Effect of correlation on viscosity and diffusion in molecular-dynamics simulations.

Area of Science:

• Computational Physics
• Materials Science
• Plasma Physics

Background:

• Material properties like diffusion and viscosity in warm dense matter (WDM) are crucial but computationally expensive to obtain.
• Traditional methods rely on lengthy quantum molecular dynamics (QMD) simulations using density functional theory (DFT).
• Accurate calculation of transport properties is essential for understanding WDM behavior.

Purpose of the Study:

• To develop a more efficient method for calculating mass transport properties in warm dense matter.
• To reduce the computational cost associated with lengthy QMD simulations.
• To analyze the functional form of autocorrelation functions (ACFs) for improved property extraction.

Main Methods:

• Fitting the time dependence of autocorrelation functions (ACFs) to extract transport properties.
• Utilizing Kohn-Sham or orbital-free density functional theory within quantum molecular dynamics simulations.
• Applying the fitting methodology to a dense correlated plasma of copper and a carbon-hydrogen mixture.

Main Results:

• The fitting procedure effectively reduces simulation duration and mitigates noise in long-time ACF behavior.
• Accurate estimation of diffusion and viscosity values was achieved using the ACF fitting method.
• Both copper plasma and the carbon-hydrogen mixture exhibited structured ACFs with multiple time scales.

Conclusions:

• Fitting autocorrelation functions provides a more efficient and accurate approach to determine mass transport properties in WDM.
• The developed methodology successfully characterizes transport properties in complex systems like dense plasmas and multi-component mixtures.
• This technique offers a valuable tool for future studies in warm dense matter physics and materials science.