Studies on the solubility of phenolic compounds

Abstract

Phenolic compounds generally act as antioxidant and free radical scavengers, having several practical applications in the pharmaceutical, food, oil and chemical industrial processes. Among those compounds, phenolic acids represent a group that is widely present in some natural products, showing interesting properties, such as preventers of some degenerative diseases, with application in the pharmaceutical industry. Furthermore, solubility studies play a key role to obtain a significant yield and a representative product, being an important parameter for the development of new drugs as well as the optimization of already existent processes. In this context, the main objective of this work is to measure the solubility of gallic, protocatechuic, gentisic and α-resorcylic acids in water and organic solvents (methanol, ethanol, 1-propanol, isopropanol, 2-butanone, ethyl acetate, dimethylformamide and acetonitrile) at 298.15 and 313.15 K and to employ the NRTL-SAC thermodynamic model coupled to the Reference Solvent Approach (RSA) to describe the solubility data. The experimental methodology was the shake-flask method coupled to the gravimetric method and, in general, the results obtained were satisfactorily consistent with the information available in literature for gallic and protocatechuic acids. For gentisic and α-resorcylic acids, no solubility studies were found at the analyzed temperatures until now. Melting points and enthalpies of fusion of the selected phenolic acids were also measured via Differential Scanning Calorimetry (DSC). Finally, the NRTL-SAC segment descriptors were obtained by fitting the solubility data in seven solvents, obtaining average relative deviations (ARD) between 25 and 34%. The model was then applied to predict the solubility in 1-propanol and dimethylformamide and the ARD% were 70 and 78%, respectively. Those values are satisfactory for semi-predictive models, using a limited set of solvents, showing that the NRTL-SAC is adequate to model binary systems containing the selected phenolic acids.