Predicting Mobility Acceleration in Two-Bead Coarse-Grained Models Using an Augmented RoughMob Framework

Coarse-grained (CG) simulations provide an efficient framework for sampling the phase space of complex fluids over time- and length-scales inaccessible to atomistic simulations. While most CG approaches accurately reproduce the microscopic structure of their underlying atomistic systems, they generally exhibit artificially accelerated dynamics. This dynamic acceleration is due to the reduction of the number of degrees of freedom in CG models, which leads to reduced roughness on the molecular surfaces. The RoughMob approach [Meinel and Müller-Plathe J. Phys. Chem. B 2022, 126 (20), 3737-3747] links the dynamic acceleration to the changes in geometry upon coarse-graining and is shown to be successful for one-bead CG models of a set of hydrocarbon liquids. In this paper, we extend this method to two-bead CG models of another set of more complex liquid hydrocarbons. By decomposing molecular volume into active and passive contributions, we establish a relationship between surface roughness and mobility acceleration. Our findings show that the acceleration factor for the diffusion coefficient correlates well with the active roughness-bearing volume, while passive contributions have a secondary role in dynamic acceleration. The resulting relation accurately predicts the acceleration factors for the diffusion coefficients of 13 liquid hydrocarbons spanning a broad range of molecular sizes and shape complexities, including different isomers of alkanes from butane to octane.