Terpenes are important varietal compounds responsible for the characteristic aromas of alcoholic beverages. Reliable vapor–liquid equilibrium (VLE) data this class aroma in hydroalcoholic media is essential to understand their behavior during distillation and thus achieve a desired quality distilled products. In work, experimental measurements VLE ?-terpineol highly diluted ethanol–water mixtur...

Tools to predict vapor–liquid phase equilibria are indispensable for the conceptualization and design of separation processes. Modified cohesive energy density (MOSCED) is a solubility-parameter-based method parameterized make accurate predictions limiting activity coefficient. As method, MOSCED can not only quantitative predictions, but shed light on underlying intermolecular interactions. In ...

The aim of this paper is to bring valuable phase equilibria information for the design and operation biolubricant related biofuel product processes. As a result, Vapor-Liquid Equilibrium (VLE) measurements, at different temperatures, pressures global compositions, ternary systems [Ethanol + 2-Ethyl-1-hexanol 1-Dodecanol] 1-Octanol 1-Dodecanol], as well multicomponent system containing these alc...

By proposing a predictive method with no adjustable parameter and by using infinite dilution activity coefficients of components in binary mixtures obtained from UNIFAC model, the binary interaction parameters (k12) in van der Waals mixing rule (vdWMR) and Orbey-Sandler mixing rule (OSMR) have been evaluated. The predicted binary interaction parameters are used in Peng-Robinson-S...

In this work, we develop a correlative model based on the surface tension data in order to calculate thermodynamic parameters, such as interaction energy between components (Uij), activity coefficients and etc. In the new approach, by using Li et al. (LWW) model, a three-parameter surface tension equation is derived for liquid mixtures. The surface tension data of 54 aqueous and 73 non-aqueous ...

Ionic liquids (ILs) are important solvents for sustainable processes and predicting activity coefficients (ACs) of solutes in ILs is needed. Recently, matrix completion methods (MCMs), transformers, graph neural networks (GNNs) have shown high accuracy ACs binary mixtures, superior to well-established models, e.g., COSMO-RS UNIFAC. GNNs particularly promising here as they learn a molecular grap...