Ind. Eng. Chem. Res. 2008, 47, 7441–7446
7441
Modeling Systems Containing Alkanolamines with the CPA Equation of State Ane S. Avlund, Georgios M. Kontogeorgis,* and Michael L. Michelsen Department of Chemical and Biochemical Engineering, Center for Phase Equilibria and Separation, Processes (IVC-SEP), Technical UniVersity of Denmark, DK-2800 Lyngby, Denmark
An association model, the cubic-plus-association (CPA) equation of state (EoS), is applied for the first time to a class of multifunctional compounds (alkanolamines). Three alkanolamines of practical and scientific significance are considered; monoethanolamine (MEA), diethanolamine (DEA), and methyl diethanolamine (MDEA). Vapor pressures and liquid densities, as well as solvatochromic parameters and mixture liquid-liquid equilibria (LLE) data with alkanes are used to estimate the five pure-compound parameters. Vapor-liquid equilibria (VLE) calculations for cross-associating mixtures, especially those with water, are used in the validation of the parameters. The influence on the results of the association scheme, cross-association combining rules, interaction parameters, and the data available is discussed also, in connection with other aqueous crossassociating mixtures previously studied using the CPA equation of state (alcohols, amines, and glycols). Introduction Alkanolamines are widely used in many different industries (e.g., in the oil industry, where aqueous solutions of alkanolamines are used to remove carbon dioxide (CO2) and hydrogen sulfide (H2S) from natural gas streams). The removal of CO2 from power plant flue gas using aqueous solutions of alkanolamines is expected to be applied on a very large scale within a few years. The cubic-plus-association (CPA) equation of state (EoS)1 has previously been applied to both self- and cross-associating mixtures that contain water, alcohols, amines, glycols, and hydrocarbons (see, e.g., refs 2-4); however, where the associating compounds listed here all only contain one type of functional group, alkanolamines contain both hydroxyl and amine groups. That feature makes them somewhat more complex to model. The main reasons for choosing the CPA method for this work are the simplicity of the model and the fact that it reduces to SRK for nonassociating compounds. This means that (i) purecomponent parameters are available for these compounds and (ii) the already-optimized interaction parameters between nonassociating compounds can be used. Moreover, as the petroleum industry knows and uses cubic equations of state, it is more willing to use CPA than other SAFT-type models. There are several studies available in regard to modeling CO2/ H2S-alkanolamine-water systems with equations of state (see, e.g., refs 5 and 6). Most of them uses an explicit electrolyte term. However, association models have only been applied to water-alkanolamine and alkanolamine-alkane systems in a few studies. Three alkanolamines are considered in this work: monoethanolamine (MEA), diethanolamine (DEA), and methyl diethanolamine (MDEA). (See Chart 1). These compounds are currently among the most important candidates for carbon dioxide removal from flue gas. Important available data that are in use for thermodynamic SAFT-type models are vapor pressures and liquid densities; however, for the three alkanolamines, the range of the typically used correlations from Design Institute for Physical Property (DIPPR) is much more extended than the actual experimental data from which the correlations were developed. This is a
limitation, and care should be exercised in the parameter regression in such cases. The DIPPR correlations8 for MDEA are based on a single density value; group contribution methods are used for the critical parameters, and data from these correlations were almost impossible to recorrelate with the CPA EoS. An experimental critical point for MDEA was published by vonNiederhausern et al. in 2006,7 along with some vapor pressure data. The experimental critical temperature deviates 10% from the predicted value. Therefore, new correlation constants for the vapor pressure and liquid density of MDEA were estimated based on these data, the data from DIPPR,8 and additional data published by Bernal-Garcia´ et al.9 and DiGuillo et al.10 DIPPR correlation constants were used for MEA and DEA. The constants are listed in Table 1. Figures 1 and 2 show experimental data and correlations of the vapor pressure and liquid density of the three alkanolamines considered in this work. The figures clearly show the lack of not only liquid density data for the alkanolamines, but also vapor pressure data for MDEA. The purpose of this work is to investigate the applicability of the CPA EoS to alkanolamines. The investigation is considered a first-level approach (i.e., explore the model’s capabilities under certain simplifying assumptions). No special treatment of polarity is considered, only the association term of CPA/SAFT is used. Existing association schemes, such as 2B and 4C,11 will be used without distinguishing the difference between N and O atoms in MEA, whereas the N atom in DEA and MDEA will be ignored. No intramolecular association will be considered either. Although we recognize the multifunctional Chart 1.
* To whom correspondence should be addressed. Tel.: +45 4525 2859. Fax: +45 4588 2258. E-mail address:
[email protected]. 10.1021/ie800040g CCC: $40.75 2008 American Chemical Society Published on Web 09/04/2008
7442 Ind. Eng. Chem. Res., Vol. 47, No. 19, 2008 Table 1. Correlation Constants for the Vapor Pressure (PS)a and Saturated Liquid Density (GL)b of Alkanolamines MEA
A B C D E Tmin Tmax maximum deviationc average deviationc a
DEA
MDEA
PS
FL
PS
FL
PS
FL
92.624 -10367 -9.4699 1.9 × 10-18 6 283.65 K 678.2 K 8.1% 2.1%
1.0011 0.22523 678.2 0.21515
106.38 -13714 -11.06 3.265 × 10-18 6 301.15 K 736.6 K 2.7% 0.8%
0.68184 0.23796 736.6 0.2062
94.165 -11725 -9.6087 2.298 × 10-18 6 252.15 K 741.9 K 6.7% 1.8%
0.73059 0.26538 741.9 0.27555
0.3% 0.1%
0.2% 0.1%
0.3% 0.1%
D
PS (Pa) ) exp[A + B/T + C ln(T) + DTE]. b FL (mol/L) ) A/{B[1+(1-T/C) ]}. c Deviations are between the experimental data and the correlations.
Figure 1. Comparison between the correlations (lines) for vapor pressure and experimental data (squares) (from refs 7 and 8) for MEA, DEA and MDEA.
Figure 2. Comparison between the correlations (lines) for liquid density and experimental data (squares) (from refs 8-10) for MEA, DEA and MDEA.
character of the alkanolamines, additional pure-component parameters will be needed to consider it. Parameter Estimation The CPA EoS has been presented in the literature; therefore, the equations will not be repeated here. A short description of the model is provided in Appendix A. The parameter sets estimated in this work are listed in Table 2. All parameters were regressed in the reduced temperature
range of Tr ) 0.55-0.90, where a significant amount of vapor pressure data is available. Unfortunately, only a few liquid density data points are located in that range. Previous studies2,4 have shown that the 2B scheme gives the best results for both alcohols and amines. MEA contains both a hydroxyl group and an amine group, and, therefore, it was chosen to investigate the 4C scheme for MEA (two sites to the hydroxyl group and two sites for the amine group). However, amines are known to associate weaker than alcohols, and, therefore, the 2B scheme was also investigated, meaning that the amine group was ignored and the hydroxyl group was given two sites. DEA and MDEA both contain two OH groups (as does MEG and other glycols) and an amine group, and the choice was made to ignore the amine group and use the 4C scheme, in agreement with the use of this scheme for glycols. Parameters initially were estimated in the usual way, from pure-component vapor pressure and liquid density data (PS and FL, respectively). Highly correlated parameter sets were obtained in this way and, therefore, additional data were needed to determine the optimal sets. As discussed in previous work (with glycols; Derawi et al.12), one way is to use LLE for the compound of interest and an inert compound (e.g., n-alkanes). Such LLE data are available for MEA with n-heptane and benzene and for DEA with hexadecane. For MEA, the association energy was fitted to the data for MEA-n-heptane simultaneously with the interaction parameter while the remaining four parameters were fitted to the purecomponent data. There was essentially no loss in the accuracy of PS and FL, compared to fitting only to the pure-component data. The mutual solubility of MEA and n-heptane modeled with CPA is shown in Figure 3. The figure shows that CPA satisfactorily correlates the experimental data using either the 2B or 4C association scheme for MEA. The most significant difference between the 2B and the 4C parameters in the modeling of this system is the value of the interaction parameter, which is significantly larger for the 2B scheme than for the 4C scheme, indicating that using the 4C scheme is more correct. The parameters obtained in this way was then used to model MEA-benzene. Figure 4 shows the results with the 4C parameter set. It is possible to match one of the solubilities when an interaction parameter is fitted, but it is necessary to account for solvation and also fit the cross-association volume (βAiBj) to match both solubilities satisfactorily (the modified CR-1 rule14). The parameters obtained from MEA-n-heptane performed better than those only fitted to pure-component data, and the 4C parameters gave significantly better results than the 2B parameters. A iB j The optimal value of βfitted for MEA-benzene is similar to the values for benzene/toluene-ethanol, whereas larger values (∼0.04-0.08) are needed for benzene/toluene-water/
Ind. Eng. Chem. Res., Vol. 47, No. 19, 2008 7443 Table 2. CPA Parameters for the Three Alkanolamines Investigated in This Work, over a Reduced Temperature Range of Tr ) 0.55-0.90a compound
association scheme
a0 [bar L2 mol-2]
b [L mol-1]
c1
ε [bar L mol-1]
β (× 103)
∆P%
∆F%
MEA MEA DEA MDEA
2B 4C 4C 4C
14.589 14.112 20.942 21.659
0.05534 0.05656 0.09435 0.11145
0.6218 0.7012 1.5743 1.3371
274.49 181.77 161.59 161.59
3.09 5.35 33.2 33.2
0.33 0.55 1.56 1.08
0.52 0.70 1.60 1.35
a
The errors in vapor pressure PS and liquid density FL are relative to the correlations.
Figure 3. MEA-n-heptane LLE with the 2B and 4C schemes for MEA and a fitted kij (experimental data taken from ref 13).
Figure 5. DEA-hexadecane LLE with an optimal interaction parameter (experimental data taken from ref. 16). Table 3. Kamlet-Taft Solvatochromic Parameters for the Three Alkanolamines Investigated in This Worka MEA
DEA
MDEA
R
β
R
β
R
β
0.39
0.72
0.60
0.67
0.49
0.60
a
R indicates the acidity, and β represents the basicity.
Figure 4. MEA-benzene LLE with the 4C scheme for MEA. Dotted line: CPA, kij ) 0; dashed line: CPA, kij ) -0.0065; solid line: CPA, kij ) 0.0016, and βAiBj ) 0.0067 (experimental data taken from ref 15).
MEG.14 This indicates that the effect of solvation is not as considerable in the systems that involve MEA or ethanol and an aromatic hydrocarbon as it is in the other systems. The same parameter estimation procedure was used for DEA, using the data for DEA-hexadecane, and the results are shown in Figure 5. Again, CPA satisfactorily correlates the mutual solubilities of the two compounds. Based on the results for these systems, the following can be concluded: (1) The use of LLE data is imperatively important in the parameter selection. (2) The 4C scheme for MEA performs better than the 2B scheme, and, thus, all three alkanolamines are treated as 4C molecules. (3) The MEA-benzene LLE is satisfactorily represented by accounting for solvation in a way similar to glycols or water with aromatics, using the modified CR-1 combining rule.
Figure 6. MDEA-methane VLE at five different temperatures (298.15, 313.15, 343.15, 373.15, and 403.15 K). Dotted line: kij ) 0; solid line: kij ) 0.164 (experimental data taken from ref. 18).
No LLE data were available for MDEA with an alkane, and, therefore, it was necessary to use other types of data to determine the optimal parameters. Kamlet-Taft solvatochromic parameters quantify the hydrogen bond donor and acceptor ability of a compound. Table 3 lists the values for the three alkanolamines. The values presented here are averages of those presented by Lagalante et al.17 The values of these parameters indicate that the association of MDEA and DEA should be similar (which is in accordance with the similar structure of the two). Therefore, the association parameters of MDEA were set equal to those of DEA, whereas the remaining parameters were fitted to the vapor pressure and liquid density data.
7444 Ind. Eng. Chem. Res., Vol. 47, No. 19, 2008 Table 4. kij Values and Errors in Bubble Point Pressure for Binary Cross-Associating Systems That Contain Alkanolamine CR-1 reference
T [K]
Nath and Bender19
Touhara et al.20 Nath and Bender19
Touhara et al.20 19
Nath and Bender
Horstmann et al.21
ECR ∆P%
kij
kij
∆P%
MEA(2B)-Ethanol System 338.15 -0.017 1.8 338.15 0 5.7 358.15 -0.017 2.1 358.15 0 7.3
-0.017 0
1.8 5.8
MEA(4C)-Ethanol System 338.15 -0.024 2.8 338.15 0 9.1 358.15 -0.024 2.9 358.15 0 10.9
-0.025 0
2.8 9.3
MEA(2B)-Water System 298.15 -0.281 7.4 0 101 364.85 -0.281 5.0 0 66
-0.34 0
9.4 143
MEA(4C)-Water System 298.15 -0.165 7.1 0 48 364.85 -0.165 3.7 0 41
-0.249 0
9.4 85
-0.33 0
9.1 70
DEA-Water System 365.15 -0.12 4.7 0 16
Figure 7. MEA (4C)-water VLE, at T ) 298.15 K. (Experimental data from ref. 20.)
Table 5. kij Values and Errors in Bubble Point Temperature and Vapor-Phase Composition for Binary Cross-Associating Systems Containing Alkanolaminesa reference Cai et al.22
Cai et al.22
Voutsas et al.23
a
∆T %
∆y1
MEA(2B)-Water System 1.0133 -0.281 0
0.54 2.6
0.0203 0.0770
MEA(4C)-Water System 1.0133 -0.165 0
0.46 1.3
0.0190 0.0385
DEA-Water System 0.0667 -0.12 0
2.2 3.4
0.108 0.140
MDEA-Water System 0.400 -0.087 0 0.533 -0.087 0
0.77 1.03 0.81 0.98
P [bar]
kij
Figure 8. DEA-water VLE, at P ) 0.0667 bar. Dashed line: prediction (kij ) 0); solid line: fitted (kij ) -0.087). (Experimental data from ref. 22.)
Results are only presented for CR-1.
A single system with an inert compound for MDEA (MDEA-methane) was used for validation, and very good results were obtained with a temperature-independent parameter kij, as can be seen in Figure 6. The figure shows that CPA predicts (kij ) 0) an incorrect temperature dependency for this system, and that this is corrected, when a temperature-independent interaction parameter fitted at T ) 298.15 K is used. Cross-Associating VLE Mixtures CPA was then applied to binary VLEs for cross-associating mixtures that contain alkanolamines, especially those with water. Such systems are important, for practical purposes, in the application of the model to CO2/H2S-water-alkanolamines, but also from a scientific point of view and for validating the model. CPA parameters for other associating compounds considered in this work are given in Appendix B. Tables 4 and 5 summarize some of the results obtained with various combining rules in the association term and different
Figure 9. MDEA-water VLE, at P ) 0.400 bar. Dashed line: prediction (kij ) 0); solid line: fitted (kij ) -0.087). (Experimental data from ref. 23.)
MEA schemes, as well as using kij ) 0 and temperatureindependent interaction parameters that have been fitted to the data. Figures 7-9 present some of the results obtained for each of the three alkanolamines.
Ind. Eng. Chem. Res., Vol. 47, No. 19, 2008 7445
Figure 7 shows MEA-water VLE at T ) 298.15 K, with the 4C parameter set. The figure shows results for two different combining rules for the association parameters: CR-1 and ECR (Elliott combining rule). It is evident from the figure that CR-1 performs better than ECR for this system, both for kij ) 0 and with a fitted kij value, and with a smaller absolute value of the interaction parameter. This was found to be the case for all the three alkanolamine-water systems. For water-ethanol, where the pure components have comparable molar volumes, the two combining rules as expected perform similarly. Figures 8 and 9 show the results for DEA-water and MDEA-water VLE, respectively, with CPA and the CR-1 rule. The figures show that CPA is capable of modeling these systems using the 4C scheme for both DEA and MDEA. Generally, CPA performs satisfactorily for this type of system, using a temperature-independent interaction parameter. However, the predictive performance is generally poor, and large negative values of the interaction parameter are usually needed. The conclusions for cross-associating systems, presented here, are in good agreement with results for similar systems previously obtained with CPA2-4 (e.g., water-glycol). Conclusion The CPA EoS has been applied to three alkanolamines (MEA, DEA, MDEA), as well as to cross-associating mixtures with water and ethanol. The investigation showed that purecomponent vapor pressures and liquid densities were not sufficient to obtain reliable parameters, but that at least one other type of information is needed. The 4C association scheme proved to be the best choice for MEA and was also used with success for DEA and MDEA. A temperature-independent interaction parameter gave satisfactory results for LLE and for alkanolamine-water VLE. However, large negative values were typically needed for the interaction parameter in the latter case, which is consistent with previous results for other aqueous cross-associating mixtures (e.g., water-alcohols and water-glycols). Despite the encouraging results obtained in this work, we do not consider the CPA parameters presented here to be final. The performance must be tested on additional systems, and other types of association schemes for alkanolamines must be investigated.
XAi is the mole fraction of molecule i not bonded at site A and xi is the mole fraction of component i. XAi is given by the following equation: XAi )
a(T) 1 RT RT × Vm - b Vm(Vm + b) 2 Vm ∂ (ln g) 1+F ∂F
(
)∑ x ∑ (1 - X ) i
i
Ai
Ai
j
Bj
AiBj Bj ∆
[ ( ) ]
εAiBj - 1 bijβAiBj RT
∆AiBj ) g(Vm)ref exp where g(Vm)ref )
1 1 - 1.9η
with η)
( )
1 b 4Vm
εAiBj and βAiBj are the association energy and volume, respectively. The energy parameter in the SRK part of the equation is given by a(T) ) a0[1 + c1(1 - √Tr)]
2
where Tr is the reduced temperature, T/Tc. The extension of the CPA EoS to mixtures requires mixing rules only for the parameters of the physical (SRK) part, while the extension of the association term to mixtures is straightforward. The mixing rules for a and b are the classical van der Waals one-fluid ones using combining rules aij ) (aiaj)1/2(1 kij) and bij ) (bi + bj)/2. When CPA is extended to mixtures with more than one associating compound combining rules are needed for the association parameters. Two different combining rules are used in this work; the Elliott (ECR) rule ∆AiBj ) √∆AiBi∆AjBj and the CR-1 rules εAiBi + εAjBj 2
and βAiBj ) √βAiBiβAjBj
For mixtures of an associating compound with an aromatic, Folas et al.14 proposed the modified CR-1 combining rule, where the cross-association energy is half-that of the associating compound, and the cross-association volume is fitted.
The CPA EoS for mixtures can be expressed in terms of pressure P as follows: P)
j
∆AiBj is the association strength between site A on molecule i and site B on molecule j, given by
εAiBj )
Appendix A. The CPA EoS
∑x∑X
where the summation over Bj is a summation over all sites.
Acknowledgment We wish to thank StatoilHydro (Norway) for their interest and support to this project.
1 1 1+ Vm
εAiBj )
εassociating 2
and βAiBj ) fitted
Appendix B. CPA Parameters The CPA parameters for other compounds used in this study are given in Table B1.
Table B1. CPA Parameters for Other Compounds Considered in This Work compound ethanol water
reference 2
Folas et al. Kontogeorgis et al.24
a0 [bar L2 mol-2]
b [L/mol]
c1
ε [bar L mol-1]
β (× 103)
∆P%
∆F%
8.6716 1.2277
0.049110 0.014515
0.73690 0.67359
215.32 166.55
8.00 69.2
1.3 0.8
0.3 0.5
7446 Ind. Eng. Chem. Res., Vol. 47, No. 19, 2008
Nomenclature List of AbbreViations CPA ) cubic-plus-association CR-1 ) combining rule 1 DEA ) diethanolamine ECR ) Elliott combining rule EoS ) equation of state Exp ) experimental LLE ) liquid-liquid equilibria MEA ) monoethanolamine MDEA ) methyldiethanolamine SAFT ) statistical associating fluid theory VLE ) vapor-liquid equilibria ∆P% ) average absolute deviation, defined as ∆P% ) (100/NP) NP ∑k)1 |(Pkexp - Pkcalc)/Pkexp| ∆T% ) average absolute deviation, defined as ∆T% ) (100/NP) NP ∑k)1 |(Tkexp - Tkcalc)/Tkexp| exp ∆y ) average absolute deviation, defined as ∆y ) (1/NP) ∑NP k)1|yi,k calc - yi,k | ∆F% ) average absolute deviation, defined as ∆p% ) (100/NP) NP ∑k)1 |(pkexp - pkcalc)/pkexp| List of Symbols a0 ) parameter in the energy term (a) (bar L2 mol-2) Ai ) site A in molecule i b ) covolume parameter (L mol-1) Bj ) site B in molecule j c1 ) parameter in the energy term (a) g ) radial distribution function kij ) binary interaction parameter P ) pressure T ) temperature Vm ) molar volume xi ) liquid mole fraction of component i XAi ) fraction of i molecules, not bonded at site A yi ) vapor mole fraction of component i Greek Letters R ) Kamlet-Taft solvatochromic parameter for the hydrogen bond donor ability (acid strength) β ) Kamlet-Taft solvatochromic parameter for the hydrogen bond acceptor ability (base strength) βAiBj ) association volume parameter between site A in molecule i and site B in molecule j ∆ ) association strength (L/mol) εAiBj ) association energy parameter between site A in molecule i and site B in molecule j (bar L mol-1) η ) reduced density F ) density (mol/L) Superscripts/Subscripts c ) critical L ) liquid r ) reduced S ) saturated
Literature Cited (1) Kontogeorgis, G. M.; Voutsas, E. C.; Yakoumis, I. V.; Tassios, D. P. An Equation of State for Associating Fluids. Ind. Eng. Chem. Res. 1996, 35 (11), 4310–4318. (2) Folas, G. K.; Gabrielsen, J.; Michelsen, M. L.; Stenby, E. H.; Kontogeorgis, G. M. Application of the Cubic-Plus-Association (CPA)
equation of state to cross-associating systems. Ind. Eng. Chem. Res. 2005, 44 (10), 3823–3833. (3) Derawi, S. O.; Kontogeorgis, G. M.; Michelsen, M. L.; Stenby, E. H. Extension of the cubic-plus-association equation of state to glycol-water cross-associating systems. Ind. Eng. Chem. Res. 2003, 42 (7), 1470–1477. (4) Kaarsholm, M.; Derawi, S. O.; Michelsen, M. L.; Kontogeorgis, G. M. Extension of the cubic-plus-association (CPA) equation of state to amines. Ind. Eng. Chem. Res. 2005, 44 (12), 4406–4413. (5) Vallee, G.; Mougin, P.; Jullian, S.; Fu¨rst, W. Representation of CO2 and H2S Absorption by Aqueous Solutions of Diethanolamine Using an Electrolyte Equation of State. Ind. Eng. Chem. Res. 1999, 38 (9), 3473– 3480. (6) Button, J. K.; Gubbins, K. E. SAFT prediction of vapour-liquid equilibria of mixtures containing carbon dioxide and aqueous monoethanolamine or diethanolamine. Fluid Phase Equilib. 1999, 158-160, 175– 181. (7) VonNiederhausern, D. M.; Wilson, G. M.; Giles, N. F. Critical Point and Vapour Pressure Measurements for 17 Compounds by a Low Residence Time Flow Method. J. Chem. Eng. Data 2006, 51 (6), 1990–1995. (8) American Insitute of Chemical Engineers, Design Institute for Physical Properties, DIADEM, 2007. (9) Bernal-Garcia´, J. M.; Ramos-Estrada, M.; Iglesias-Silva, G. A.; Hall, K. R. Densities and Excess Molar Volumes of Aqueous Solutions of n-Methyldiethanolamine (MDEA) at Temperatures from (283.15 to 363.15) K. J. Chem. Eng. Data 2003, 48 (6), 1442–1445. (10) DiGuillo, R. M.; Lee, R.-J.; Schaeffer, S. T.; Brasher, L. L.; Teja, A. S. Densities and viscosities of the ethanolamines. J. Chem. Eng. Data 1992, 37 (2), 239–242. (11) Huang, S. H.; Radosz, M. Equation of state for small, large, polydisperse, and associating molecules. Ind. Eng. Chem. Res. 1990, 29 (11), 2284–2294. (12) Derawi, S. O.; Michelsen, M. L.; Kontogeorgis, G. M.; Stenby, E. H. Application of the CPA equation of state to glycol/hydrocarbons liquid-liquid equilibria. Fluid Phase Equilib. 2003, 209 (2), 163–184. (13) Gustin, J.-L.; Renon, H. Heats of mixing of binary mixtures of N-methylpyrrolidone, ethanoamine, n-heptane, cyclohexane, and benzene by differential flow calorimetry. J. Chem. Eng. Data 1973, 18 (2), 164– 166. (14) Folas, G. K.; Kontogeorgis, G. M.; Michelsen, M. L.; Stenby, E. H. Application of the cubic-plus-association (CPA) equation of state to complex mixtures with aromatic hydrocarbons. Ind. Eng. Chem. Res. 2006, 45 (4), 1527–1538. (15) Sørensen, J. M.; Arlt, W. Liquid-Liquid Equilibrium Data Collection. 1, Binary Systems; Chemistry Data Series, Vol. 5; DECHEMA: Frankfurt/Main, Germany, 1995. (16) Abdi, M. A.; Meisen, A. Mutual Solubility of Hexadecane with Diethanolamine and with bis(hydroxyethyl)piperazine. J. Chem. Eng. Data 1998, 43 (2), 138–142. (17) Lagalante, A. F.; Spadi, M.; Bruno, T. J. Kamlet-Taft Solvatochromic Parameters of Eight Alkanolamines. J. Chem. Eng. Data 2000, 45 (2), 382–385. (18) Jou, F.-Y.; Mather, A. E. Solubility of Ethane in Aqueous Solutions of Monoethanolamine and Diethanolamine. J. Chem. Eng. Data 2006, 51 (3), 1141–1143. (19) Nath, A.; Bender, E. Isothermal vapor-liquid equilibria of binary and ternary mixtures containing alcohol, alkanolamine, and water with a new static device. J. Chem. Eng. Data 1983, 28 (4), 370–375. (20) Touhara, H.; Okazaki, S.; Okino, F.; Tanaka, H. M.; Ikari, K.; Nakanishi, K. Correlation of liquid-liquid equilibria for alcohol/hydrocarbon mixtures using the CPA equation of state. J. Chem. Thermodynam. 1982, 14, 145–156. (21) Horstmann, S.; Mougin, P.; Lecomte, F.; Fischer, K.; Gmehling, J. Phase equilibrium and excess enthalpy data for the system methanol + 2,2′-diethanolamine + water. J. Chem. Eng. Data 2002, 47 (6), 1496–1501. (22) Cai, Z.; Xie, R.; Wu, Z. Binary Isobaric Vapour-Liquid Equilibria of Ethanolamines + Water. J. Chem. Eng. Data 1996, 41 (5), 1101–1103. (23) Voutsas, E. C.; Vrachnos, A.; Magoulas, K. Measurement and thermodynamic modeling of the phase equilibrium of aqueous N-methyldiethanolamine solutions. Fluid Phase Equilib. 2004, 224 (2), 193–197. (24) Kontogeorgis, G. M.; V. Yakoumis, I.; Meijer, H.; Hendriks, E.; Moorwood, T. Multicomponent phase equilibrium calculations for watermethanol-alkane mixtures. Fluid Phase Equilib. 1999, 158-160, 201– 209.
ReceiVed for reView January 10, 2008 ReVised manuscript receiVed April 23, 2008 Accepted July 10, 2008 IE800040G
