Applying UNIFAC-based models to predict the solubility of solids in subcritical water

Solubility and Decomposition of Organic Compounds in Subcritical Water

In this article, studies on organic solubility and stability in subcritical water reported during the past 25 years have been reviewed. Data on the solubility and decomposition of organic compounds in subcritical water, a green solvent, are needed in environmental remediation, chemistry, chemical engineering, medicine, polymer, food, agriculture, and many other fields. For solubility studies, the experimental systems used to measure solubility, mathematical equations derived and applied for the modeling of the experimentally determined solubility data, and the correlation between the predicated and experimental data have been summarized and discussed. This paper also reviewed organic decomposition under subcritical water conditions. In general, the solubility of organics is significantly enhanced with increasing water temperature. Likewise, the percentage of organic decomposition also increases with higher temperature.

Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String

A new method of Hansen solubility parameters (HSPs) prediction was developed by combining the multivariate adaptive regression splines (MARSplines) methodology with a simple multivariable regression involving 1D and 2D PaDEL molecular descriptors. In order to adopt the MARSplines approach to QSPR/QSAR problems, several optimization procedures were proposed and tested. The effectiveness of the obtained models was checked via standard QSPR/QSAR internal validation procedures provided by the QSARINS software and by predicting the solubility classification of polymers and drug-like solid solutes in collections of solvents. By utilizing information derived only from SMILES strings, the obtained models allow for computing all of the three Hansen solubility parameters including dispersion, polarization, and hydrogen bonding. Although several descriptors are required for proper parameters estimation, the proposed procedure is simple and straightforward and does not require a molecular geometry optimization. The obtained HSP values are highly correlated with experimental data, and their application for solving solubility problems leads to essentially the same quality as for the original parameters. Based on provided models, it is possible to characterize any solvent and liquid solute for which HSP data are unavailable.

Optimization of subcritical fluid extraction of bioactive compounds using Hansen solubility parameters

Process engineering operations in food and nutraceutical industries pertaining to the design of extraction of value-added products from biomass using pressurized liquids involve a careful selection of the solvent and optimal temperature conditions to achieve maximum yield. Complex molecular structure and limited physical property data in the literature of biological solutes extracted from biomass compounds have necessitated the process modeling of such operations. In this study, we have applied the Hansen 3-dimensional solubility parameter concept to optimize the extraction of molecularly complex solutes using subcritical fluid solvents. Hansen solubility spheres characterized by the relative energy differences (RED) have been used to characterize and quantify the solute-subcritical solvent interactions as a function of temperature. The solvent power of subcritical water and compressed hydroethanolic mixtures above their boiling points has been characterized using the above-mentioned method. The use of group contribution methods in collaboration with computerized algorithms to plot the Hansen spheres provides a quantitative prediction tool for optimizing the design of extraction conditions. The method can be used to estimate conditions for solute-solvent miscibility, an optimum temperature range for conducting extractions under pressurized conditions, and approximate extraction conditions of solutes from natural matrices.