and
conformational properties with reference data from smaller systems,
equilibrated with less efficient methods.
