Understanding alkanes and their properties is essential to produce superior oil and gas products. One of the most important properties of alkanes is their kinematic viscosity, yet this is poorly understood in pure alkanes.
Theoretical and computational methods have been developed to investigate alkanes’ viscosity variation with molecular structure, temperature and pressure. However, none of the semi-analytical methods, modern statistical methods, EMD or NEMD have been able to reliably model viscosity of all alkanes.
This paper presents two computational techniques that enhance current NEMD methods to study liquid density and kinematic viscosity of alkanes.
We perform molecular dynamics simulations to model density as a function of temperature for 74 alkanes with 5 to 10 carbon atoms and non-equilibrium molecular dynamics simulations in the NVT ensemble to model kinematic viscosity of 10 linear alkanes as a function of molecular weight, pressure, and temperature. To model density, we perform simulations in the NPT ensemble before applying correction factors to exploit the systematic error in the SciPCFF force field, and compare results to experimental values, obtaining an average absolute deviation of 3.4 g/l at 25°C and of 7.2 g/l at 100°C. We develop a sampling algorithm that automatically selects good shear rates at which to perform viscosity simulations in the NVT ensemble and use the Carreau model with weighted least squares regression to extrapolate Newtonian viscosity. Viscosity simulations are performed at experimental densities and show an excellent agreement with experimental viscosities, with an average percent deviation of -1% and an average absolute percent deviation of 5%. Future plans to study and apply the sampling algorithm are outlined.
Publication: Journal of Chemical Physics 153, 014102 (2020)
Title:”Enhancing NEMD with improved sampling of shear rates to model viscosity and correction of systematic errors in modelling density: Application to linear and light branched alkanes”
Authors: P. Santak & G.J. Conduit
Link / DOI: https://aip.scitation.org/doi/