(591f) Predicting the Phase Behavior of Fluids with Multiple Polar Groups Using the GC-SAFT-VR Equation of State | AIChE

(591f) Predicting the Phase Behavior of Fluids with Multiple Polar Groups Using the GC-SAFT-VR Equation of State

Authors 

McCabe, C., Vanderbilt University

Predicting the Phase Behavior of Fluids with Multiple Polar Groups Using the GC-SAFT-VR Equation of State

Gaurav Das,1 Jessica D. Haley1, and Clare McCabe1,2

1Department of Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN

2Department of Chemistry, Vanderbilt University, Nashville, TN

The statistical associating fluid theory1 is a popular molecular-based equation of state (EOS) that has been successfully applied to predict the thermodynamics and phase behavior of a wide range of fluid systems. In recent developments, group contribution approaches have been combined with the SAFT equation in order to develop more predictive models.  The GC-SAFT-VR2,3 equation is one such approach, based on the SAFT-VR equation in which attractive interactions are described through a potential of variable range (VR).  The GC-SAFT-VR EOS models chains composed of segments of different size and/or energy of interaction at both the monomer and chain levels of theory, thus molecules are described by heterosegmented chains in which each type of segment represents a functional group present in the molecule. Parameters for key functional groups (such as CH3, CH2, CH, CH2=CH, C=O, C6H5, ether and ester, OH, NH2, CH=O, COOH) have been obtained by fitting to experimental vapor pressure and saturated liquid density data and their transferability tested by comparing the theoretical predictions with experimental data for pure fluids and binary mixtures not included in the fitting process, as well as by studying the VLE and LLE of small molecules in polymer systems.4,5-7 In general the GC-SAFT-VR approach is found to predict the phase behavior of the systems studied in excellent agreement with experimental data without adjusting the group parameters to binary mixture data; however deviations were seen for some of the polymer systems studied which contained multiple polar groups. Here we incorporate an explicit dipolar term into the GC-SAFT-VR EOS following the work of Zhao and McCabe.  The new equation is tested through the study of fluorinated ether (HFE’s) molecules and their mixtures with alcohols, ethers, and ketones.

1.       A. Gil-Villegas, A. Galindo, P. J. Whitehead, S. J. Mills, G. Jackson and A. N. Burgess, "Statistical associating fluid theory for chain molecules with attractive potentials of variable range," J. Chem. Phys., 106, 4168-4186 (1997).

2.       C. McCabe, A. Gil-Villegas, G. Jackson and F. del Rio, "The thermodynamics of heteronuclear molecules formed from bonded square-well (BSW) segments using the SAFT-VR approach," Mol. Phys., 97, 551-558 (1999).

3.       Y. Peng, H. G. Zhao and C. McCabe, "On the thermodynamics of diblock chain fluids from simulation and heteronuclear statistical associating fluid theory for potentials of variable range," Mol. Phys., 104, 571-586 (2006).

4.       Y. Peng, K. D. Goff, M. C. dos Ramos and C. McCabe, "Developing a predictive group-contribution-based SAFT-VR equation of state," Fluid Phase Equilib., 277, 131-144 (2009).

5.       Y. Peng, K. D. Goff, M. C. dos Ramos and C. McCabe, "Predicting the Phase Behavior of Polymer Systems with the GC-SAFT-VR Approach," Industrial & Engineering Chemistry, 49, 1378-1394 (2010).

6.       M. C. dos Ramos and C. McCabe, "On the prediction of ternary mixture phase behavior from the GC-SAFT-VR approach: 1-Pentanol + dibutyl ether plus n-nonane," Fluid Phase Equilib., 302, 161-168 (2011).

7.       M. C. dos Ramos, J. D. Haley, J. R. Westwood and C. McCabe, "Extending the GC-SAFT-VR approach to associating functional groups: alcohols, aldehydes, amines and carboxylic acids," Fluid Phase Equilib., 306, 97-111 (2011).

See more of this Session: Thermophysical Properties and Phase Behavior V

See more of this Group/Topical: Engineering Sciences and Fundamentals