Quantitative bridging between full-atomistic and bead-spring models for polybutadiene and poly(butadiene-styrene) copolymers

A Baba and Y Masubuchi, JOURNAL OF CHEMICAL PHYSICS, 154, 044901 (2021).

DOI: 10.1063/5.0036555

Despite lots of attempts on the bridging between full-atomistic and coarse-grained models for polymers, a practical methodology has not been established yet. One of the problems is computation costs for the determination of spatial and temporal conversion parameters, which are ideally obtained for the long chain limit. In this study, we propose a practical, yet quantitative, bridging method utilizing the simulation results for rather short chains. We performed full-atomistic simulations for polybutadiene and some poly(butadiene-styrene) copolymers in the melt state by varying the number of repeating units as 20, 30, and 40. We attempted to construct corresponding coarse-grained models for such systems. We employed the Kremer-Grest type bead-spring chains with bending rigidity. The stiffness parameter of coarse-grained models and the spatial conversion factor between the full-atomistic and coarse- grained models were obtained according to the conformational statistics of polymer chains. Although such a bridging strategy is similar to the earlier studies, we incorporated the molecular weight dependence of the conformational statistics for the first time. By introducing several empirical functions of the conformational statistics for the molecular weight dependence, we attained a rigorous bridging for the conformational statistics. We confirmed that the structural distribution functions of the coarse-grained systems are entirely consistent with the target full-atomistic ones. Owing to the structural conversion parameters thus obtained, we constructed the coarse-grained models that corresponded to the polymers consisting of 200 repeating units and traced the segmental diffusion. The full-atomistic simulations were also performed from the initial configurations created from the equilibrated coarse-grained models via the back-mapping scheme. From the comparison of the mean-square-displacement of the segments positioned at the middle of the chain, we obtained the temporal conversion factors.

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