Development and critical evaluation of group contribution methods for the estimation of critical properties, liquid vapour pressure and liquid viscosity of organic compounds.

Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2006.Critical properties, liquid vapour pressures and liquid viscosities are important thermophysical properties required for the design, simulation and optimisation of chemical plants. Unfortunately, experimental data for these properties are in most cases not available. Synthesis of sufficiently pure material and measurements of these data are expensive and time consuming. In many cases, the chemicals degrade or are hazardous to handle which makes experimental measurements difficult or impossible. Consequently, estimation methods are of great value to engineers. In this work, new group contribution methods have been developed for the estimation of critical properties, liquid vapour pressures and liquid viscosities of non-electrolyte organic compounds. The methods are based on the previous work of Nannoolal (2004) & Nannoolal et al. (2004) with minor modifications of structural group definitions. Critical properties, viz. critical temperature, critical pressure and critical volume, are of great practical importance as they must be known in order to use correlations based on the law of corresponding states. However, there is a lack of critical property data in literature as these data are difficult or in many cases impossible to measure. Critical property data are usually only available for smaller molecules of sufficient thermal stability. The proposed group contribution method for the estimation of critical properties reported an average absolute deviation of 4.3 K (0.74%), 100 kPa (2.96%) and 6.4 cm3.mol1 (1.79%) for a set of 588 critical temperatures, 486 critical pressures and 348 critical volumes stored in the Dortmund Data Bank (DDB (2006)), respectively. These results were the lowest deviations obtained when compared to ten well known estimation methods from literature. In addition, the method showed a wider range of applicability and the lowest probability of prediction failure and leads to physically realistic extrapolation when applied to a test set of components not included in the training set. For the estimation of the critical temperature using the new method, knowledge about the normal boiling point is required. If there is no information on the latter property, then the previous group contribution estimation method can be employed for estimation. Because of their great importance in chemical engineering, liquid vapour pressures have received much attention in literature. There is currently an abundance of experimental data for vapour pressures, especially for smaller molecules, but data are scarce or of low quality for larger and more complex molecules of low volatility. The estimation of liquid vapour pressures from molecular structure has met with very limited success. This is partly due to the high quality predictions required for vapour pressures for use in the design of for example distillation columns. This work presents a new technique for the estimation of liquid vapour pressures by developing a two-parameter equation where separate parameters model the absolute value and slope while at the same time the equation is able to approximate the nonlinearity of the curve. The fixed point or absolute value chosen was the normal boiling point for which a large amount of experimental data is available. A group contribution estimation of the slope was then developed which showed nearly no probability of prediction failure (high deviation). Employing experimental normal boiling points in the method, an absolute relative deviation of 6.2% in pressure for 1663 components or 68835 (68670 from DDB and 165 from Beilstein) data points was obtained. This result is in comparable accuracy or slightly higher in deviation than correlative models such as the Antoine and DIPPR equations (direct correlations). A test of the predictive capability by employing data that were not used in the training set also showed similar results. Estimations are possible up to the inflection point or a reduced normal boiling temperature of ±1.2. If there is no information about the experimental normal boiling point, two options are recommended to obtain this value. The first and more reliable is back-calculation using the known boiling point at other pressures and the estimated slope of the vapour pressure equation. Results in this case are similar to cases where experimental normal boiling points were used. The second possibility is to estimate the normal boiling point using the method developed previously. In this case, an absolute relative deviation of 27.0% in pressure is obtained. The saturated liquid viscosity is an important transport property that is required for many engineering applications. For this property, experimental data are limited to mostly simple and more common components and, even for these components the data often cover only a small temperature range. There have been many different approaches to estimate liquid viscosities of organic compounds. However, correlative and empirical methods are often the only or preferred means to obtain liquid viscosities. The technique used for the estimation of the liquid viscosity is similar to that in case of liquid vapour pressures, i.e. a two-parameter equation models the absolute value, slope and the non-linearity of the curve. As there was no convenient reference point at a standard viscosity available to model the absolute value (viscosity reference temperature), an algorithm was developed to calculate this temperature which was chosen at a viscosity of 1.3 cP. This work then presents a group contribution estimation of the slope and using calculated or adjusted reference temperatures, an absolute relative deviation of 3.4% in viscosity for 829 components or 12861 data points stored in the DDB was obtained. This result is in comparable accuracy or slightly higher in deviation than correlative models such as the Andrade and Vogel equations (direct correlations). The estimation method has an upper temperature limit which is similar to the limit in case of liquid vapour pressures. If no data are available for a viscosity close to 1.3 cP then, as in case of the vapour pressure estimation method, the temperature can be back calculated from data at other viscosity values. Alternately, the viscosity reference temperature can be estimated by a group contribution method developed in this work. This method reported an average absolute deviation of 7.1 K (2.5%) for 813 components. In case both the slope and absolute value were estimated for the liquid viscosity curve, an average absolute deviation of 15.3 % in viscosity for 813 components or 12139 data points stored in the DDB was obtained. The new method was shown to be far more accurate than other group contribution methods and at the same time has a wider range of applicability and lower probability of prediction failure. For the group contribution predictions, only the molecular structure of the compound is used. Structural groups were defined in a standardized form and fragmentation of the molecular structures was performed by an automatic procedure to eliminate any arbitrary assumptions. To enable comparison, chemical family definitions have been developed that allow one to automatically classify new components and thus inform the user about the expected reliability of the different methods for a component of interest. Chemical family definitions are based on the kind and frequency of the different structural groups in the molecule

Development of a group contribution method for the prediction of normal boiling points of non-electrolyte organic compounds.

Thesis (M.Sc.Eng.)-University of Natal, Durban, 2004.Physical properties are fundamental to all chemical, biochemical and environmental industries. One of these properties is the normal boiling point of a compound. However, experimental values in literature are quite limited and measurements are expensive and time consuming. For this reason, group contribution estimation methods are generally used. Group contribution is the simplest form of estimation requiring only the molecular structure as input. Consequently, the aim of this project was the development of a reliable group contribution method for the estimation of normal boiling points of non-electrolytes applicable for a broad range of components. A literature review of the available methods for the prediction of the normal boiling points from molecular structure only, was initially undertaken. From the review, the Cordes and Rarey (2002) method suggested the best scientific approach to group contribution. This involved defining the structural first-order groups according to its neighbouring atoms. This definition also provided knowledge of the neighbourhood and the electronic structure of the group. The method also yielded the lowest average absolute deviation and probability of prediction failure. Consequently, the proposed group contribution method was then developed using the Cordes and Rarey method as a starting point. The data set included experimental data for approximately 3000 components, 2700 of which were stored in the Dortmund Data Bank (DDB) and about 300 stored in Beilstein. The mathematical formalism was modified to allow for separate examination and regression of individual contributions using a meta-language filter program developed specifically for this purpose. The results of this separate examination lead to the detection of unreliable data, the re-classification of structural groups, and introduction of new structural groups to extend the range of the method. The method was extended using steric parameters, additional corrections and group interaction parameters. Steric parameters contain information about the greater neighbourhood of a carbon. The additional corrections were introduced to account for certain electronic and structural effects that the first-order groups could not capture. Group interactions were introduced to allow for the estimation of complex multifunctional compounds, for which previous methods gave extraordinary large deviations from experimental findings. Several approaches to find an improved linearization function did not lead to an improvement of the Cordes and Rarey method. The results of the new method are extensively compared to the work of Cordes and Rarey and currently-used methods and are shown to be far more accurate and reliable. Overall, the proposed method yielded an average absolute deviation of 6.50K (1.52%) for a set of 2820 components. For the available methods, Joback and Reid produced an average absolute deviation of 21.37K (4.67%) for a set of 2514 components, 14.46K (3.53%) for 2578 components for Stein and Brown, 13.22K (3.15%) for 2267 components for Constantinou and Gani, 10.23 (2.33%) for 1675 components for Marrero and Pardillo and 8.18K (1.90%) for 2766 components for Cordes and Rarey. This implies that the proposed method yielded the lowest average deviation with the broadest range of applicability. Also, on an analysis of the probability of prediction failure, only 3% of the data was greater than 20K for the proposed method. This detailed comparison serves as a very valuable tool for the estimation of prediction reliability and probable error. Structural groups were defined in a standardized form and the fragmentation of the molecular structures was performed by an automatic procedure to eliminate any arbitrary assumptions