Ion Exchange Thermodynamics at the Rutile–Water Interface: Flow Microcalorimetric Measurements and Surface Complexation Modeling of Na–K–Rb–Cl–NO<sub>3</sub> Adsorption

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The adsorption of aqueous ions onto natural mineral surfaces controls numerous mineral−water interactions and is governed by, among other numerous factors, ion dehydration and hydrolysis. This work explored the extent to which dehydration and hydrolysis affect the adsorption of three metal cations, Al 3+ , Cr 3+ , and Mn 2+ , onto quartz (SiO 2 ) and corundum (Al 2 O 3 ) surfaces at pH 3.8 through the integration of flow microcalorimetry (FMC), quartz crystal microbalance with dissipation (QCM-D) measurements and density functional theory (DFT) calculations. At pH 3.8, negligible amounts of Mn 2+ and Al 3+ are hydrolyzed, while 78% of Cr 3+ exist in hydrolyzed species. QCM-D and FMC measurements showed that Al 3+ and Cr 3+ adsorb to both surfaces, while Mn 2+ adsorbed only to Al 2 O 3 . DFT bond energy calculations confirmed the favorable bonding between the mineral surfaces and Al 3+ and Cr 3+ , and that Mn 2+ adsorption onto SiO 2 was unfavorable. Furthermore, FMC showed that on both surfaces, the adsorption of Al 3+ was endothermic and reversible, while that of Cr 3+ was exothermic and partially irreversible. Through the integration of experimental and computational methods, this work suggested that the reversible adsorption of unhydrolyzed cations (Mn 2+ and Al 3+ ) occurred through weak electrostatic interactions. The large energy cost required to dehydrate unhydrolyzed cations resulted in an endothermic adsorption process. Meanwhile, hydrolyzed Cr 3+ species can adsorb on quartz and corundum through covalent-bond formation, and thus, their adsorption was partially irreversible. Furthermore, the hydrolysis of Cr 3+ lowered the dehydration energy during adsorption, resulting in an exothermic adsorption. By using bond energies as a guide to indicate the possibility of thermodynamically favored adsorption, there was a strong agreement between the DFT and experimental techniques. The findings presented here contribute to understanding and predicting various mineral−water interfacial processes in the natural environment.

Section: Results and Discussionmentioning

confidence: 99%

Section: Results and Discussionmentioning

confidence: 99%

Section: Experimental Sectionmentioning

confidence: 99%

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Adsorption Study of Al³⁺, Cr³⁺, and Mn²⁺ onto Quartz and Corundum using Flow Microcalorimetry, Quartz Crystal Microbalance, and Density Functional Theory

Allen

Dai

et al. 2019

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“…The model was built with custom-made Mathematica notebooks, versions of which have been previously used to simulate the rutile, − magnetite, ferrihydrite, and goethite interfaces. They have also been extended to fit adsorption data to 290 °C. , The multistart optimization routine was integrated in the original SCM model to optimize multiple parameters using as criteria the mean squared error (MSE) and Model Selection Criterion (MSC), with larger MSC values indicating a better fit. , Both MSE and MSC depend on the experimental data, specifically the amount and variability of available data, and number of fitting parameters for the latter; thus, they are used to compare different fits for a single data set.…”

Section: Materials and Methodsmentioning

confidence: 99%

Assessment of Modeling Uncertainties Using a Multistart Optimization Tool for Surface Complexation Equilibrium Parameters (MUSE)

Bompoti

Chrysochoou

Machesky

2018

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The MUlti-start optimization algorithm for Surface complexation Equilibrium (MUSE) algorithm has been developed to optimize the fitting of thermodynamic constants for surface complexation modeling (SCM). Although there is a plethora of software to perform data fitting and determine intrinsic equilibrium constants, the algorithms used are highly dependent on initial values and choice of parameters. This limits their transferability to model other systems, for example, reactive transport processes. With this in mind, a hybridized optimization approach, based on a multistart algorithm combined with a local optimizer, has been developed to allow the simultaneous optimization of SCM parameters and to assess the sensitivity of these parameters to changes in the model assumptions. In this study, the CD–MUSIC formalism with a Basic Stern electrostatic model is utilized to model chromate adsorption on ferrihydrite, although the MUSE algorithm can be applied to any adsorption data set and be implemented in any model formulation. This study offers two innovative components to the inverse SCM modeling approach: (a) determination of the true global optimum by performing multiple minimizations of the mean squared error between the simulated and observed data using a large number of initial starting points and (b) quantitative simulation of spectroscopic pH-dependent profiles for two chromate surface complexes. We demonstrate that when MUSE is implemented to determine chromate log Ks, their dependence on other adjustable parameters such as specific surface area (SSA) and capacitance is relatively small (i.e., less than one unit difference for chromate log Ks on ferrihydrite) and can be accounted by mathematical functions determined through the MUSE algorithm. The robustness of the algorithm is demonstrated in the absence of the spectroscopy data as well, with traditional batch tests yielding similar thermodynamic constants as the spectroscopic profiles.

“…Surface complexation models (SCMs) have been successfully applied to describe and predict surface protonation and ion sorption at a host of interfaces, primarily metal oxides, − but also clay minerals, and ionic solids such as carbonates. , Although most SCMs mimic interfacial reactions fairly well, the parameters used in early models were not based on specific molecular-level data for the systems studied. Consequently, one experimental data set could be modeled by several different yet plausible sets of parameter values .…”

Section: Introductionmentioning

confidence: 99%

Surface Complexation Modeling Approach for Aluminum-Substituted Ferrihydrites

Adams

Machesky

Kabengi

2021

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Surface complexation models (SCMs) have been successfully used to describe and predict adsorption phenomena for a large number of surfaces. SCMs have benefited from advancements in the microscopic characterization of interfacial structure which has aided in constraining their parametrization. Yet, SCMs have not adequately addressed the role of defects and substitutions in surface reactivity despite the fact that such surfaces are more environmentally prevalent than their ideal counterparts. In this study, we address this challenge by investigating the aluminum-doped variant of ferrihydrite (Fh). We consider the placement of Al within the Fh structure and develop a basic Stern SCM accommodating that placement which we apply to a set of previously published ζ potential data. Our hypothesis is that Al primarily replaces Fe1 surface sites within the Fh structure forming singly coordinated AlOH surface groups possessing higher protonation constants than their FeOH counterparts. The SCM fits the ζ potential data adequately, including a close match to the isoelectric pH values (pHiep, ζ potential = 0) of 8.0, 8.5, and 8.9 for pure, 12% Al-substituted, and 24% Al-substituted Fh, respectively. Moreover, the fit slipping plane distance, where the ζ potential is assumed to be expressed, is consistent with previous modeling efforts. Although a wider variety of experimental data will be necessary to determine the true extent and location of Al substitution within the Fh structure, and to thoroughly characterize the charging and adsorptive properties of variously substituted Al-Fhs, our SCM represents a vital stepping stone toward developing more environmentally relevant SCMs.