resumo
The recently proposed category of type V deep eutectic solvents (DESs), composed only of non-ionic species, has attracted great interest in the literature. However, despite their importance in solvent design, measuring the solid-liquid equilibrium (SLE) diagrams of all possible type V DES precursor combinations is unfeasible. Therefore, a reliable computational tool must be found to estimate SLE phase diagrams and, thus, the melting points of type V DESs. In this work, a total of 134 different binary eutectic systems (1744 datapoints) were gathered from the literature, and the calculation capabilities and accuracy of three different models-COSMO-RS, UNIFAC of Dortmund, and Group and Group-Interaction Contribution method (GGIC)-were evaluated. UNIFAC and COSMO-RS were, by far, the best performing models, with average absolute deviations (AADs) of, respectively, 6.9 K for 94 systems and 7.4 K for 133 systems. Due to a lack of group interaction parameters, UNIFAC could only describe 94 systems, a severe disadvantage over COSMO-RS. Moreover, despite being able to describe all 134 systems, the GGIC model resulted in an AAD of 37 K. Finally, the effect of using the different parametrizations or multiple conformers in COSMO-RS predictions was also evaluated, and the validity of neglecting heat capacity terms when performing SLE calculations was verified.
palavras-chave
MODIFIED UNIFAC MODEL; SOLID PLUS LIQUID; PHASE-DIAGRAMS; MIXTURES; EQUILIBRIUM; PREDICTION; SOLUBILITY
categoria
Engineering
autores
Teixeira, G; Abranches, DO; Ferreira, O; Coutinho, JAP
nossos autores
Grupos
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 CICECO-Aveiro Institute of Materials, UIDB/50011/2020, UIDP/50011/2020, and LA/P/0006/2020, and CIMO-Mountain Research Center, UIDB/00690/2020 and LA/P/0007/2020, financed by national funds through the Portuguese Foundation for Science and Technology/MCTES. G.T. thanks FCT for his Ph.D. grant (UI/BD/151114/2021).