Predicting the phase behavior of fatty acid methyl esters and their mixtures using the GC-SAFT-VR approach

Abstract

Biodiesel fuels, which consist of a blend of long chain fatty acid methyl esters, have attracted increased interest in recent years as possible alternates to fuels derived from petroleum. An understanding of the thermophysical properties and phase behavior of these molecules are therefore important to the investigation and design of biodiesel processes; however, such data is limited making the development of molecular based modeling approaches that can accurately and reliably determine the thermophysical properties of fatty acid methyl esters an important research area. Here we apply the group contribution based statistical associating fluid theory for potential of variable range (GC-SAFT-VR) equation of state to the study of long chain fatty acid methyl esters that comprise biodiesel fuels. With minimal reliance on experimental data, the GC-SAFT-VR equation of state offers a predictive approach that allows for the description of heterosegmented chains to correlate and predict the phase behavior of pure associating and nonassociating fluids and their mixtures. Model parameters for the C=O, CH 3 , CH 2 , CH=CH2, OCH 2 , and OCH 3 functional groups and their cross interactions were taken from earlier work and used here in a transferable fashion to predict the thermophysical properties and phase behavior of pure fatty acid methyl esters and their mixtures with other fatty acid methyl esters, alcohols, and carbon dioxide. It is shown that the GC-SAFT-VR approach can be used as a purely predictive tool, without fitting any new model parameters, to accurately predict the phase behavior of the fatty acid methyl ester fluids and their mixtures studied.

Molecular Dynamics Simulations Study on the Shear Viscosity, Density, and Equilibrium Interfacial Tensions of CO2 + Brines and Brines + CO2 + n-Decane Systems

“…The group-contribution statistical associating fluid theory calculations for the segment−segment dispersion energy parameters (ε ij /k B ) showed CO 2 -CH 3 and CO 2 -CH 2 dispersion energy values of 204.95 and 206.25 K, respectively, in comparison to the CO 2 −water dispersion energy of 1575.2 K. 45 Therefore, the association energy of CO 2 −water has a tremendous effect on the reduction of IFT at the interface Figure 11 illustrates the comparisons between experimental IFT values 16 and the simulated values at the interface between water and the CO 2 −decane system, which are obtained from molecular dynamic simulations in the medium of high salinity.…”

“…The group-contribution statistical associating fluid theory calculations for the segment–segment dispersion energy parameters (ε ij / k B ) showed CO 2 -CH 3 and CO 2 -CH 2 dispersion energy values of 204.95 and 206.25 K, respectively, in comparison to the CO 2 –water dispersion energy of 1575.2 K . Therefore, the association energy of CO 2 –water has a tremendous effect on the reduction of IFT at the interface between the water and n -decane, because it acts as a Lewis acid increasing the electron donor–acceptor forces, which are responsible for lowering the IFT.…”

Heterosegmental Modeling of Long-Chain Molecules and Related Mixtures using PC-SAFT: 1. Polar Compounds

“…However, no prior averaging step is necessary due to the heterosegmental formalism. McCabe and co-workers obtained promising results applying GC-SAFT-VR to describe the vapor pressures and liquid densities of short-chain 44 and long-chain 50 methyl alkanoates as well as some n-aldehydes. 45 In 2014, Perdomo et al 51 modeled the same thermodynamic pure-component properties of some methyl alkanoates using SAFT-γ.…”

Modeling systems relevant to the biodiesel production using the CPA equation of state. Part 2. Systems with supercritical CO2

“…Finally, Haley and McCabe used a group contribution SAFT-VR (GC-SAFT-VR) model to predict the VLE of CO2 mixtures with methyl myristate, methyl oleate, methyl stearate, and methyl palmitate. Without using binary adjustable parameters (pure predictions), their model presented a satisfactory agreement with the experimental data away from the critical region, but resulted in an over prediction of the critical point, which is typical of all equations of state of this type [40].…”