pyIAST: Ideal adsorbed solution theory (IAST) Python package

Published: 1 March 2016| Version 1 | DOI: 10.17632/3kkcn7gpwf.1
Cory M. Simon, Berend Smit, Maciej Haranczyk


This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract 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... Title of program: pyIAST Catalogue Id: AEZA_v1_0 Nature of problem Using ideal adsorbed solution theory (IAST) to predict mixed gas adsorption isotherms from pure-component adsorption isotherm data. Versions of this program held in the CPC repository in Mendeley Data AEZA_v1_0; pyIAST; 10.1016/j.cpc.2015.11.016



Statistical Physics, Computational Physics, Thermodynamics