pyIAST: Ideal Adsorbed Solution Theory (IAST) Python Package

Published: 21 Apr 2016 | Version 1 | DOI: 10.17632/msm8sws7n6.1
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Description of this data

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.

Experiment data files

peer reviewed

This data is associated with the following peer reviewed publication:

pyIAST: Ideal adsorbed solution theory (IAST) Python package

Published in: Computer Physics Communications

Latest version

  • Version 1

    2016-04-21

    Published: 2016-04-21

    DOI: 10.17632/msm8sws7n6.1

    Cite this dataset

    Haranczyk, Maciej; Simon, Cory; Smit, Berend (2016), “pyIAST: Ideal Adsorbed Solution Theory (IAST) Python Package”, Mendeley Data, v1 http://dx.doi.org/10.17632/msm8sws7n6.1

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Natural Sciences

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MIT Learn more

The files associated with this dataset are licensed under a MIT License licence.

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