Multiscale simulation of ideal mixtures using smoothed dissipative particle dynamics

Area of Science:

• Computational physics
• Fluid dynamics
• Statistical mechanics

Background:

• Smoothed dissipative particle dynamics (SDPD) is a particle-based continuum hydrodynamics solver.
• SDPD incorporates scale-dependent thermal fluctuations.
• Existing methods lacked accurate multicomponent mixture simulation capabilities.

Purpose of the Study:

• To develop a new formulation of SDPD for ideal two-component mixtures.
• To create a general multiscale multicomponent SDPD framework.
• To ensure the method reproduces correct fluctuations, diffusion dynamics, and equilibrium properties.

Main Methods:

• Discretization of the advection-diffusion equation with thermal noise in the concentration field.
• Development of a multicomponent approach consistent with fluid volumes.
• Validation through one-dimensional diffusion simulations across multiple length scales.

Main Results:

• A novel SDPD formulation for ideal two-component mixtures was obtained.
• The multicomponent approach correctly reproduces fluctuations and diffusion dynamics.
• The framework successfully simulates molecularly miscible systems across various length scales.

Conclusions:

• The developed SDPD framework provides a robust tool for simulating multicomponent mixtures.
• This method accurately captures thermal fluctuations and diffusion across scales.
• It offers a validated approach for studying molecularly miscible systems from nano to continuum scales.