Abstract
Two methodologies were developed to predict adsorption equilibria of a binary system when one of the components is described by the dual-process Langmuir (DPL) model and the other component is described by either the single process Langmuir (SPL) or linear isotherm (LI) model. Energetic site matching with the DPL–SPL model considered perfect positive (PP), perfect negative (PN) and unselective (US) correlations, and that with the DPL–LI model considered PP and PN correlations. A consistent set of single and binary isotherms for O2 and N2 on 5A zeolite were used to successfully demonstrate these concepts. For the DPL–SPL binary system, PP meant O2 adsorbed only on the N2 low energy site, PN meant O2 adsorbed only on the N2 high energy site, and US meant O2 adsorbed on both sites with the ratio of its saturation capacity on each site the same as that for N2. For this case, the PP model predicted the binary data well and correctly predicted that O2 only adsorbed on the low energy site of N2; the PN model predicted the data poorly and US was close but not as good as PP. The binary predictions from the DPL–SPL model that require only single component information to obtain the single component DPL and SPL parameters were nearly as good as those obtained from a non-predictive formulation similar to the US correlation but that utilized all the single and binary data to obtain the single component DPL and SPL parameters. For the DPL–LI binary system, with O2 having an affinity for only one site, PN meant O2 interacted solely with the high energy site of N2 and PP meant O2 interacted solely with the low energy site of N2; and because O2 exhibited a linear isotherm (i.e., the Henry’s law constants from the SPL parameters), it did not affect the adsorption of N2 on its sites, but N2 did affect the adsorption of O2 on its sites. For this case, the PP model predicted the binary data well and correctly predicted that O2 did not affect the adsorption of N2, but that N2 did affect the adsorption of O2 on the low energy site of N2; the PN model predicted the data poorly.
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