pyIAST: Ideal adsorbed solution theory (IAST) Python package

Ideal adsorbed solution theory (IAST) is a widely-used thermodynamic framework to readily predict mixed-gas adsorption isotherms from a set of pure-component adsorption isotherms. We present an open-source, user-friendly Python package, pyIAST, to perform IAST calculations for an arbitrary number of...

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Veröffentlicht in:Computer physics communications Jg. 200; H. C; S. 364 - 380
Hauptverfasser: Simon, Cory M., Smit, Berend, Haranczyk, Maciej
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Netherlands Elsevier B.V 01.03.2016
Elsevier
Schlagworte:
Adsorption
Computer simulation
IAST
Ideal adsorbed solution theory
Isotherms
Mathematical analysis
Mathematical models
Mixed-gas adsorption
Packages
Source code
Summaries
Mixed-gas adsorption
Ideal adsorbed solution theory
IAST
ISSN:0010-4655, 1879-2944
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Zusammenfassung:Ideal adsorbed solution theory (IAST) is a widely-used thermodynamic framework to readily predict mixed-gas adsorption isotherms from a set of pure-component adsorption isotherms. We present an open-source, user-friendly Python package, pyIAST, to perform IAST calculations for an arbitrary number of components. pyIAST supports several common analytical models to characterize the pure-component isotherms from experimental or simulated data. Alternatively, pyIAST can use numerical quadrature to compute the spreading pressure for IAST calculations by interpolating the pure-component isotherm data. pyIAST can also perform reverse IAST calculations, where one seeks the required gas phase composition to yield a desired adsorbed phase composition. Source code: https://github.com/CorySimon/pyIAST Documentation: http://pyiast.readthedocs.org/en/latest/ Program title: pyIAST Catalogue identifier: AEZA_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEZA_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: MIT No. of lines in distributed program, including test data, etc.: 38478 No. of bytes in distributed program, including test data, etc.: 1918879 Distribution format: tar.gz Programming language: Python. Operating system: Linux, Mac, Windows. Classification: 23. External routines: Pandas, Numpy, Scipy Nature of problem: Using ideal adsorbed solution theory (IAST) to predict mixed gas adsorption isotherms from pure-component adsorption isotherm data. Solution method: Characterize the pure-component adsorption isotherm from experimental or simulated data by fitting a model or using linear interpolation; solve the nonlinear system of equations of IAST. Running time: Less than a second.
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AC05-06OR23100; FG02-12ER16362
USDOE Office of Science (SC), Office of Workforce Development for Teachers & Scientists (WDTS)
ISSN:0010-4655
1879-2944
DOI:10.1016/j.cpc.2015.11.016