TY - JOUR
T1 - Isobaric Vapor-Liquid Equilibrium Prediction from Excess Molar Enthalpy Using Cubic Equations of State and PC-SAFT
AU - Brouwer, Thomas
AU - Crespo, Emanuel A.
AU - ten Kate, Antoon
AU - Coutinho, João A.P.
AU - Kersten, Sascha R.A.
AU - Bargeman, Gerrald
AU - Schuur, Boelo
N1 - Funding Information:
This has been an ISPT (Institute for Sustainable Process Technology) project (BL-20-07), cofunded by the Topsector Energy by the Dutch Ministry of Economic Affairs and Climate Policy (TEEI314006). This work was also partly developed within the scope of the project CICECO-Aveiro Institute of Materials, UIDB/50011/2020, UIDP/50011/2020 and LA/P/0006/2020, financed by national funds through the FCT/MEC (PIDDAC).
Publisher Copyright:
© 2023 The Authors. Published by American Chemical Society
PY - 2023/7/26
Y1 - 2023/7/26
N2 - 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.
AB - 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.
KW - UT-Hybrid-D
UR - http://www.scopus.com/inward/record.url?scp=85167815444&partnerID=8YFLogxK
U2 - 10.1021/acs.iecr.3c00804
DO - 10.1021/acs.iecr.3c00804
M3 - Article
AN - SCOPUS:85167815444
SN - 0888-5885
VL - 62
SP - 12329
EP - 12344
JO - Industrial and Engineering Chemistry Research
JF - Industrial and Engineering Chemistry Research
IS - 31
ER -