abstract
To achieve a successful liquid-liquid extraction, the selection of the biphasic system is crucial for the proper separation of the solutes of interest. The number of biphasic systems that can be employed is vast, requiring a large amount of time and cost to experimentally determine the most suitable for each application. The use of computational methods to predict partition coefficients in biphasic systems is of great interest to design and select the most appropriate. COSMO-RS, a quantum chemical computational tool that requires only the chemical structure of the compounds for calculations, would be an ideal tool for that purpose. Here, we present a systematic evaluation of COSMO-RS as a predictive tool for partition coefficients. Its performance was evaluated for the partitioning of 228 solutes in 9 binary and 3 ternary organic biphasic systems (OBS). The results show that the use of COSMO-RS with TZVPD_FINE parametrization allows for very good predictions. They also show that predictions are greatly dependent on an accurate description of the compositions of the phases in equilibrium. Thus, the use of experimental mutual solubilities (binary OBS) or tie lines (ternary OBS) when available is the most suitable option for this purpose. In the case of using a total predictive tool, TZVPD_FINE parametrization can properly predict both mutual solubilities and tie lines, so it can also be used for the estimation of partition coefficients in an OBS. Therefore, the COSMO-RS method is demonstrated here to be a useful and reliable tool to predict partition coefficients in binary and ternary OBS, which can be used for the screening and selection of the most appropriate system to be used in a separation process.
keywords
COUNTER-CURRENT; SCREENING MODEL; CHROMATOGRAPHY; SELECTION; SOLVENT; PHASE
subject category
Engineering
authors
Santiago, R; Sosa, FHB; Díaz, I; González-Miquel, M; Coutinho, JAP
our authors
Projects
CICECO - Aveiro Institute of Materials (UIDB/50011/2020)
Associated Laboratory CICECO-Aveiro Institute of Materials (LA/P/0006/2020)
Collaboratory for Emerging Technologies, CoLab (EMERGING TECHNOLOGIES)
acknowledgements
This work was developed within the scope of project CICECO-Aveiro Institute of Materials (UIDB/50011/2020, UIDP/ 50011/2020, and LA/P/0006/2020), financed by national funds through the FCT/MCTES (PIDDAC). Ruben Santiago thanks Ministerio Universidades for his Margarita Salas contract (CA1/RSUE/2021-00585). Filipe H. B. Sosa acknowledges FCT - Fundacao para a Ciencia e a Tecnologia, I.P. for researcher contract CEECIND/07209/2022 under the Scientific Employment Stimulus - Individual Call. Authors from Universidad Politecnica de Madrid acknowledge Community of Madrid (Spain) for funding through the Multiannual Agreement with Universidad Politecnica de Madrid in the line Excellence Programme for University Professors, in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).