Modeling the solubility of monoterpenoids with hybrid and predictive thermodynamic tools

• Autor(a) principal: Vilas-Boas, Sérgio M.
• Data de Publicação: 2020
• Outros Autores: Cordova, Isabella Weber, Abranches, Dinis O., Coutinho, João A.P., Ferreira, Olga, Pinho, Simão
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10198/22101
• topic: Molecule solubility; Solute descriptors; Thymol; Drug; Camphor; Terpenes; Solvents; Water; Pure

The Abraham and NRTL-SAC semipredictive models were employed to represent the solubility of (-)-borneol, (1R)-(+)-camphor, L-(-)-menthol, and thymol in water and organic solvents, using data measured in this work and collected from the literature. A reduced set of solubility data was used to estimate the model parameters of the solutes, and global average relative deviations (ARDs) of 27% for the Abraham model and 15% for the NRTL-SAC model were obtained. The predictive capability of these models was tested by estimating the solubilities in solvents not included in the correlation step. Global ARDs of 8% (Abraham model) and 14% (NRTL-SAC model) were obtained. Finally, the predictive COSMO-RS model was used to describe the solubility data in organic solvents, with ARD of 16%. These results show the overall better performance of NRTL-SAC in a hybrid correlation/prediction approach, while COSMO-RS can produce very satisfactory predictions even in the absence of any experimental data.