Dresden 2026 – scientific programme

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DY: Fachverband Dynamik und Statistische Physik

DY 43: Poster: Statistical Physics

DY 43.8: Poster

Wednesday, March 11, 2026, 15:00–18:00, P5

Bottom-Up DPD Thermostat Parameterization for Coarse-Grained Molecular Liquids — •Karan Venkatesh and Nico F. A. van der Vegt — Technische Universität Darmstadt

Coarse-grained (CG) models substantially accelerate molecular dynamics simulations but often yield dynamical properties that diverge from those of fine-grained (FG) systems. We introduce a dynamic coarse-graining framework that bottom-up parameterizes a Markovian Dissipative Particle Dynamics (DPD) thermostat in conjunction with a CG model of liquid cyclohexane, enabling more consistent reproduction of FG dynamical behavior. We determine the Markovian friction for the DPD thermostat by extracting its distance dependence from the fluctuations of pair forces measured in the FG simulations. The resulting distance-dependent friction is subsequently scaled by an amplitude optimized through an iterative procedure to match the long-time diffusion coefficient[1]. Compared to standard DPD[2], our bottom-up parameterized model significantly improves the reproduction of velocity autocorrelation functions (VACFs) on all time scales. It also yields a closer match to the frequency-dependent viscosity. Overall, this method offers a physically grounded, systematic route to parameterizing DPD thermostats for molecular liquids, preserving the efficiency of single-site coarse-graining while delivering improved dynamics across all time scales.

[1] V. Klippenstein; N F A van der Vegt; J. Chem. Theory Comput. 2023, 19(4), 1099-1110. [2] C. Junghans; M. Praprotnik; K. Kremer; Soft Matter 2008, 4(1), 156-161.

Keywords: DPD thermostat; Molecular liquids; Coarse grain; Parameterization; Molecular dynamics