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Manuscript Title: pyIAST: Ideal Adsorbed Solution Theory (IAST) Python Package
Authors: Cory M. Simon, Berend Smit, Maciej Haranczyk
Program title: pyIAST
Catalogue identifier: AEZA_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 200(2016)364
Programming language: Python.
Operating system: Linux, Mac, Windows.
Keywords: Ideal adsorbed solution theory, IAST, mixed gas adsorption.
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.