Correspondence pubs.acs.org/IECR
Reply to “Comments on ‘Comparison of the a Priori COSMO-RS Models and Group Contribution Methods: Original UNIFAC, Modified UNIFAC(Do), and Modified UNIFAC(Do) Consortium’” Jürgen Gmehling,*,† Zhimin Xue,‡ and Tiancheng Mu*,‡ †
Department of Industrial Chemistry, Institute for Pure and Applied Chemistry, Carl von Ossietzky University of Oldenburg, D-26111, Oldenburg, Germany ‡ Department of Chemistry, Renmin University of China, 100872, Beijing, People’s Republic of China
T
equation of state PSRK (VTPR). If the required group interaction parameters are missing, today, thanks to the work of Dr. A. Klamt, the different versions of COSMO-RS are the next choice. For the chemical engineer using the predictive methods, not only is access to these methods important, but reliable information about the quality of the predicted results and the weaknesses of the different predictive methods also is valuable. Therefore, it was always my interest to inform the chemical engineer about the quality and weaknesses of the published predictive methods. For example, in the literature,1 the strengths and weaknesses of the predictive models developed in my group (UNIFAC, modified UNIFAC, PSRK, VTPR, etc.) are described in detail. As a continuation of our model comparisons, it was the task of Prof. T. Mu during his research stay in my research group (Industrial Chemistry, University of Oldenburg, Germany) to check the results of the COSMO-RS-models available in my group with results of the group contribution methods original UNIFAC and modified UNIFAC, using a very comprehensive database (Dortmund Data Bank). The results are given in this paper. It did not surprise us that the results of modified UNIFAC for the presented data (VLE, excess enthalpies, activity coefficients) are superior, compared to the results of the COSMO-RS versions considered. However, for a few cases, the best results are also found for the COSMO-RS versions (see tables in the Supporting Information of the original paper).4 At the same time, T. Mu also looked at the weaknesses of the different predictive models. The main weaknesses of the COSMO-RS models are, e.g.,
he main interest of my research was always the computerdriven synthesis, design, and simulation of chemical processes, where, because of the great importance for chemical industry in particular, separation processes are considered. A prerequisite for this work is a reliable knowledge of the thermophysical properties of pure compounds and their mixtures. For the development and design of separation processes, in particular, phase equilibria (vapor−liquid equilibria (VLE), liquid−liquid equilibria (LLE), solid−liquid equilibria, gas solubilities, etc.) are required. Since, for the existing models (gE-models, equations of state), only a very small amount of the binary data is available, the development of reliable predictive methods with a large range of applicability is most desirable for this work.1 Most important for the development of a reliable predictive model with a large range of applicability is a comprehensive factual databank. Therefore, in 1973, I (J.G.) already started with the creation of a factual data bank, later called the Dortmund Data Bank (DDB) by Aage Fredenslund/LyngbyDenmark. At the beginning, only VLE data were stored. Later, all other phase equilibria, excess and transport properties, and pure component properties for nonelectrolytes and electrolytes also were added. In the meantime, it has become the largest factual databank worldwide and is used not only by most chemical and petroleum companies, but also engineering companies for their daily work.2 With the help of the Dortmund Data Bank, various powerful predictive models, such as UNIFAC, modified UNIFAC, PSRK, VTPR, LIQUAC, LIFAC, COSMO-RS (Ol), Kow-UNIFAC, and Pharma-modified UNIFAC for nonelectrolyte and electrolyte systems were developed. Because of the reliable results obtained and the large ranges of applicability, most of them were directly implemented in commercial process simulators. Because of the importance for industry, the predictive models UNIFAC, modified UNIFAC, and PSRK have been further revised and extended in the so-called UNIFAC consortium.3 This consortium started in 1996 and was run until my retirement March 31, 2011, at the University of Oldenburg. Because of the importance for industry and the great interest of the consortium members, it is now continued by DDBST GmbH.2 Usually, for the chemical engineer, the first choice during the design and synthesis of the different separation processes is the use of reliable experimental data. If the required experimental data are missing, the next choice is the use of the group contribution modified UNIFAC or the group contribution © 2012 American Chemical Society
• problems with asymmetric systems (combinatorial part) • a poor consideration of dispersive forces • too-simplified description of hydrogen bonding effects These were also reported in our previously published paper.5 Also, the poor results for the COSMO-RS flavors for perfluoroalkane−alkane systems were mentioned by Grensemann,6 who, in his Ph.D. thesis, introduced the dual sigmaprofile for systems with ethers, etc. to improve the results of the COSMO-RS method. It is correct that we have not used COSMOtherm from the company of A. Klamt (Cosmologic GmbH & Co KG): we had no access to his program. Unfortunately, in contrast to UNIFAC, modified UNIFAC, PSRK, and the other predictive Published: October 8, 2012 13541
dx.doi.org/10.1021/ie3024142 | Ind. Eng. Chem. Res. 2012, 51, 13541−13543
Industrial & Engineering Chemistry Research
Correspondence
for the calculation of API solubilities in solvent and solvent mixtures.17 The model comparison in this paper was limited to thermophysical properties of interest in chemical engineering (VLE, hE, γ∞), which means thermophysical properties that can be predicted using a gE-model. Of course, we also would be able to perform a model comparison for octanol−water-partition coefficients, the solubility of pharmaceutical, flash points, etc. Using the group contribution equations of state PSRK and VTPR, we could even extend the comparison to phase equilibria with supercritical compound (gas solubilities, phase equilibria for supercritical extraction processes), densities, caloric properties, Joule-Thomson coefficients, etc. By the way, I am convinced that, within a few years, group contribution equations of state,18,19 because of their great advantages, may replace the predictive gE-models (UNIFAC, COSMO-RS) in chemical engineering. In his comments, A. Klamt compares the results shown in the figures of the article with the results observed with the current version of his approach. I (J.G.) asked colleagues to calculate the VLE behavior of the perfluorohexane−n-hexane system at 318.15 K, using the current software from COSMOlogic. Surprisingly, the results received do not agree with the results shown by Dr. A. Klamt in Figures 5 and 6 of his comment paper.20 The results obtained from the colleagues show a heterogeneous azeotrope with a large miscibility gap. Without any doubt, the various COSMO-RS versions are useful tools, if experimental data and group interaction parameters are missing. However, if the group interaction parameters are available, group contribution methods will always be more accurate than a priori predictive models, as shown in this paper. For the chemical engineer, it is most important to obtain good agreement with reliable experimental data (separation factors, activity coefficients at infinite dilution, excess enthalpies, etc.). Thereby, the number of parameters used for the calculation is less important for the chemical engineer. The fact that no additional parameters are used (the basic parameters of the COSMO-RS method were also fitted to experimental data) is an advantage but, at the same time, a disadvantage for the different COSMO-RS versions, since not all of the interactions can be taken into account correctly. Furthermore, with COSMO-RS, problems with the selection of the best sigma profile (choice of the conformer) already occur. Prof. Dr. W. Arlt21 shows that the activity coefficients at infinite dilution can vary by a factor of 10, depending on the conformer (sigma profile) chosen, such as that observed in the case of the 2,3-butanediol−water system.
models developed in my group, the equations and parameters for the different terms of his COSMOtherm model have not been published. Klamt is correct that the Dortmund Data Bank was used to fit the parameters of the group contribution methods. The Dortmund Data Bank contains nearly all the worldwide available data. The use of a comprehensive database, of course, is most desirable for fitting reliable group interaction parameters and for a comprehensive model comparison. However, the parameters for modified UNIFAC were already fitted approximately 20−25 years ago.7,8 At this time, the Dortmund Data Bank only contained 35% of the experimental data stored in the databank today. This means that, for the results shown in the manuscript, at least 65% of the binary systems and data were not used for fitting the group interaction parameters. It is slightly different for the modified UNIFAC parameters fitted for the consortium. The consortium was started in 1996. However, a great part of the consortium parameters and, of course, the required equations were published.9−15 Since VLE and activity coefficients are only available for liquid compounds with at least a low vapor pressure, the number of compounds (groups) is limited to these compounds. However, I estimate that, thanks to the comprehensive databank (DDB), data for more than 1000 compounds and their binary mixtures were taken into account. We do not agree that the UNIFAC methods cannot take into account strong interactions and show problems with more complex molecules. On his company’s home page, Dr. A. Klamt shows the results for the system 2-cyanoethanol−3-ethoxypropionitrile and mentions that his COSMOtherm from COSMOlogic is able to resolve the very small differences in electronic effects of the isomers. However, the isomeric system considered is an ideal system, which can be calculated using Raoult’s law with the same accuracy. The weaknesses of the group contribution methods UNIFAC and modified UNIFAC are discussed in the literature.1 However, most of the weaknesses observed for the group contribution methods are also obtained for the COSMORS versions, e.g., also a miscibility gap is calculated for the homogeneous system tert-butanol−water, using the different COSMO-RS versions. Because of our long experience with the measurement and the quality of the published activity coefficients at infinite dilution, very large “experimental” values were not used for the model comparison. The reason is that a great part of the activity coefficients at infinite dilution with large values are often unreliable, e.g., the published γ∞ values of n-hexane in water vary between 2600 and 588 000 at 298 K. Also, often very poor large γ∞ values were measured by liquid−liquid chromatography. Unfortunately, in contrast to VLE, the γ∞ values reported cannot be checked for thermodynamic consistency. This is the reason that these data were not used for the model comparison. The reason that a special UNIFAC matrix for the calculation of octanol−water partition coefficients (Kow-UNIFAC) and Pharma-mod. UNIFAC were developed is not because of problems with the modification, but the idea to reduce the number of parameters drastically. In Kow-UNIFAC, for example, only the parameters between the functional groups and water and octanol, i.e., between the “CH2”, “OH”, and “H2O” groups, are used.16 A similar procedure was also applied
■
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected] (J.G.), tcmu@ chem.ruc.edu.cn (T.M.). Notes
The authors declare the following competing financial interest(s): The senior author (J.G.) is CEO of DDBST GmbH, which is responsible for the update of the Dortmund Data Bank and the integrated software package. Since the retirement of J.G. on April 1, 2011, DDBST GmbH is also responsible for the further development of the UNIFAC methods within the UNIFAC consortium. 13542
dx.doi.org/10.1021/ie3024142 | Ind. Eng. Chem. Res. 2012, 51, 13541−13543
Industrial & Engineering Chemistry Research
■
Correspondence
(21) Arlt, W. Experience with COSMO-RS, Melbourne, Australia, April 2006; available via the Internet at http://www.docstoc.com/docs/ 101112505/arlt030306.
REFERENCES
(1) Gmehling, J.; Kolbe, B.; Kleiber, M.; Rarey, J. Chemical Thermodynamics for Process Simulation; Wiley−VCH: Weinheim, Germany, 2012. (2) Dortmund Data Bank and DDB Software Package, DDBST GmbH, Oldenburg, Germany, 2008 (www.ddbst.de). (3) UNIFAC consortium. Accessible via the Internet at www.unifac. org. (4) Xue, Z.; Mu, T.; Gmehling, J. Comparison of the a Priori COSMO-RS Models and Group Contribution Methods: Original UNIFAC, Modified UNIFAC(Do), and Modified UNIFAC(Do) Consortium. Ind. Eng. Chem. Res. 2012, 51, 11809−11817. (5) Mu, T.; Rarey, J.; Gmehling, J. Performance of COSMO-RS with sigma profiles from different model chemistries. Ind. Eng. Chem. Res. 2007, 46 (20), 6612−6629. (6) Grensemann, H.; Gmehling, J. Performance of a conductor-like screening model for real solvents model in comparison to classical group contribution methods. Ind. Eng. Chem. Res. 2005, 44 (5), 1610− 1624. (7) Weidlich, U.; Gmehling, J. A Modified UNIFAC Model. 1. Prediction of VLE, hE, and γ∞. Ind. Eng. Chem. Res. 1987, 26 (7), 1372−1381. (8) Gmehling, J.; Li, J. D.; Schiller, M. A Modified UNIFAC Model. 2. Present Parameter Matrix and Results for Different Thermodynamic Properties. Ind. Eng. Chem. Res. 1993, 32 (1), 178−193. (9) Gmehling, J.; Lohmann, J.; Jakob, A.; Li, J. D.; Joh, R. A modified UNIFAC (Dortmund) model. 3. Revision and extension. Ind. Eng. Chem. Res. 1998, 37 (12), 4876−4882. (10) Gmehling, J.; Wittig, R.; Lohmann, J.; Joh, R. A modified UNIFAC (Dortmund) model. 4. Revision and extension. Ind. Eng. Chem. Res. 2002, 41 (6), 1678−1688. (11) Wittig, R.; Lohmann, J.; Joh, R.; Horstmann, S.; Gmehling, J. Vapor−liquid equilibria and enthalpies of mixing in a temperature range from 298.15 to 413.15 K for the further development of modified UNIFAC (Dortmund). Ind. Eng. Chem. Res. 2001, 40 (24), 5831−5838. (12) Lohmann, J.; Joh, R.; Gmehling, J. From UNIFAC to modified UNIFAC (Dortmund). Ind. Eng. Chem. Res. 2001, 40 (3), 957−964. (13) Lohmann, J.; Gmehling, J. Modified UNIFAC (Dortmund): Reliable model for the development of thermal separation processes. J. Chem. Eng. Jpn. 2001, 34 (1), 43−54. (14) Wittig, R.; Lohmann, J.; Gmehling, J. Prediction of phase equilibria and excess properties for systems with sulfones. AIChE J. 2003, 49 (2), 530−537. (15) Jakob, A.; Grensemann, H.; Lohmann, J.; Gmehling, J. Further development of modified UNIFAC (Dortmund): Revision and extension 5. Ind. Eng. Chem. Res. 2006, 45 (23), 7924−7933. (16) Wienke, G.; Gmehling, J. Prediction of octanol-water partition coefficients, Henry-coefficients and water solubilities using UNIFAC. Toxicol. Environ. Chem. 1998, 65, 57−86. Erratum, Toxicol. Environ. Chem. 1998, 67, 275. (17) Diedrichs, A.; Gmehling, J. Solubility calculation of active pharmaceutical ingredients in alkanes, alcohols, water and their mixtures using various activity coefficient models. Ind. Eng. Chem. Res. 2011, 50 (3), 1757−1769. (18) Ahlers, J.; Gmehling, J. Development of a universal group contribution equation of state. III. Prediction of vapor−liquid equilibria, excess enthalpies, and activity coefficients at infinite dilution with the VTPR model. Ind. Eng. Chem. Res. 2002, 41 (23), 5890− 5899. (19) Schmid, B.; Gmehling, J. The universal group contribution equation of state VTPR present status and potential for process development. Fluid Phase Equilib. 2011, 302 (1−2), 213−219. (20) Klamt, A. Comment on “Comparison of the a Priori COSMORS Models and Group Contribution Methods: Original UNIFAC, Modified UNIFAC(Do), and Modified UNIFAC(Do) Consortium”. Ind. Eng. Chem. Res. 2012, DOI: 10.1021/ie302247q. 13543
dx.doi.org/10.1021/ie3024142 | Ind. Eng. Chem. Res. 2012, 51, 13541−13543
