Ind. Eng. Chem. Res. 2005, 44, 7043-7044
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Rebuttal to the Comments of Andreas Klamt on “Performance of a COSMO-RS Model in Comparison to Classical Group Contribution Methods” H. Grensemann and J. Gmehling* Department of Industrial Chemistry, University of Oldenburg, D-26111 Oldenburg, Germany
Sir: We are not in agreement with the remark of Dr. Klamt that, because of biased decisions, the results presented are not objective. 1. In contrast to the statement of Dr. Klamt, the improvements published after 1995 were taken into account in COSMO-RS(Ol). For example, the multiplesegment descriptor generalization was exploited in particular for systems with ionic liquids because for these systems distinct improvements were observed. For other systems, like ethanol-water, etc., no real improvement was observed. Therefore, ignoring the multiple-segment descriptor generalization is justified. 2. Unfortunately, in the literature not too many COSMO-RS versions were published. Often, it is also impossible to figure out whether, in all cases, e.g., nonpolar, polar, and aqueous systems, the same parameters were used by the authors. Of course, it is no problem to correct the activity coefficients that are too high in the case of the system ethanol-water by using special parametrizations. In our paper, all results were predicted with the same set of parameters, listed in Tables 1 and 2 of the publication. By the way, with the modification introduced, this means that when going from COSMO-RS(Ol)* to COSMO-RS(Ol), the results obtained for the system ethanol-water are better than the results of COSMO-SAC. Unfortunately, no comparison with the versions of Klamt is possible because the required parameters are not available to us and the recent development state (equations, parameters, etc.) of the commercial software package were not published up until now. 3. The objective of the paper is to give the chemical engineer an idea about the quality of the different predictive gE models that can be applied for the synthesis, design, and optimization of chemical processes. For a comprehensive comparison, of course only reliable experimental data should be used. Therefore, in the case of vapor-liquid equilibrium (VLE), only data that passed two thermodynamic consistency tests were used for the comparison. To be able to compare the results of the different models at the same time, a common database is required. Because the parameter matrix of the ASOG and modified UNIFAC(Ly) is smaller than the one for the original UNIFAC and modified UNIFAC(Do), not all of the consistent VLE data were applied to the comparison. However, even the ASOG parameter matrix contains 47 functional groups. In the case of modified UNIFAC, 21 structural groups are covered. This means that not only data for “simple” systems were taken into account. From other investigations, we can tell that even the solubility of complex pharmaceuticals is described distinctly better with modified UNIFAC(Do) than with the COSMO-RS(Ol) approach.
4. The database for the activity coefficients was not chosen arbitrary at all. The reasons for excluding systems with very high activity coefficients are described in detail. Unfortunately, no thermodynamic consistency test exists to exclude questionable activity coefficients. Because very high activity coefficients often vary by an order of magnitude such as, for example, those for hydrocarbon-water systems (see the example hexane-water below), they cannot be used for a sound model comparison. That was the reason to exclude systems with activity coefficients larger than 500. A statistic also showed that with higher cutoff values the deviations of all models increased by nearly the same factor. Therefore, again the group contribution methods are not favored by excluding systems with very high activity coefficients. By the way, it is not a problem to reliably describe the high activity coefficients, e.g., of alkanes in water with the group contribution concept, when the parameters are only used to describe the γ∞ values as in the case of Putnam et al.1 This means that it is not a problem to achieve at least the same quality of the γ∞ results as shown by Putnam et al.1 However, with the group contribution methods, not only γ∞ but also other phase equilibria [VLE, liquid-liquid equilibria (LLE), solid-liquid equilibria (SLE), azeotropic data, etc.] and excess enthalpies should be described. This was already described in different papers published by one of the authors (J.G.).2-4 The problems arise when changing an H atom in hexane to an OH group; all of a sudden, instead of an activity coefficient of 35 000502 000 (range of the published γ∞ values at 298 K) for hexane, a value of around 550-1050 (range of the published γ∞ values at 298 K) should be achieved for hexanol in water. At the same time, the azeotropic composition should be approximately 90 mol % at atmospheric pressure and the azeotropic point should disappear below 30 °C for the system ethanol-water. Furthermore, the C1-C3 alcohols should be miscible, while starting from the C4 alcohols, a miscibility gap should be formed. This is the reason that VLE data of alcohol-water systems were used to fit the required alkane-water, alkane-alcohol, and alcohol-water group interaction parameters simultaneously. Maybe because of these weaknesses already mentioned in different papers2-4 of one of the authors (J.G.), a lot of research groups like to use alkane-water systems to show the γ∞ improvements that can be achieved with their “new” model in comparison with modified UNIFAC(Do). 5. As described in the paper in detail, all systems with hE values < 10 J/mol and all systems containing only increments from one main group (e.g., hydrocarbonhydrocarbon systems) were excluded from the model comparison. However, that has no influence on the results of the comparison. In Table 1, the results are
10.1021/ie050523l CCC: $30.25 © 2005 American Chemical Society Published on Web 07/12/2005
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Ind. Eng. Chem. Res., Vol. 44, No. 17, 2005
Table 1 data sets COSMO-RS(Ol) modified UNIFAC(Do)
all (8192) |400 J/mol| (5226) all (8192) |400 J/mol| (5226)
∆hEabs,
∆hErel,
279 134 361 134 61 175
60.1 109.3 32.2 32.2 61.9 15.4
J/mol
%
listed, when all systems, only systems with absolute E E < |400 J/mol|, and only systems with hmax > |400 hmax J/mol| were considered for the comparison. In all three cases, not only the relative deviations but also the absolute deviations of COSMO-RS(Ol) are nearly twice as high as the relative deviations achieved using modified UNIFAC(Do). This means that the results presented in the paper are not unfavorable for the evaluation of the performance of the COSMO-RS(Ol) approach. The opposite is true because also alkane-cycloalkane systems were excluded from the comparison. For these systems, poor results are obtained for the COSMORS(Ol) approach. It delivers negligible hE, while with the help of modified UNIFAC(Do), good results are obtained, as can be recognized from Figure 12B in the paper. 6. It is true and everyone knows that reliable experimental data (VLE, hE, cEP , γ∞, azeotropic data, SLE, and sometimes LLE) are needed to fit the required group interaction parameters. If possible, a large temperature range should be covered, and at the same time, a database with various compounds, e.g., very different in size, should be used. For example, to fit modified UNIFAC(Do) parameters for alkane-ketone systems, all reliable data for systems of C3-C32 alkanes and C3C35 ketones in the temperature range from 113 to 500 K stored in the Dortmund Data Bank were taken into account to fit the two temperature-dependent alkaneketone parameters (in total, four parameters). This means that as the database for fitting the alkaneketone parameters in total 337 data sets (consistent VLE, hE, SLE, cEP , and LLE) and 533 azeotropic data and activity coefficients at infinite dilution were used. Furthermore, it has to be mentioned that the parameters for the basic groups that are also covered by the modified UNIFAC(Ly) and ASOG model were mainly fitted approximately 15 years ago. Since then, of course also data for a large number of new systems were included in the Dortmund Data Bank. While, e.g., in 1990, 13 300 VLE and 6 000 hE data sets of normal boiling substances were stored, now 25 400 VLE and 17 500 hE data sets are available. Furthermore, it has to be mentioned that experimental information is also
used to fit the necessary model parameters for the COSMO-RS(Ol) approach. Dr. Klamt is correct that the sum and not the difference of the screening charge densities is used as described in eq 1. He is also correct that there is a misprint in eq 25. The integration constant should be η′ and not η. However, the cross correlation is taken into account by eqs 22-25 because eq 24 reduces to eq 23 for surface segment pairs with only electrostatic interactions. Acknowledgment We are grateful to DDBST GmbH, which allowed us to use the Dortmund Data Bank for the further development of thermodynamic models, such as modified UNIFAC,5 group contribution equations of state, and electrolyte models, but, of course, we are not allowed to distribute the Dortmund Data Bank.6 However, a great part of the VLE data, hE data, and γ∞ data were already published in the different volumes of the DECHEMA Chemistry Data Series.7-9 There is a good chance that we will be able to convince the responsible directors from DDBST that the Dortmund Data Bank can be used in Oldenburg by a person of a “neutral” research group to perform a comprehensive model comparison. However, we believe that also the educational version of the Dortmund Data Bank and the software package6 would be suitable for such a model comparison. This version already contains more than 40 000 data sets for pure compounds and mixtures. Literature Cited (1) Putnam, R.; Taylor, R.; Klamt, A.; Eckert, F.; Schiller, M. Prediction of Infinite Dilution Activity Coefficients Using COSMORS. Ind. Eng. Chem. Res. 2003, 42, 3635-3641. (2) Skjold-Jørgensen, S.; Kolbe, B.; Gmehling, J.; Rasmussen, P. Vapor-Liquid Equilibria by UNIFAC Group Contribution. Revision and Extension. Ind. Eng. Chem. Process Des. Dev. 1979, 18, 714-722. (3) 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: 1998, 67, 275). (4) Lohmann, J.; Gmehling, J. From UNIFAC to Modified UNIFAC (Dortmund). Ind. Eng. Chem. Res. 2001, 40, 957-964. (5) www.uni-oldenburg.de/tchemie/consortium. (6) www.ddbst.de. (7) Gmehling, J.; Onken, U.; et al. Vapor-Liquid Equilibrium Data Collection; 30 parts of the DECHEMA Chemistry Data Series; DECHEMA: Frankfurt, Germany, starting in 1977. (8) Gmehling, J.; et al. Heats of Mixing Data Collection; four parts of the DECHEMA Chemistry Data Series; DECHEMA: Frankfurt, Germany, starting in 1984. (9) Gmehling, J.; et al. Activity Coefficients at Infinite Dilution; four parts of the DECHEMA Chemistry Data Series; DECHEMA: Frankfurt, Germany, starting in 1986.
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