Surface Complexation Model Research Articles

Mn loading on montmorillonite surfaces for Cd stabilization: Insights from density functional theory calculations and surface complexation modeling

The latest works have been devoted to the stabilization mensuration for heavy metals and indicate that clay minerals can promote Cd(II) precipitation by favoring the retention of Mn(II). The assessment however has been tempered due to lacking the information about the molecular-level surface complexation structure and Cd nucleation process on clay surfaces. In this study, microscopic mechanisms for adsorption and stabilization of Cd at montmorillonite interfaces with or without Mn loading were leveraged by combining surface complexation model (SCM) evaluations and density functional theory (DFT) calculations. Mn(II) substitution resulted in increases in surface acidity equilibrium constant (pKa) by about 1 unit and complexation constant (lgK(SOCd+)) of Cd(II) by about 0.15 units at clay surface, and Mn(II) adion can provide extra active sites (i.e., OH− groups) for complexing Cd(II) via hydrolysis. DFT calculations revealed Mn(II) and Cd(II) adions bind on base surfaces by isomorphic substitutions through weak long-range interactions, whereas on edge surfaces by surface complexation with strong but short-range connections. Adsorption energy calculations and electrostatic distribution showed heterogenous nucleation with subsequent cations on clay surfaces was thermodynamically favored, the stabilization process underwent the steps of the adsorption-hydrolysis-precipitation. The derived results provide a quantitative basis for understanding the precipitation and heterogenous nucleation of cations on clay surfaces in surficial environments.

Measurement of total amine site concentrations on bacterial cell surfaces using selective site-blocking and potentiometric titrations

Bacterial cell surface amine binding sites can form strong complexes with both toxic metal cations and anionic contaminants, thereby affecting the behavior of these contaminants in both natural and engineered systems. In this study, a novel approach was developed to measure the concentration of total amine sites on bacterial cell surfaces by combining selective site-blocking, potentiometric titrations and surface complexation modeling. Our controls show that the amine blocker sulfo-N-hydroxysulfosuccinimide acetate (SNHS) selectively reacts with primary and secondary amine sites but does not react with other binding sites on the bacterial cell surface. Amine site concentrations on bacterial cell surfaces, therefore, can be measured as the difference between the total site concentrations of un-blocked and SNHS-blocked bacterial samples. We measured amine site concentrations on Bacillus subtilis and Pseudomonas putida of 52 ± 5 and 78 ± 6 μmol/g, respectively, which account for 24% and 32% of the total binding sites on each bacterial surface. Our results suggest that amine sites can be present in relatively high concentrations on bacterial surfaces, and further studies that are focused on the role of cell surface amine sites on the transport and bioavailability of toxic metal cations and anionic contaminants are crucial.

Modeling of phosphate speciation on goethite surface: Effects of humic acid

Iron (hydr)oxides and humic acid (HA) are important active components in soils and usually coexist in the environment. The effects of HA on the adsorption and subsequent immobilization of phosphate on iron (hydr)oxide surface are of great importance in studies of soil fertility and eutrophication. In this study, two types of goethite with different particle sizes were prepared to investigate the phosphate adsorption behaviors and complexation mechanisms in the absence or presence of HA by combining multiple characterization and modeling studies. The adsorption capacity of micro- (M-Goe) and nano-sized goethite (N-Goe) for phosphate was 2.02 and 2.04 μmol/m2, which decreased by ∼25% and ∼45% in the presence of 100 and 200 mg/L HA, respectively. Moreover, an increase in equilibrium phosphate concentration significantly decreased the adsorption amount of goethite for HA. Charge distribution-multisite surface complexation (CD-MUSIC) and natural organic matter-charge distribution (NOM-CD) modeling identified five phosphate complexes and their corresponding affinity constants (logKP). Among these phosphate complexes, FeOPO2OH, (FeO)2PO2, and (FeO)2POOH species were predominant complexes on the surface of both M-Goe and N-Goe across a wide range of pH and initial phosphate concentrations. The presence of HA had little effect on the coordination mode and logKP of phosphate on goethite surface. These results and the obtained model parameters shed new lights on the interfacial reactivity of phosphate at the goethite-water interface in the presence of HA, and may facilitate further prediction of the environmental fate of phosphate in soils and sediments.

The adsorption of U(VI) on chlorite: batch, modeling and XPS study

Abstract A mechanistic modelling of the adsorption processes onto individual minerals presenting in the near- and far-fields can greatly enhance the credibility of long-term safety assessments of granite-based geological repositories. In this study, the titration and U(VI) adsorption characteristics of chlorite, one of the major minerals of rock fractures, have been studied. Potentiometric titration curves at two ionic strengths (0.1 and 0.4 mol/L NaCl) are successfully interpreted by considering protonation/deprotonation reactions on generic edge sites (≡SOH) in the framework of a non-electrostatic surface complexation model (SCM). The adsorption of U(VI) on chlorite was reached after 24 h, the adsorption kinetics can be described by a pseudo-second-order model. A non-electrostatic SCM with three surface complexes (≡SOUO2 +, ≡SO(UO2)3(OH)5 and ≡SO(UO2)3(OH)7 2−) was set up based on pH edges of U(VI) at adsorption equilibrium in the absence of CO2. Additional, experimental data measured as a function of U(VI) concentration, solid-to-liquid ratio and carbonate concentration were well reproduced by the proposed model. Finally, parallel experiments were conducted using X-ray photoelectron spectroscopy (XPS) to analyze the variation of U(VI) surface species speciation at different pH values. The good agreement between SCM prediction and XPS analysis demonstrates the reliability of the model in predicting and quantifying the radionuclides retention by chlorite.

Synthesis and characterization of a new natural saccharide polymer (n-LTP) for adsorption of Methylene blue dye from an aqueous solution

ABSTRACT In this study, a new natural polysaccharide material, i.e., n-LTP, was synthesized by mixing Linum usitatissimum seed oil cake, Trigonella foenum-graecum and Plantago physilium husk in a 1:1:1 ratio for adsorption of Methylene blue. BET, FTIR and SEM reveal the presence of various organic and inorganic groups besides heterogeneous surfaces of the adsorbent having a surface area of 384 m2/g. It is observed that at pH values of 12, contact time of 100 min, n-LTP dose of 1.5 mg, with dye concentration of 70 ppm at 50 °C, nearly 88% of adsorption take place. Experimental data shows that the Freundlich isotherm (R2 = 0.96) and pseudo-first-order kinetic model (R2 = 0.9538) fit best to the process. A thermodynamic study showed that the process was spontaneous, endothermic and feasible. Electrostatic, π -π and hydrogen bonding interactions are involved in MB dye adsorption on n-LTP as confirmed by a surface complexation model (SCM). Overall, results of the study explored the potential f n-LTP for removal of MB dye from contaminated water. This study is novel as till now, to the best of our knowledge, no work has been reported on MB adsorption using n-LTP as Q5 an adsorbent specifically.

Study on advection–dispersion behavior for simulation of 3H, 99Tc, and 90Sr transport in crushed sandstone of column experiments

Abstract In order to establish a universal and safety-compliant post-closure safety assessment technique, it is necessary to develop appropriate models to explain the migration behavior of radioactive materials within the rock system. Advection-dispersion experiments (ADE) have proven successful in designing transport models through a calibration/validation process of breakthrough curves (BTCs). In the present investigation, we employed a dynamic column device to examine the transport of Tritium (3H), Technetium-99 (99Tc), and Strontium-90 (90Sr) in crushed sandstone. Non-reactive transport experiments utilizing conservative tracers enabled us to determine the transport parameters, including retardation factors (R) and dispersivity (α). Our study focused on investigating the surface complexation model (SCM) using an additive approach coupled with the advection-dispersion equation to simulate the reactive transport behavior of 90Sr. The results affirm the robustness of our chosen thermodynamic database and modeling approach, emphasizing the criticality of accurately modeling and predicting reactive transport behavior in porous media.

Surface complexation adsorption of Tl(III) by Fe and Mn (hydr)oxides

Thallium(III) (Tl(III)) is mobile in acidic environments and under ligand complexation, posing a potential threat to the environment and human health. The adsorption of Tl(III) on manganese and iron (hydr)oxides will affect its environmental mobility and engineering removal efficiency. However, the adsorption behavior and interfacial reaction mechanism of Tl(III) remain largely unknown. This study is the first to elucidate the surface complexation mechanism of Tl(III) on Fe/Mn (hydr)oxides and to investigate the adsorption behavior of Tl(III) under the influence of typical environmental ligands. Deprotonation of surface hydroxyl groups contributes to the increase in adsorption capacity for Tl(III) (δ-MnO2, 1619.93 mg g−1; α-FeOOH, 48.25 mg g−1; and α-Fe2O3, 58.66 mg g−1 from Langmuir thermodynamic fitting). Surface complexation modeling reveals tridentate complexation of Tl(III) on birnessite and monodentate complexation on iron (hydr)oxides. The anionic ligand strongly inhibits the adsorption of Tl(III) (up to 16.0 %–40.0 %) by complexing with Tl(III) and occupying the adsorption sites. In addition, HA also reduces the adsorption of Tl(III) by 8.2 %–23.2 % by exacerbating the aggregation and surface coating of the adsorbent particles. New insights into the binding mechanism of Tl(III) on Fe/Mn oxides can help to guide the development of efficient Tl(III) removal adsorbents.

Characterization of Surfactant Adsorption Profile in Carbonates Under Severe Reservoir Conditions With Geochemical Modeling Approach

Abstract Chemical flooding has gained ample popularity as an effective technique to increase oil displacement and sweep efficiencies. However, very limited numerical applications of chemical flooding (surfactant and polymer) in carbonates are reported in the literature. Therefore, a geochemical-based surface complexation model is developed to characterize the adsorption profile of surfactants for the first time across the length of a core/reservoir. The proposed model is validated with various zeta-potential measurements and also with a recently conducted chemical flooding study. Additionally, sensitivity analysis of various parameters is performed, and it is found that surfactant effluent concentration decreases with the increase in flood temperature. It is observed that salinity reduction decreases the surfactant adsorption, increases the ionic repulsion amid the rock surface charge and the chemical species polarity. Similarly, when the concentration of surfactant is increased, the adsorption of surfactant concentration increases. However, the increase in surfactant adsorption is insignificant. The effect of sulfate spiking in chemical flooding is also investigated and it is found that an increase in sulfate concentration reduces the adsorption of surfactant across the reservoir. Moreover, the lowermost surfactant adsorption level is achieved through the injection of diluted water (<0.1 mg/g).

A triple-layer based surface complexation model for oil-brine interface in low-salinity waterflooding: Effect of sulphate interaction with carboxylic and basic groups, pH and temperature

The determination of the electrokinetic properties of oil-brine interface is necessary to understand and evaluate the low-salinity waterflooding (LSWF) effect on enhanced oil recovery (EOR). Among the least understood aspects are the effect of SO42- interaction with the polar oil components, and temperature on the zeta-potential of the oil-brine interface. Therefore, a novel triple-layer based surface complexation model (SCM) was developed to capture the effect of SO42- interaction with both carboxylic and amine sites. One of the key uncertainties in a SCM is the surface site density of the functional groups. In this regard a Monte-Carlo based optimization algorithm for determination of these parameters as a function of pH and brine composition was devised. The SCM was successfully validated with the published zeta-potential data and was further used to evaluate the electrokinetic properties of oil-brine interface in a wide range of temperature and pH and to unravel the reason behind positive oil-brine zeta-potential at high ionic strength and pH, as reported for some crude oils in the literature. A sensitivity analysis was conducted to determine the relative contribution of site densities of carboxylic and amine groups as well as the capacitances to the oil-brine zeta-potential. The results clearly show that the interaction of SO42- ions with both carboxylic and particularly amine groups affects the surface potential significantly, thus should not be underestimated. Presence of SO42- in Na2SO4 and MgSO4 brines results in an incremental negative zeta-potential compared to that in NaCl and MgCl2 brines; confirming its role in changing charge distribution in the Stern layer. If these interactions are ignored, it should be compensated for by artificially adjusting concentration of positively and neutrally charged surface species. One important finding is that, despite the common perceptions, the site density of the oil polar groups is not constant and should be changed as pH and brine composition are changed and linear correlations between acid and base number and site densities are not justifiable. It is also found that zeta-potential tends to shift to neutral values as temperature is elevated due to the increased adsorption of divalent cations to the interface. The findings of this paper can help predict the zeta-potential of oil-brine interface more accurately and explain the observed trends in the experimental data.

Surface properties of schwertmannite with different sulfate contents and its effect on Cr(VI) adsorption

Sulfate is a critical component of schwertmannite. However, the sulfate content of schwertmannite decreases with the increase in AMD-polluted river pH value, and its impact on the surface properties and Cr(VI) adsorption of schwertmannite remains unclear. To address this issue, different methods, including batch adsorption, N2 physisorption, scanning electron microscopy (SEM), potentiometric titration, X-ray photoelectron spectroscopy (XPS), attenuated total reflectance–Fourier transform infrared spectroscopy (ATR-FTIR) in combination with two-dimensional correlation spectroscopy (2D-COS) analysis, and surface complexation modeling (SCM) were employed. Our results showed that sulfate existed as both non-protonated bidentate-binuclear complexes and non-protonated outer-sphere complexes in schwertmannite. The surface morphology and particle size of schwertmannite were unaffected by the sulfate content. However, a decrease in sulfate content resulted in a drop in the negative charge on the surface of schwertmannite, which is conducive to particle aggregation. An increase in pH, on the other hand, raised the negative charge and encouraged the dispersion of the particles. And then, reducing the sulfate content of schwertmannite led to a decrease in acid-base buffer and Cr(VI) adsorption capacity of schwertmannite. The adsorption process of Cr(VI) by schwertmannite can be divided into two stages. In the first stage, Cr(VI) was adsorbed primarily through anion exchange reactions with the sulfate; however, the contribution of surface complexation gradually increased as the initial sulfate content decreased because of a reduced likelihood of anion exchange and an increase in the specific surface area of schwertmannite. Additionally, the behavior of sulfate and Cr(VI) in this stage could be predicted based on the initial sulfate content of schwertmannite. In the second stage, surface complexation with hydroxyl sites became the predominant mechanism of adsorption, which still exhibited great potential at higher Cr(VI) concentrations. Finally, the aforementioned hypothesis was used to establish a CD-MUSIC model, and the fitting results demonstrated that the density and Cr(VI) adsorption capacity of the sulfate site dropped as the sulfate content decreased, while the hydroxyl site was less impacted. The findings have provided insights into further understanding the properties of schwertmannite and its adsorption of Cr(VI).

Rare Earth Element Adsorption to Clay Minerals: Mechanistic Insights and Implications for Recovery from Secondary Sources.

The energy transition will have significant mineral demands and there is growing interest in recovering critical metals, including rare earth elements (REE), from secondary sources in aqueous and sedimentary environments. However, the role of clays in REE transport and deposition in these settings remains understudied. This work investigated REE adsorption to the clay minerals illite and kaolinite through pH adsorption experiments and extended X-ray absorption fine structure (EXAFS). Clay type, pH, and ionic strength (IS) affected adsorption, with decreased adsorption under acidic pH and elevated IS. Illite had a higher adsorption capacity than kaolinite; however, >95% adsorption was achieved at pH ∼7.5 regardless of IS or clay. These results were used to develop a surface complexation model with the derived binding constants used to predict REE speciation in the presence of competing sorbents. This demonstrated that clays become increasingly important as pH increases, and EXAFS modeling showed that REE can exist as both inner- and outer-sphere complexes. Together, this indicated that clays can be an important control on the transport and enrichment of REE in sedimentary systems. These findings can be applied to identify settings to target for resource extraction or to predict REE transport and fate as a contaminant.

Effects of Fe(II) and humic acid on U(VI) mobilization onto oxidized carbon nanofibers derived from the pyrolysis of bacterial cellulose

The effects of Fe(II) and humic acid on U(VI) immobilization onto oxidized carbon nanofibers (Ox-CNFs, pyrolysis of bacterial cellulose) were investigated by batch, spectroscopic and modeling techniques, with results suggesting that, Ox-CNFs exhibited fast adsorption rate (adsorption equilibrium within 3 h), high adsorption performance (maximum adsorption capacity of 208.4 mg/g), good recyclability (no notable change after five regenerations) in the presence of Fe(II) towards U(VI) from aqueous solutions (e.g., 40 % reduction and 10 % adsorption at pH 8.0), which was attributed to the various oxygen-containing functional groups, excellent chemical stability, large specific surface area and high redox effect. U(VI) adsorption increased with increasing pH from 2.0 to 5.0, then high-level plateau and remarkable decrease were observed at 5.0–6.0 and at pH > 6.0, respectively. According to FT-IR and XPS analysis, a negative correlation between U(VI) reduction and organic in the presence of Fe(II) implied that U(VI) reduction was driven by Fe(II) while inhibited by humic acid. The interaction mechanism of U(VI) on Ox-CNFs was demonstrated to be adsorption and ion exchange at low pH and reduction at high pH according to XPS and surface complexation modeling. These findings filled the knowledge gaps pertaining to the effect of Fe(II) on the transformation and fate of U(VI) in the actual environment. This carbon material with distinctive performance and unique topology offers a potential platform for actual application in environmental remediation.

Speciation controls on Ni adsorption to birnessite and organo-birnessite

Nickel (Ni) is an essential micronutrient for phytoplankton. Its importance to both the modern and ancient Earth system has encouraged development of Ni and its isotopes as biogeochemical tracers. To interpret these signatures however, understanding of how Ni and its isotopes are recorded in marine archives is required. Here we simulate different inorganic and organic Ni species in seawater and investigate their adsorption behaviours to variably crystalline phyllomanganates and organo-mineral phyllomanganate. We conduct pH adsorption edge experiments to determine the binding affinity of the different Ni species to the minerals and then perform desorption experiments to operationally define Ni bonding strength. We also use thermodynamic surface complexation modelling to constrain Ni adsorption mechanisms. From the adsorption edges and stability constants generated from our modelling, the binding affinity increases in the order of Ni-formate+ (aq) < NiCl+ (aq) < Ni2+ (aq). From the desorption experiments, desorption at pH 8 is non quantitative and increases in the opposite order of Ni-formate+ (aq) > NiCl+ (aq) ∼ Ni2+ (aq). For the organo-mineral however, Ni desorption at pH 8 is non quantitative and similar for all three experiments, and is significantly higher compared to the variably crystalline phyllomanganates. Although both our adsorption and desorption experiments were performed over 48 h, it is possible that desorption is somewhat slower than adsorption such that a longer desorption period may result in further Ni loss to solution and thus greater adsorption reversibility. Taken together however, the Ni-formate+ (aq) and Ni organo-birnessite desorption experiments suggest that Ni bonding strength is decreased by the presence of organic carbon, compared to NiCl+ (aq) and Ni2+ (aq). Because bonding strength governs equilibrium stable isotope fractionation, we use our experimental findings to suggest how Ni speciation in seawater might influence Ni isotope behaviour during adsorption to phyllomanganate. We find that our suggestions are consistent with isotopic measurements from natural sediments. Although the balance of Ni adsorption versus incorporation during uptake to phyllomanganates may play a greater part in explaining the variation in the Ni isotope composition in Mn-rich sediments, Ni speciation and the presence of organics might increase the range of δ60Ni values measured in natural settings.

Machine learning surrogates for surface complexation model of uranium sorption to oxides

The safety assessments of the geological storage of spent nuclear fuel require understanding the underground radionuclide mobility in case of a leakage from multi-barrier canisters. Uranium, the most common radionuclide in non-reprocessed spent nuclear fuels, is immobile in reduced form (U(IV) and highly mobile in an oxidized state (U(VI)). The latter form is considered one of the most dangerous environmental threats in the safety assessments of spent nuclear fuel repositories. The sorption of uranium to mineral surfaces surrounding the repository limits their mobility. We quantify uranium sorption using surface complexation models (SCMs). Unfortunately, numerical SCM solvers often encounter convergence problems due to the complex nature of convoluted equations and correlations between model parameters. This study explored two machine learning surrogates for the 2-pK Triple Layer Model of uranium retention by oxide surfaces if released as U(IV) in the oxidizing conditions: random forest regressor and deep neural networks. Our surrogate models, particularly DNN, accurately reproduce SCM model predictions at a fraction of the computational cost without any convergence issues. The safety assessment of spent fuel repositories, specifically the migration of leaked radioactive waste, will benefit from having ultrafast AI/ML surrogates for the computationally expensive sorption models that can be easily incorporated into larger-scale contaminant migration models. One such model is presented here.

Prediction of adsorption of metal cations by clay minerals using machine learning

Adsorption of heavy metals by clay minerals occurs widely at the solid-liquid interface in natural environments, and in this paper, the phenomenon of adsorption of Cd2+, Cu2+, Pb2+, Zn2+, Ni2+ and Co2+ by montmorillonite, kaolinite and illite was simulated using machine learning. We firstly used six machine learning models including Random Forest(R), Extremely Forest(E), Gradient Boosting Decision Tree(G), Extreme Gradient Boosting(X), Light Gradient Boosting(LGB) and Category Boosting(CAT) to feature engineer the metal cations and the parameters of the minerals, and based on the feature engineering results, we determined the first order hydrolysis constant(log K), solubility product constant(SPC), and higher hydrolysis constant (HHC) as the descriptors of the metal cations, and site density(SD) and cation exchange capacity(CEC) as the descriptors of the clay minerals. After comparing the predictive effects of different data cleaning methods (pH50 method, Box method and pH50-Box method) and six model combinations, it was finally concluded that the best simulation results could be achieved by using the pH 50-Box method for data cleaning and Extreme Gradient Boosting for modelling (RMSE = 4.158 %, R2 = 0.977). Finally, model interpretation was carried out using Shapley explanation plot (SHAP) and partial dependence plot(PDP) to analyse the potential connection between each input variable and the output results. This study combines machine learning with geochemical analysis of the mechanism of heavy metal adsorption by clay minerals, which provides a different research perspective from the traditional surface complexation model.

Deep neural network surrogate for surface complexation model of metal oxide/electrolyte interface

HypothesisSurface Complexation Models (SCM) are one of the most successful geochemical thermodynamics models of the speciation and charging of the mineral/electrolyte interface. However, finding unique and transferable SCM parameter values by fitting experimental data using existing numerical solvers is often challenging. We hypothesized that SCM surrogates built using Artificial Intelligence algorithms provide an alternative strategy for determining model parameter values and thus offer an ultrafast prediction of electrical double layer characteristics of metal oxide/electrolyte interface. ExperimentsWe generated synthetic datasets of surface charge and electrokinetic potential as a function of pH, ionic strength, varying site densities, acidity, and ion-affinities of mineral surfaces using the 2-pK Triple Layer Model - one of the most used generic SCM. We explored a wide range of types of mineral surfaces using random walks in the parameter space. Next, we trained and validated two AI surrogates using our synthetic SCM data. FindingsWe showed that AI-SCM surrogates for oxide/electrolyte interfaces are possible and cost-effective. They allow ultrafast and accurate SCM parametrization using synthetic data. AI-SCM can predict thermodynamic parameters from just a few titration data points, such as ion affinities and proton binding constants. What is more, the computational strategy we presented here to surrogate geochemical models by pre-trained AI architectures is more universal and can be applied to other geochemical/thermodynamic models – replacing the computationally expensive solvers with trained AI, thus minimizing computing costs and speeding up data analysis.

Sorption of U(VI) on MX-80 Bentonite and Granite in Ca-Na-Cl Saline Solutions

Uranium has been identified as an element of interest for the safety assessment of a deep geological repository for used nuclear fuel. This paper examines the sorption behavior of U(VI) onto MX-80 bentonite and granite in Ca-Na-Cl solutions of varying ionic strengths [0.05 to 3 mol/kgw (m)] and across a pH range of 4 to 10. U(VI) sorption on MX-80 showed that U(VI) sorption gradually increased with pHm until pHm = 6, where it reached its maximum, and decreased slightly with pHm until pHm = 8, and then became constant. U(VI) sorption on granite increased along with pHm, reached the maximum around pHm = 7 to 8, and then slightly decreased with pHm. Both MX-80 and granite showed essentially no ionic strength dependence for sorption of U(VI). A nonelectrostatic surface complexation model successfully predicted sorption of U(VI) onto MX-80 and granite using the formation of an inner-sphere surface complex. Optimized values of surface complexation reaction constants (log K0) for the formation reactions of these surface species are proposed.

Natural and synthetic plagioclases: Surface charge characterization and sorption of trivalent lanthanides (Eu) and actinides (Am, Cm)

The environmental fate of radiotoxic actinides may be controlled by their interactions with feldspars. Here, the sorption of trivalent minor actinides (Am, Cm) and their rare earth analog Eu onto synthetic pure Ca-feldspar (anorthite) and natural plagioclases of different Ca contents is investigated, covering ranges of [M3+] (52 nM–10 μM), solid-liquid ratios (1–3 g/L), pH (3–9), and ionic strengths (0.01–0.1 M NaCl) under both ambient and CO2-free conditions. As a first step to understand the uptake behavior of the heavy metals, the hitherto unknown surface charge and (de-)protonation reaction of Ca-feldspars is characterized. The zeta potential shows an unusual increase and charge reversal between pH 4 and 7 , which becomes more pronounced with increasing amounts of Ca in the crystal lattice and is likely connected to adsorption and/or surface precipitation of dissolved Al3+. Streaming potential measurements yield (de)protonation constants for anorthite surface sites of log K- = −6.94 ± 0.38 and log K+ = +6.84 ± 0.38. Batch sorption data shows strong immobilization of M3+ by plagioclases at mildly acidic and basic pH. Time-resolved laser fluorescence spectroscopy using Cm indicates the formation of an inner-sphere complex and its two hydrolyzed forms. The complex reactivity of dissolved Al3+ at the plagioclase-water interface severely complicated the development of a surface complexation model, emphasizing the need for additional research in this area. Our study highlights the importance of molecular-level studies to understand surface reactions and uncover unknown processes, which may have significant impact on the transport of (radiotoxic) contaminants in the geosphere.

The Role of the Mineralogical Composition on Wettability via Flotation Test and Surface Complexation Modeling (SCM)

Minerals are the chief constituents of rocks and have varied properties, such as the surface area, surface charge, site density, etc. Hence, numerous interactions are bound to occur in a reservoir during rock–fluid (i.e., rock, crude oil and brine) interactions. This study seeks to assess the role of the mineralogical composition in the wettability of sandstone rocks (SRs) and mineral mixture (MM) using both surface complexation modeling (SCM) and a flotation test. From the considered sandstone rocks, both the experimental results and the simulated counterparts revealed that the SRs were preferentially hydrophilic. For the MM, when the mass fraction of the hydrophobic mineral was increased, the affinity of the MM became slightly hydrophobic, and vice versa. For the dominant sandstone reservoir rock minerals with predominantly negatively charged surfaces, negligible oil adsorption took place due to the interfacial repulsive forces at the oil–brine and mineral–brine interfaces. For the MM with low calcite content, the wetting preference was influenced by the mineral with a prominent surface area. Our developed model portrayed that the main mechanism of oil adhesion onto sandstone minerals was divalent cation bridging. Nonetheless, adhesion of carboxylate (&gt;COO−) onto the illite, montmorillonite and calcite sites also took place, with the latter being more pronounced.

Face-dependent phosphate speciation on goethite: CD-MUSIC modeling and ATR-FTIR/2D-COS study

Understanding the face-dependent phosphate adsorption mechanisms and their variations with environmental conditions is of great significance for revealing phosphate adsorption mechanisms on various goethites and predicting phosphorus speciation in iron-rich soils. In this study, micro- (MicroGoe) and nano-sized goethite (NanoGoe) were synthesized and used to investigate the face-dependent adsorption behaviors of proton and phosphate on goethite by combining the charge distribution-multisite surface complexation (CD-MUSIC) model and attenuated total reflectance Fourier transform infrared (ATR-FTIR). The results demonstrated that MicroGoe had a higher charge density and phosphate adsorption capacity than NanoGoe, which could be attributed to the higher site density of ≡FeOH−0.5 and inner-layer capacitance arising from a higher proportion of capping face and rougher surface of MicroGoe. The logKH of ≡FeOH−0.5 on the main and capping face was 8.2 and 8.9, respectively. Three types of monodentate mononuclear phosphate complexes in different protonated states were identified, along with the non-protonated bidentate complex. Protonated monodentate complexes were formed at relatively low pH and high surface loadings, whereas non-protonated complexes were the predominant species at intermediate to high pH. MicroGoe had a higher percentage of monodentate complexes than NanoGoe, and both goethites had considerably lower phosphate adsorption on the capping face than on the main face. The results provide valuable insights into the interfacial reactivity of goethite prepared with various methods and facilitate further prediction of phosphorus speciation and availability in iron-rich soils.