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Application of GC-PC-SAFT EoS to Organic Sulfur Compounds
Fan Zhang, Elise El Ahmar, Chien-Bin Soo, Xavier Canet, Christophe Coquelet
To cite this version:
Fan Zhang, Elise El Ahmar, Chien-Bin Soo, Xavier Canet, Christophe Coquelet. Application of GC-PC-SAFT EoS to Organic Sulfur Compounds. Équations d’état en thermodynamique: des équations cubiques aux équations issues de la thermodynamique moléculaire, Oct 2015, Toulouse, France. �hal-01251077�
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Application of GC-PC-SAFT EoS to Organic
Sulfur Compounds
Fan Zhang 1,2, Elise El-Ahmar 1, Chien-Bin Soo 2, Xavier Canet 2, Christophe Coquelet 1 1. Mines ParisTech, PSL – Research University, CTP - Centre Thermodynamique des Procédés,
35 rue St Honoré, 77305 Fontainebleau Cedex, France
2. PROCESSIUM, CEI 3 - CS 52132, 62 Boulevard Niels Bohr, 69603 Villeurbanne Cedex, France
Équations d'état en thermodynamique: des équations cubiques aux équations issues de la thermodynamique moléculaire E-mail: fan.zhang@mines-paristech.fr
christophe.coquelet@mines-paristech.fr
Design and optimization of separation processes require accurate knowledge of the thermodynamic properties and phase equilibria of involved pure compounds and mixtures. Thermodynamic models are thus needed to determine these properties. Model development relies on not only appropriate theory but also experimental data. However, for the organic sulfur compounds which are commonly found in diverse industrial sectors, few or even no experimental data exist in the literature. Therefore, models with predictive features may act as an alternative to handle engineering purposes.
Statistical Associating Fluid Theory (SAFT) equation of states (EoS) has been proved to be a powerful tool for modeling phase equilibria, as statistic mechanics and molecular theory were incorporated into the development. In this work, the Perturbed-Chain SAFT (PC-SAFT) EoS [1] was combined with the Group Contribution method proposed by Tamouza et al. [2]. The predictive model (named GC-PC-SAFT) was applied to investigate two series of typical organic sulfur compounds: sulfide (R-S-R’) and 1-thiol (R-SH). The group parameters of (S) and (SH) were fitted to vapor pressure and liquid density data (from [3]) of 9 sulfides and 7 1-thiols, respectively. The regression results show that the average deviations on vapor pressure are generally lower than 5%, while those on liquid density are generally lower than 2%.
Introduction
GC-PC-SAFT EoS
Reference
Conclusion & Perspective
Application of GC-PC-SAFT EoS with a dipolar term to investigate the sulfides and 1-thiols Good correlation and prediction of pure compound properties (AAD generally less than 5%) Satisfactory prediction of mixture VLE and hE data without any binary interaction parameters (k
ij=0)
Prediction for multi-compound systems Improvement in representing the solvation Extension to other organic sulfur compounds
Results
[1]: J. Gross, G. Sadowski, Ind.Eng.Chem.Res., 40 (2001) 1224. [2]: S. Tamouza et al., Fluid Phase Equilibr., 222–223 (2004) 67.
[3]: C. Yaws, Chemical Properties Handbook; McGraw-Hill: USA, 1999. [4]: P. K. Jog, W. G. Chapman, Mol. Phys., 97 (1999) 307.
[5]: ThermoDataEngine, NIST, USA, 2008.
[6]: E. Sapei et al., J. Chem. Eng. Data 52 (2007) 192.
[7]: S. Didaoui-Nemouchi, A. Ait Kaci, J. Therm. Anal. Calorim. 69 (2002) 669. [8]: N.F. Giles et al., J. Chem. Eng. Data. 42 (1997) 1067.
[9]: E. Sapei et al. Fluid Phase Equilibr. 301 (2011) 200. [10]: Z. Ferhat-Hamida et al. J. Chim. Phys. 76 (1979) 130.
Segment energy ε
Segment number m
Dipole moment μ
Dipolar segment number xpm
Chain formation
Dispersion Dipolar term from Jog
and Chapman [4] Association Hard spherical segment Segment diameter σ εAB κAB PC-SAFT EoS [1]
Pure compound parameters CH2
Group Contribution method of Tamouza et al. [2]
CH3 S Group parameters {mi, σi, εi} SH CH2 CH3 S SH CH2 CH2 CH3 CH3
•m(S) depends on the position of (S) •{μ, xpm} are applied directly to the entire molecule
•1-thiols are considered as non auto-associative 1.E-01 1.E+00 1.E+01 1.E+02 1.E+03 1.E+04 1.E+05 1.E+06 1.5 2.5 3.5 P sat [Pa] 1000/T [1/K]
Prediction of vapor pressure data (from [5]) C1SC5 C2SC8 C5SC5 C6SC6 C8SC8 GC-PC-SAFT 100 200 300 400 150 250 350 liqu id heat capacit y at P sat [J/m ol/K] T [K]
Prediction of heat capacity data (from [5]) C3SH C4SH C5SH C6SH C7SH C10SH GC-PC-SAFT 0 100 200 300 400 500 600 700 800 0.5 0.6 0.7 0.8 0.9 1.0 0 0.5 1 h E [J/ mo l] P [b ar ] x, y C2SC2 Prediction for C2SC2 + nC7 (kij=0)
Sapei et al. [6] GC-PC-SAFT Didaoui-Nemouchi and Ait Kac [7]
0 2 4 6 8 10 12 14 16 18 20 0 0.5 1 P [b ar] x, y C3SH Prediction for C3SH + nC4 (kij=0)
GC-PC-SAFT Giles et al. [8]
0.5 0.6 0.7 0.8 0.9 1.0 1.1 0 0.5 1 P [b ar] x, y C2SC2
Prediction for C2SC2 + C3OH (kij=0)
Sapei et al. GC-PC-SAFT without solvation
GC-PC-SAFT with solvation [9] Solvation 0 100 200 300 400 500 600 700 0 0.5 1 h E [J/m ol] x C3SC3
Prediction for C3SC3 + n-alkane (kij=0)
+ nC6 + nC8 + nC12
+ nC16 GC-PC-SAFT
[10] [10] [10]
[10]
26th – and 27th October 2015 at Toulouse, France
680 700 720 740 760 780 800 820 840 300 350 400 450 500 ρ liq [kg /m 3 ] T [K]
Prediction of saturated liquid density data (from [5]) C2SC8 GC-PC-SAFT 20 30 40 50 60 70 80 90 250 400 550 Enth alpy of v apo riz at ion [kJ/mo l] T [K]
Prediction of enthalpy of vaporization data (from [5])
C1SC1 C1SC2 C1SC3
C2SC2 C2SC8 C8SC8
