Mesoscopic simulation of entanglements using dissipative particle dynamics: application to polymer brushes

Area of Science:

• Computational materials science
• Polymer physics
• Soft matter physics

Background:

• Polymer entanglements significantly influence the macroscopic properties of polymeric materials.
• Accurate modeling of entanglements is crucial for understanding phenomena like polymer brush lubrication.
• Dissipative Particle Dynamics (DPD) is a mesoscopic simulation technique widely used for soft matter systems.

Purpose of the Study:

• To introduce a novel, simple spring-spring repulsion model for simulating polymer entanglements in DPD.
• To investigate the impact of reduced polymer entanglements on the lubrication properties of polymer brushes.
• To quantify the relationship between entanglement reduction and changes in rheological properties.

Main Methods:

• Implementation of a spring-spring repulsion force to represent polymer entanglements within DPD simulations.
• Application of the model to a polymer brushes system under shear conditions.
• Calculation of bond crossings as a quantitative measure of entanglement and analysis of friction coefficients.

Main Results:

• The spring-spring repulsion model effectively models entanglements and achieves mechanical equilibrium in polymer brushes at standard DPD time steps.
• A significant reduction (up to 99%) in bond crossings was achieved without substantially altering the simulation time step.
• Decreasing polymer entanglements led to an increase in the friction coefficient of the polymer brushes.

Conclusions:

• The proposed spring-spring repulsion model offers an efficient method for simulating polymer entanglements in DPD.
• Reducing entanglements in polymer brushes can enhance lubrication by increasing friction.
• This approach provides a quantitative link between polymer entanglement, brush structure, and rheological behavior.