Solubility prediction UNIFAC

It the productivity target cannot be achieved then a co-solvent system could be selected using solubility prediction methods like NRTL-SAC [1] and Local UNIFAC [4], The addition of a second solvent to increase solubility is an effective way of increasing productivity for a sparingly soluble solute. 

Wienke, G. Gmehling, J. Prediction of octanol - water - partition coefficients. Henry-coefficients and water solubilities using UNIFAC. Toxicol. Environ. Chem. 1998, 65, 57-86. 

A.queous Solubility. SolubiHty of a chemical in water can be calculated rigorously from equiHbrium thermodynamic equations. Because activity coefficient data are often not available from the Hterature or direct experiments, models such as UNIFAC can be used for stmcture—activity estimations (24). Phase-equiHbrium relationships can then be appHed to predict miscibility. Simplified calculations are possible for low miscibiHty however, when there is a high degree of miscibility, the phase-equiHbrium relationships must be solved rigorously. 

One problem limiting the consideration of salt extractive distillation is the fact that the performance and solubility of a salt in a particiilar system is difficult to predict without experimental data. Some recent advances have been made in modeling the X T.E behavior of organic-aqueous-salt solutions using modified UNIFAC, NRTL, UNIQUAC, and other approaches [Kumar, Sep. Sci. Tech., 28(1), 799 (1993)]. 

The most important aspect of the simulation is that the thermodynamic data of the chemicals be modeled correctly. It is necessary to decide what equation of state to use for the vapor phase (ideal gas, Redlich-Kwong-Soave, Peng-Robinson, etc.) and what model to use for liquid activity coefficients [ideal solutions, solubility parameters, Wilson equation, nonrandom two liquid (NRTL), UNIFAC, etc.]. See Sec. 4, Thermodynamics. It is necessary to consider mixtures of chemicals, and the interaction parameters must be predictable. The best case is to determine them from data, and the next-best case is to use correlations based on the molecular weight, structure, and normal boiling point. To validate the model, the computer results of vapor-liquid equilibria could be checked against experimental data to ensure their validity before the data are used in more complicated computer calculations. 

Al-Sahhaf, T. A. (1989) Prediction of the solubility of hydrocarbons in water using UNIFAC. J. Environ. Sci. Health A24, 49-56. 

The application of thermodynamic models to the correlation and prediction of pharmaceutical solubility behaviour is an underutilized technique in today s process research and development environment. This is due to the relatively poor accuracy and limited predictive ability of the previous generation of models. Recent advances in computational chemistry and an increased focus on the life science sectors has led to the development of more appropriate models with significantly improved predictive capabilities. The NRTL-SAC and Local UNIFAC approaches will be discussed here with additional examples given in section 8. 

Solubility modelling with activity coefficient methods is an under-utilized tool in the pharmaceutical sector. Within the last few years there have been several new developments that have increased the capabilities of these techniques. The NRTL-SAC model is a flexible new addition to the predictive armory and new software that facilitates local fitting of UNIFAC groups for Pharmaceutical molecules offers an interesting alternative. Quantum chemistry approaches like COSMO-RS [25] and COSMO-SAC [26] may allow realistic ab-initio calculations to be performed, although computational requirements are still restrictive in many corporate environments. Solubility modelling has an important role to play in the efficient development and fundamental understanding of pharmaceutical crystallization processes. The application of these methods to industrially relevant problems, and the development of new... 

Kuramochi, H., Noritomi, H., Hoshino, D., and Nagahama, K. Measurements of solubilities of two amino acids in water and prediction by the UNIFAC model, Biotechnol Prog., 12(3) 371-379, 1996. 

Kan, A. T., and M. B. Tomson, UNIFAC prediction of aqueous and nonaqueous solubilities of chemicals with enviromental interest , Environ. Sci. Technol., 30,1367-1376 (1996). 

Ruelle, R, M. Buchmann, H. Nam-Tran, andU.W. Kesselring. 1992. The mobile order theory versus UNIFAC and regular solution theory-derived models for predicting the solubility of solid substdftbasn. Res.9 788-791. 

Solubility data of biological compounds taken from literature are considered in this work. Different thermodynamic models based on cubic equations of state and UNIFAC are used in the correlation of experimental data. Interaction parameters are obtained by group contribution approach in order to establish correlations suitable for the prediction of the solid solubility. 

The application of UNIFAC to the solid-liquid equilibrium of sohds, such as naphthalene and anthracene, in nonaqueous mixed solvents provided quite accurate results [11]. Unfortunately, the accuracy of UNIFAC regarding the solubility of solids in aqueous solutions is low [7-9]. Large deviations from the experimental activity coefficients at infinite dilution and the experimental octanol/water partition coefficients have been reported [8,9] when the classical old version of UNIFAC interaction parameters [4] was used. To improve the prediction of the activity coefficients at infinite dilution and of the octanol/water partition coefficients of environmentally significant substances, special ad hoc sets of parameters were introduced [7-9]. The reason is that the UNIFAC parameters were determined mostly using the equihbrium properties of mixtures composed of low molecular weight molecules. Also, the UNIFAC method cannot be applied to the phase equilibrium in systems containing... 

The calculation of the activity coefficient of a solid in a saturated solution of a n-component mixture constitutes the main difficulty in predicting the solid solubility. Generally speaking, the activity coefficient of a solid in a saturated solution of a n-component mixture can be predicted using either group-contribution methods, such as UNIFAC and ASOG, or the experimental solubilities of the solid in subsystems of the multi-component mixed solvent combined with the Wilson, NRTL, etc. equation (Acree, 1984 Prausnitz et al., 1986). 

The application of UNIFAC to the solubility of naphthalene in nonaqueous mixed solvents provided satisfactory results when compared to experimental data (Acree, 1984). However, the UNIFAC was inaccurate in predicting the solubilities of solids in aqueous solutions (Fan and Jafvert, 1997). Furthermore, the application of the traditional UNIFAC to mixtures containing a polymer or another large molecule, such as a drug, and low molecular weight solvents is debatable (Fredenslund and Sprensen, 1994). The reason is that the UNIFAC parameters were determined mostly... 

From the predictive category, we bring some examples of the application of the UNIFAC model. In one study, this model has been used to predict the solubility of naphtalene, anthracene, and phenanthrene in various solvents and their mixtures [8], They showed the applicability of the UNIFAC model in prediction of the phase behavior of solutes in solvents. There have been efforts to make the UNIFAC model more robust and powerful in the prediction of phase behaviors [14], In one study, the solubility of buspirone-hydrochloride in isopropyl alcohol was measured and evaluated by the modified UNIFAC model [15]. It was concluded that for highly soluble pharmaceutics, the modified form of the UNIFAC model was not suitable. In another study, the solubility of some chemical species in water and some organic solvents was predicted by the UNIFAC model [16]. For some unknown functional groups, they used other known groups which had chemical structures that were similar to unknown ones. 

In conclusion, it was stated that the UNIFAC model is not a proper model for use in crystallization and related processes. The UNIFAC model also has been utilized to predict the solubility of some aromatic components as well as long-chain hydrocarbons [17]. The results showed that the predictions for the linear hydrocarbons are not as good as the ones for the aromatics. 

It should, however, be pointed out that in the above case, if one simply ascribes a single solubility parameter to each monomer, it is Impossible to predict an overall negative enthalpy of mixing. It has also been noted that a window of miscibility can be explained by a favorable specific interaction without recourse to a cross term. If one separates the normal dispersive forces from the specific interaction, then as a first approximation, when the solubility parameters of the two polymers are similar the unfavorable dispersive interactions are small and specific interactions yield miscibility. For a copolymer/polymer mixture the solubility parameters might be expected to match at some specific copolymer composition (32). A method of combining the features of both the specific interaction and the cross term is to use something similar to the UNIFAC group contribution system and model all the interactions, both favorable and unfavorable within the system. 

Predictions of calculated versus experimental data were in the following order of absolute average duration (aad) of Xy. SAFT of 1.90 x IQr, PR eos of 3.7 x Qr UNIFAC with Magnussen et al. [12] parameters of 3.5 x 10, and UNIFAC with Larsen parameters of 5.4 x 10. SAFT was also best for extrapolation of both lie and solubility. SAFT also predicted the ternary systems that tested best. 

---