Ideal Adsorbed Solution Theory

Overview

Adsorption behaviours of gas mixtures can be predicted from pure component isotherms by using the Ideal Adsorbed Solution Theory (IAST).

The main IAST code was written by Cory Simon [1], and was then incorporated in pyGAPS. A very good explanation of the method, complete with use cases and recommendations can still be found on the pyIAST documentation

With the inclusion of the source code, several changes have been introduced, to improve the usability of the method and to conform it to the rest of the code. A tutorial of IAST within pyGAPS follows.

[1]

C. Simon, B. Smit, M. Haranczyk. pyIAST: Ideal Adsorbed Solution Theory (IAST) Python Package. Computer Physics Communications. (2015)

IAST calculations in pyGAPS

To use the IAST functionality, a list of pure component isotherms is needed. The isotherms can be either:

• A ModelIsotherm, where the model will be used for the calculation of spreading pressure. Some models cannot be used for IAST calculations.

• A PointIsotherm, where the spreading pressure calculation will use interpolated data.

The original pyIAST functions still exist, as iast_point() and reverse_iast(). They can be used to determine the adsorbed fraction of each adsorbate given their partial pressures, or vice-versa.

To use:

import pygaps.iast as pgi
iast_loadings = pgi.iast_point(
    isotherms=[iso1, iso2, iso3],
    partial_pressures=[0.1, 1.0, 2.3],
)

Since IAST is often used for binary mixture adsorption prediction, several new functions have been introduced which make it easier to do common calculations and generate graphs:

• iast_point_fraction() is a version of IAST requiring bulk fluid fractions and total pressure instead of partial pressures for each component.

  import pygaps.iast as pgi
  
  result_dict = pgi.iast_point_fraction(
      isotherms=[iso1, iso2, iso3],
      gas_mole_fraction=[0.1, 0.5, 0.4],
      total_pressure=2,
  )
  

• iast_binary_svp() is a function to calculate the selectivity of a known composition mixture as a function of pressure. This example will plot selectivities over a pressure range of 0.01 to 10 of an equimolar mixture of methane and ethane:

  import numpy
  import pygaps.iast as pgi
  
  result_dict = pgi.iast_binary_svp(
      isotherms=[ch4, c2h6],
      mole_fractions=[0.5, 0.5],
      pressures=numpy.linspace(0.01, 10, 30),
  )
  

• iast_binary_vle() is a function to calculate the gas-adsorbed equilibrium at a constant pressure, over the entire range of molar fractions. This example will plot the gas-adsorbed equilibrium for all molar fractions of methane in ethane at a pressure of 2 bar:

  import pygaps.iast as pgi
  
  result_dict = pgi.iast_binary_vle(
      isotherms=[ch4, c2h6],
      total_pressure=2,
  )
  

IAST examples

Check out the Jupyter notebook in the examples section for a demonstration.