Dynamic Monte Carlo algorithm for out-of-equilibrium processes in colloidal dispersions

Area of Science:

• Colloidal science
• Soft matter physics
• Computational materials science

Background:

• Colloidal dispersions are crucial in diverse industrial applications, from personal care to paints.
• External forces can significantly alter colloidal behavior and thermodynamic equilibrium, impacting formulation performance.
• Accurate simulation of colloidal dynamics, especially out-of-equilibrium states, is essential for scientific understanding and engineering.

Purpose of the Study:

• To generalize an efficient Dynamic Monte Carlo (DMC) approach for simulating colloidal particle Brownian motion.
• To model the out-of-equilibrium dynamics of colloidal dispersions under external fields.
• To investigate the isotropic-to-nematic phase transition induced by external fields and subsequent system behavior.

Main Methods:

• Developed and applied an efficient Dynamic Monte Carlo (DMC) simulation method.
• Investigated monodisperse and bidisperse rod-like particles in the isotropic phase.
• Applied an external field to induce particle reorientation and phase transitions, followed by field removal.

Main Results:

• The generalized DMC approach successfully reproduces Brownian motion in transitory unsteady states.
• Simulations accurately capture the isotropic-to-nematic phase transition and subsequent system dynamics.
• DMC simulation results show excellent quantitative agreement with Brownian Dynamics simulations after rescaling.

Conclusions:

• The developed DMC method provides a rigorous and efficient way to simulate colloidal dynamics, including out-of-equilibrium phenomena.
• The findings offer a valuable tool for predicting and controlling the behavior of colloidal formulations.
• Rescaling DMC results with a time-dependent acceptance ratio ensures quantitative accuracy against established methods.