A Statistical Associating Fluid Theory Perspective of the Modeling of Compounds Containing Ethylene Oxide Groups
authors Crespo, EA; Coutinho, JAP
nationality International
journal INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
keywords EQUATION-OF-STATE; DIRECTIONAL ATTRACTIVE FORCES; VAPOR-LIQUID-EQUILIBRIUM; PRESSURE PHASE-EQUILIBRIA; COARSE-GRAINED MODELS; SIMPLIFIED PC-SAFT; CARBON-DIOXIDE; POLYETHYLENE-GLYCOL; POLY(ETHYLENE GLYCOL); TRIETHYLENE GLYCOL
abstract Compounds containing ethylene oxide groups as a repeating unit, such as glycols and their ethers, have several applications across different industrial fields. For efficient simulation, design, and optimization of industrial processes based on these compounds, reliable and robust thermodynamic models able to accurately describe their phase equilibria and thermophysical properties are required. For the choice of thermodynamic models available in the literature, the selection of the most adequate is not always obvious, but results have shown overtime that, for associating or polar fluids, association models derived from the statistical associating fluid theory are more accurate and physically sound than the cubic equations of state widely used by industry. However, the current modeling approaches used within the framework of association models have known limitations that must be understood by those developing and applying these models as they often result in a loss of accuracy and extrapolative or predictive ability. This review provides a literature survey of the different works on the modeling of compounds containing ethylene oxide groups using association models, discussing their capabilities and limitations while giving a perspective for future developments in this field.
publisher AMER CHEMICAL SOC
issn 0888-5885
year published 2019
volume 58
issue 9
beginning page 3562
ending page 3582
digital object identifier (doi) 10.1021/acs.iecr.9b00273
web of science category Engineering, Chemical
subject category Engineering
unique article identifier WOS:000460996700002
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journal impact factor 3.141
5 year journal impact factor 3.284
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