Literature DB >> 21413784

On the use of the dual-process Langmuir model for correlating unary equilibria and predicting mixed-gas adsorption equilibria.

James A Ritter1, Shubhra J Bhadra, Armin D Ebner.   

Abstract

A new model has been developed for predicting mixed-gas adsorption equilibria from multicomponent gas mixtures based on the dual-process Langmuir (DPL) formulation. It predicts ideal, nonideal, and azeotropic adsorbed solution behavior from a knowledge of only single-component adsorption isotherms and the assertion that each binary pair in the gas mixture correlates in either a perfect positive (PP) or perfect negative (PN) fashion on each of the two Langmuir sites. The strictly PP and strictly PN formulations thus provide a simple means for determining distinct and absolute bounds of the behavior of each binary pair, and the PP or PN behavior can be confirmed by comparing predictions to binary experimental adsorption equilibria or from intuitive knowledge of binary pairwise adsorbate-adsorbent interactions. The extension to ternary and higher-order systems is straightforward on the basis of the pairwise additivity of the binary adsorbent-adsorbate interactions and two rules that logically restrict the combinations of PP and PN behaviors between binary pairs in a multicomponent system. Many ideal and nonideal binary systems and two ternary systems were tested against the DPL model. Each binary adsorbate-adsorbent pair exhibited either PP or PN behavior but nothing in between. This binary information was used successfully to predict ternary adsorption equilibria based on binary pairwise additivity. Overall, predictions from the DPL model were comparable to or significantly better than those from other models in the literature, revealing that its correlative and predictive powers are universally applicable. Because it is loading-explicit, simple to use, and also accurate, the DPL model may be one of the best equilibrium models to use in gas-phase adsorption process simulation.
© 2011 American Chemical Society

Year:  2011        PMID: 21413784     DOI: 10.1021/la104965w

Source DB:  PubMed          Journal:  Langmuir        ISSN: 0743-7463            Impact factor:   3.882


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