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Advisor(s)
Abstract(s)
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.
Description
Keywords
Molecule solubility Solute descriptors Thymol Drug Camphor Terpenes Solvents Water Pure
Pedagogical Context
Citation
Vilas-Boas, Sérgio M.; Cordova, Isabella Weber; Abranches, Dinis O.; Coutinho, João A.P.; Ferreira, Olga; Pinho, Simão (2023). Modeling the solubility of monoterpenoids with hybrid and predictive thermodynamic tools. Industrial & Engineering Chemistry Research. ISSN 0888-5885. 62:12, p. 5326-5335
Publisher
American Chemical Society