Evaluation of Statistical Associating Fluid Theory (SAFT) and Perturbed Chain-SAFT Equations of State for the Calculation of Thermodynamic Derivative Properties of Fluids Related to Carbon Capture and Sequestration

2011 ◽  
Vol 25 (7) ◽  
pp. 3334-3343 ◽  
Author(s):  
Nikolaos I. Diamantonis ◽  
Ioannis G. Economou
Keyword(s):  
Carbon Capture ◽  
Equations Of State ◽  
Carbon Capture And Sequestration ◽  
Statistical Associating Fluid Theory ◽  
Fluid Theory

scholarly journals Application of PC-SAFT and cubic equations of state for the correlation of solubility of some pharmaceutical and statin drugs in SC-CO2

2013 ◽  
Vol 19 (3) ◽  
pp. 449-460 ◽  
Author(s):  
El Abdallah ◽  
C. Si-Moussa ◽  
S. Hanini ◽  
M. Laidi
Keyword(s):  
Experimental Data ◽  
Equations Of State ◽  
Van Der Waals ◽  
Energy Parameter ◽  
Pure Component ◽  
Binary Interaction ◽  
Statistical Associating Fluid Theory ◽  
Binary Interaction Parameters ◽  
Fluid Theory ◽  
Statin Drugs

In this work, the solubilities of some anti-inflammatory (nabumetone, phenylbutazone and salicylamide) and statin drugs (fluvastatin, atorvastatin, lovastatin, simvastatin and rosuvastatin) were correlated using the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) with one-parameter mixing rule and commonly used cubic equations of state Peng-Robinson (PR) and Soave-Redlich-Kwong (SRK) combining with van-der Waals-1 parameter (VDW1) and van-der Waals-2 parameters (VDW2) mixing rules. The experimental data for studied compounds were taken from literature at temperature and pressure in ranges (308-348 K) and (100-360 bar) respectively. The critical properties required for the correlation with PR and SRK were estimated using Gani and Noonalol contribution group methods whereas, PC-SAFT pure-component parameters; segment number (m), segment diameter (?) and energy parameter (?/k) have been estimated by tihic?s group contribution method for nabumetone. For phenylbutazone and salicylamide those parameters were determined using a linear correlation. For statin drugs, PC-SAFT parameters were fitted to solubility data, and binary interaction parameters (kij and lij) have been obtained by fitting the experimental data. The result was found to be in good agreement with the experimental data and showed that PC-SAFT approach can be used to model solid-SCF equilibrium with better correlation accuracy than cubic equations of state.

Extended statistical associating fluid theory (SAFT) equations of state for dipolar fluids

AIChE Journal ◽  
2005 ◽  
Vol 51 (8) ◽  
pp. 2328-2342 ◽  
Author(s):  
Eirini K. Karakatsani ◽  
Theodora Spyriouni ◽  
Ioannis G. Economou
Keyword(s):  
Equations Of State ◽  
Statistical Associating Fluid Theory ◽  
Dipolar Fluids ◽  
Fluid Theory

scholarly journals Multi-criteria Optimization for Parameterization of SAFT-type Equations of State for Water

2021 ◽  
Author(s):  
Esther Forte ◽  
Jakob Burger ◽  
Kai Langenbach ◽  
Hans Hasse ◽  
Michael Bortz
Keyword(s):  
Equations Of State ◽  
Goal Function ◽  
Liquid Density ◽  
Saturated Liquid ◽  
Statistical Associating Fluid Theory ◽  
Conflicting Objectives ◽  
Pareto Sets ◽  
Fluid Theory ◽  
Molecular Nature ◽  
Saturated Liquid Density

Finding appropriate parameter sets for a given equation of state (EoS) to describe different properties of a certain substance is an optimization problem with conflicting objectives. Such problem is commonly addressed by single-criteria optimization in which the different objectives are lumped into a single goal function. We show how multi-criteria optimization (MCO) can be beneficially used for parameterizing equations of state. The Pareto set, which comprises a set of optimal solutions of the MCO problem, is determined. As an example, the perturbed-chain statistical associating fluid theory (PC-SAFT) EoS is used and applied to the description of the thermodynamic properties of water, focusing on saturated liquid density and vapor pressure. Different options to describe the molecular nature of water by the PC-SAFT EoS are studied and for all variants, the Pareto sets are determined, enabling a comprehensive assessment. When compared to literature models, Pareto optimization yields improved models.

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