Modeling the Solubility of Monoterpenoids with Hybrid and Predictive Thermodynamic Tools

Sérgio M Vilas-Boas; Isabella W Cordova; Dinis O Abranches; João A P Coutinho; Olga Ferreira; Simão P Pinho

doi:10.1021/acs.iecr.2c03991

Modeling the Solubility of Monoterpenoids with Hybrid and Predictive Thermodynamic Tools

Ind Eng Chem Res. 2023 Mar 13;62(12):5326-5335. doi: 10.1021/acs.iecr.2c03991.

Authors

Sérgio M Vilas-Boas^{1

2

3}, Isabella W Cordova^{1

2

3}, Dinis O Abranches³, João A P Coutinho³, Olga Ferreira^{1

2}, Simão P Pinho^{1

2}

Affiliations

¹ Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal.
² Laboratório para a Sustentabilidade e Tecnologia em Regiões de Montanha, Instituto Politécnico de Bragança, Campus de Santa Apolónia, 5300-253 Bragança, Portugal.
³ CICECO - Aveiro Institute of Materials, Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal.

Abstract

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.