Although multiple types of adsorption sites have long been observed in montmorillonite, a consistent explanation about the chemical structure of these adsorption sites has not yet been established. Identifying the cation interlayer adsorption sites based on the octahedral cation distribution on montmorillonite was investigated in this study by using a Density Functional Theory (DFT) simulation. A clay structural model (H[Al6MgFe]Si16O40(OH)8) with a similar composition to Wyoming SWy-1 montmorillonite was built, where two octahedral Al were respectively substituted by Fe and Mg, and H+ was the charge compensating cation. This model had twenty-one different possible configurations as a function of the distribution of octahedral Al, Fe, and Mg cations. The DFT simulations of 15 of these different configurations showed no preference for the formation of any configuration with a specific octahedral Fe-Mg distance. However, the H+ adsorption energy was separated into three distinct groups based on the number of octahedral jumps from Fe to Mg atoms. The H+ adsorption energy significantly decreased with increasing number of octahedral jumps from Fe to Mg. Assuming an even probability of occurrence of 21 octahedral structures in montmorillonite, the percentages of these three groups are 43, 43, and 14%, respectively, which are very close to the three major sites on montmorillonite from published cation adsorption data. These DFT simulations offer an entirely new explanation for the location and chemical structure of the three major adsorption sites on montmorillonite, namely, all three sites are in the interlayer, and their adsorption strengths are a function of the number of octahedral jumps from Fe to Mg atoms.
Ion-exchange modeling is used widely to describe and predict ion-adsorption data on clay minerals. Although the model parameters are usually optimized by curve fitting experimental data, this approach does not confirm the identity of the adsorption sites. The purpose of the present study was to extend to divalent cations a previous study on the retention of monovalent cations on Na-saturated montmorillonite (NaMnt) which optimized some of the model parameters using density functional theory (DFT) simulations. The adsorption strength of divalent cations increased in the order Mg2+ < Cd2+ < Ca2+ < Sr2+ < Ba2+. After adding adsorption of metal hydroxide species (MOH+), the three-site ion-exchange model was able to describe adsorption data over a wide pH range (pH 1–10) on NaMnt. X-ray diffraction (XRD) analyses were conducted to investigate the interlayer dimension of clay samples under various conditions. The cation retention strengths of divalent cations did not correlate with interlayer dimensions. The XRD analyses of the Mnt showed a d001 value of 19.6 Å when saturated with alkaline earth cations, 22.1 Å with Cd2+, 15.6 Å with Na+, and 15.2 Å with H+. In the case of Na+, the 15.6 Å peak decreased gradually and disappeared, and new peaks at 22.1 and 19.6 Å appeared when the percentages of Mg2+ and Ba2+ adsorbed increased on NaMnt. The peak shifted from 22.1 to 20.3 and 19.6 Å when the pH increased for all cations except Cd2+, which stayed constant at 22.1 Å. The coexistence of multiple d001 peaks in the XRD patterns suggested that the interlayer cations were segregated, and that the interlayer ion–ion interactions among different types of ions were minimized.
Ion-exchange modeling is one of the most widely used methods to predict ion adsorption data on clay minerals. The model parameters (e.g. number of adsorption sites and the cation adsorption capacity of each site) are optimized normally by curve fitting experimental data, which does not definitively identify the local environment of the adsorption sites. A new approach for constructing an ion-exchange model was pursued, whereby some of the parameters needed were obtained independently, resulting in fewer parameters being based on data-curve fitting. Specifically, a reversed modeling approach was taken in which the number of types of sites used by the model was based on a previous first-principles Density Functional Theory study, and the relative distribution of these sites was based on the clay’s chemical composition. To simplify the ion-exchange reactions involved, montmorillonite was Na-saturated to produce a well-controlled Na-montmorillonite (NaMnt) adsorbent. Ion adsorption data on NaMnt were collected from batch experiments over a wide range of pH, Cs+ concentrations, and in the presence of coexisting cations. Ion-exchange models were developed and optimized to predict these cation adsorption data on NaMnt. The maximum amount of adsorption of monovalent cations on NaMnt was obtained from the plateau of the adsorption envelope data at high pH. The remaining equilibrium constants (pK) were optimized by curve fitting the edges of the adsorption envelope data. The resultant three-site ion-exchange model was able to predict the retention of Li+, Na+, K+, and Cs+ very well as a function of pH. The model was then tested on adsorption envelopes of various combinations of these cations, and on Cs+ adsorption isotherms at three different pH values. The pK values were constant for all assays. The interlayer spacing of NaMnt was also analyzed to investigate its relation with cation adsorption strength. An X-ray diffraction study of the samples showed that the measured d001 values for these cations were consistent with their adsorption pK values. The Cs+ cation showed a strong ability to collapse the interlayer region of montmorillonite. In the presence of multiple competing cations, the broadening and presence of multiple d001 XRD peaks suggested that the cations in the interlayers may be segregated.
This article was updated to correct changes to the text made during production. The phrase "Fe can be placed in one of three ways at j = 1 and 2" was updated.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.