resumo
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.
palavras-chave
MOLECULE SOLUBILITY; SOLUTE DESCRIPTORS; THYMOL; DRUG; CAMPHOR; TERPENES; SOLVENTS; WATER; PURE
categoria
Engineering
autores
Vilas-Boas, SM; Cordova, IW; Abranches, DO; Coutinho, JAP; Ferreira, O; Pinho, SP
nossos autores
Dinis O. Abranches
Investigador Auxiliar
Isabella W. Cordova
Estudante de doutoramento
Simão Pedro de Almeida Pinho
ColaboradorGrupos
G4 - Materiais Renováveis e Economia Circular
G6 - Materiais Virtuais e Inteligência Artificial
Projectos
CICECO - Aveiro Institute of Materials (UIDB/50011/2020)
CICECO - Aveiro Institute of Materials (UIDP/50011/2020)
Associated Laboratory CICECO-Aveiro Institute of Materials (LA/P/0006/2020)
agradecimentos
This work was developed within the scope of the project CIMO-Mountain Research Center, UIDB/00690/2020 and LA/P/0007/2020, and CICECO-Aveiro Institute of Materials, UIDB/50011/2020, UIDP/50011/2020, and LA/P/0006/2020, financed by national funds through the Portuguese Foundation for Science and Technology (FCT)/MCTES. Sergio M. Vilas-Boas (SFRH/BD/138149/2018 and COVID/BD/152936/2022) and Isabella W. Cordova (2022.12407.BD) thank FCT and the European Social Fund (ESF) for their Ph.D. grants.