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  5. SGTPy: A Python code for calculating the interfacial properties of fluids based on the Square Gradient Theory using the SAFT-VR Mie equation of state
 
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SGTPy: A Python code for calculating the interfacial properties of fluids based on the Square Gradient Theory using the SAFT-VR Mie equation of state
File(s)
main-SGTPY-mini.docx (2.39 MB)
Accepted version
Author(s)
Mejia, Andres
Muller, Erich
Chaparro Maldonado, Gustavo
Type
Journal Article
Abstract
In this work, we showcase SGTPy, a Python open-source code developed to calculate interfacial properties (interfacial concentration profiles and interfacial or surface tension) for pure fluids and fluid mixtures. SGTPy employs the Square Gradient Theory (SGT) coupled to the Statistical Associating Fluid Theory of Variable Range employing a Mie potential (SAFT-VR-Mie). SGTPy uses standard Python numerical packages (i.e., NumPy, SciPy) and can be used under Jupyter notebooks. Its features are the calculation of phase stability, phase equilibria, interfacial properties, and the optimization of the SGT and SAFT parameters for vapor–liquid, liquid–liquid and vapor–liquid–liquid equilibria for pure fluids and multicomponent mixtures. Phase equilibrium calculations include two-phase and multiphase flash, bubble and dew points, and the tangent plane distance. For the computation of interfacial properties, SGTPy incorporates several options to solve the interfacial concentration, such as the path technique, an auxiliary time function, and orthogonal collocation. Additionally, the SGTPy code allows the inclusion of subroutines from other languages (e.g., Fortran, and C++) through Cython and f2py Python tools, which opens the possibility for future extensions or recycling tested and optimized subroutines from other codes. Supporting Information includes a review of the theoretical expressions required to couple SAFT-VR-Mie equation of state with the SGT. The use and capabilities of SGTPy are illustrated through step by step examples written on Jupyter notebooks for the cases of pure fluids and binary and ternary mixtures in bi- and three- phasic equilibria. The SGTPy code can be downloaded from https://github.com/gustavochm/SGTPy.
Date Issued
2021-03-22
Date Acceptance
2021-02-01
Citation
Journal of Chemical Information and Modeling, 2021, 61 (3), pp.1244-1250
URI
http://hdl.handle.net/10044/1/87581
DOI
https://www.dx.doi.org/10.1021/acs.jcim.0c01324
ISSN
1549-9596
Publisher
American Chemical Society
Start Page
1244
End Page
1250
Journal / Book Title
Journal of Chemical Information and Modeling
Volume
61
Issue
3
Copyright Statement
© 2021 American Chemical Society.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/E016340/1
EP/J014958/1
EP/R013152/1
Subjects
Medicinal & Biomolecular Chemistry
0304 Medicinal and Biomolecular Chemistry
0307 Theoretical and Computational Chemistry
0802 Computation Theory and Mathematics
Publication Status
Published
Date Publish Online
2021-02-17
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