Isobaric Vapor-Liquid Equilibrium Prediction from Excess Molar Enthalpy Using Cubic Equations of State and PC-SAFT

Thomas Brouwer, Emanuel A. Crespo, Antoon ten Kate, João A.P. Coutinho, Sascha R.A. Kersten, Gerrald Bargeman, Boelo Schuur*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
68 Downloads (Pure)

Abstract

Vapor-liquid equilibrium (VLE) data, essential for an accurate design of distillation columns, are not always readily available. This work has systematically assessed the feasibility of determining VLE data based on excess molar enthalpy (hE) results. Twelve cubic Equation of State (cEoS) models combined with eight mixing rules and the Perturbed Chain Statistical Associating Fluid Theory (PC-SAFT) have been assessed. cEoS models are robust and applicable to a significant number of solvent families, while the PC-SAFT model is typically applied for strongly nonideal systems exhibiting molecular association behavior. VLE predictions based on the Peng-Robinson cEoS with the 2-parameter Stryjek-Vera-Margules-type mixing rule, one of the best cEoS-mixing rule combinations, was reasonably accurate, but less accurate than predictions based on the standard modified (mod.) UNIFAC (Do) model. This makes the developed hE-cEoS-VLE methodology relevant only for systems whose binary interaction parameters in UNIFAC (Do) and VLE data are not available. For the most nonideal self-associating systems evaluated, the PC-SAFT model parametrized with experimental hE data provided isobaric VLE results with similar or even higher accuracy than the mod. UNIFAC (Do) model. This indicates the potential of the hE-PC-SAFT-VLE model for accurately predicting VLE data for highly nonideal and associating systems. Therefore, this methodology can be used as a quick evaluation method for the separation of complex systems, including ionic liquids and deep eutectic solvents, for which the mod. UNIFAC (Do) model does not provide sufficiently accurate VLE predictions.

Original languageEnglish
Pages (from-to)12329-12344
Number of pages16
JournalIndustrial and Engineering Chemistry Research
Volume62
Issue number31
DOIs
Publication statusPublished - 26 Jul 2023

Keywords

  • UT-Hybrid-D

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