Transport properties of supercritical methane

Area of Science:

• Thermodynamics
• Fluid Dynamics
• Physical Chemistry

Background:

• Supercritical fluids exhibit unique properties between gas and liquid phases.
• Understanding molecular diffusion is key to predicting transport phenomena in supercritical methane.
• Previous studies have reported experimental data on molecular diffusion in supercritical methane across a wide pressure range.

Purpose of the Study:

• To compare experimental molecular diffusion data in supercritical methane with theoretical predictions from the Lennard-Jones model.
• To analyze the transition from gas-like to liquid-like dynamical behavior using the Stokes-Einstein-Sutherland relation.
• To differentiate between distinct transitions in transport properties and the rigid-fluid regime.

Main Methods:

• Comparison of experimental results with theoretical expectations based on the Lennard-Jones model.
• Application of the kinetic approach within the Chapman-Enskog approximation for low-pressure, low-density regimes.
• Utilization of the freezing density scaling approach for higher pressures and densities.
• Analysis of the Stokes-Einstein-Sutherland relation to link self-diffusion and shear viscosity.

Main Results:

• The kinetic approach is adequate in the low-pressure, low-density limit.
• The freezing density scaling approach effectively describes behavior at higher pressures and densities.
• A dynamical crossover is located near the experimentally observed transition to liquid-like molecular diffusion.
• Two distinct transitions are identified: the intersection of transport property asymptotes and the onset of the rigid-fluid regime.

Conclusions:

• The study provides a framework for understanding and predicting transport properties of supercritical methane.
• Distinguishing between different transition types clarifies conflicting definitions of dynamical crossover and the Frenkel line.
• The findings offer practical insights for supercritical fluid applications where experimental data is scarce.