Comprehensive Assessment of the Accuracy of the Ideal Adsorbed Solution Theory for Predicting Binary Adsorption of Gas Mixtures in Porous Materials

Quantifying the adsorption of chemical mixtures in porous adsorbents is critical to developing these materials for useful separation applications. The ideal adsorbed solution theory (IAST) is the most widely applied mixing theory for predicting mixture adsorption using singlecomponent adsorption data, but a perceived lack of experimental data has limited previous efforts to explore the accuracy of FAST in a systematic way. In this paper, we take advantage of a large collection of binary experimental data for gas adsorption that became available recently (Cai. X et al., Ind. Eng. Chem. Res. 2021, 60; 639) to tackle this issue. We identify more than 400 examples in which binary adsorption data and single-component data are available in the same publication and apply LAST to all these examples. This analysis includes experimental data from 63 gas mixtures of 37 different molecular species and 174 different adsorbents. In addition to being the most systematic evaluation to date of the accuracy of LAST for gas adsorption, these data will be valuable for future efforts to test or develop mixing theories that improve upon FAST.

Automated summary

This paper systematically evaluates the accuracy of the ideal adsorbed solution theory (IAST) for gas adsorption using a large collection of binary experimental data, which will be valuable for future efforts to test or develop mixing theories that improve upon FAST. This analysis includes data from 63 gas mixtures of 37 different molecular species and 174 different adsorbents, making it the most systematic evaluation to date of the accuracy of IAST for gas adsorption.