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Updated: Jul 15, 2026

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

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

Manisha Dhillayan¹, Florian Müller-Plathe¹

¹Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technical University of Darmstadt, 64287 Darmstadt, Germany.

The Journal of Physical Chemistry. B

|July 13, 2026

Summary

Coarse-grained simulations accelerate molecular dynamics due to reduced surface roughness. The RoughMob method quantifies this acceleration by linking it to the active volume of hydrocarbon molecules, improving dynamic predictions.

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Area of Science:

Computational chemistry and molecular dynamics simulations.
Soft matter physics and fluid dynamics.

Background:

Coarse-grained (CG) simulations offer efficient phase space sampling for complex fluids at larger scales than atomistic methods.
CG models often exhibit accelerated dynamics due to reduced degrees of freedom and surface roughness.
The RoughMob approach previously linked dynamic acceleration to geometric changes in one-bead CG models.

Purpose of the Study:

To extend the RoughMob approach to two-bead CG models for more complex liquid hydrocarbons.
To establish a quantitative relationship between molecular surface roughness and dynamic acceleration.
To accurately predict diffusion coefficient acceleration factors for various liquid hydrocarbons.

Main Methods:

Decomposition of molecular volume into active and passive contributions.
Application of the RoughMob method to two-bead CG models of 13 liquid hydrocarbons.
Correlation analysis between acceleration factors and molecular volume components.

Main Results:

A strong correlation was found between the diffusion coefficient acceleration factor and the active, roughness-bearing molecular volume.
Passive volume contributions were identified as having a secondary role in dynamic acceleration.
The developed relation accurately predicted acceleration factors across a range of molecular sizes and complexities.

Conclusions:

The RoughMob approach, extended to two-bead CG models, effectively predicts dynamic acceleration in liquid hydrocarbons.
Molecular surface roughness, particularly within the active volume, is a key determinant of dynamic acceleration.
This work provides a robust method for correcting dynamic inaccuracies in coarse-grained simulations of complex fluids.