Preference Parameters for the Calculation of Thermal Conductivity by Multiparticle Collision Dynamics.

Area of Science:

• Computational physics
• Materials science
• Nanotechnology

Background:

• Molecular dynamics (MD) simulations for thermal conductivity are computationally intensive, limiting system size.
• Nanofluids require accurate thermal conductivity calculations for various applications.

Purpose of the Study:

• To investigate and optimize multiparticle collision dynamics (MPCD) parameters for accurate thermal conductivity calculations.
• To demonstrate the applicability of MPCD for simulating larger systems, including nanofluids.

Main Methods:

• Systematic parameterization of MPCD simulations, including bin size, number density, time-step, rotation angle, and temperature.
• Analysis of parameter influence on thermal conductivity calculations.
• Validation of the optimized MPCD method using liquid argon, water, and a Cu-water nanofluid.

Main Results:

• MPCD parameter selection significantly impacts thermal conductivity results.
• Accurate thermal conductivity calculations were achieved for liquid argon (3.4% error), water (1.5% error), and Cu-water nanofluid (1.2% error) compared to theoretical values.
• The optimized MPCD method enables simulation of larger systems with reduced computational workload.

Conclusions:

• MPCD is a viable and accurate method for calculating the thermal conductivity of nanofluids.
• The developed parameterization strategy enhances the reliability of MPCD simulations for thermal transport properties.
• This approach facilitates the study of thermal conductivity in larger, more complex nanoscale systems.