To investigate the effect of ionic strength as well as pH, two sets of experiments, in the presence of 0.1 and 0.05 mol·dm⁻³ NaCl, were used with a control having no NaCl present. The effect of surface area has been taken into consideration in the surface complexation studies using the JChess geochemical code. This chapter reports a study of the effect of pH on sorption of radionuclides to some granitic rocks and minerals. NaCl is used to create a low concentration brine/seawater environment. With the possible disposal/storage of nuclear waste in deep geological repository, and with the potential rise in sea levels due to climate change, there is growing concern regarding the possible intrusion of brine into repository vaults. Thus, it is important to understand the effect of sea water on sorption of radionuclides in the far-field.

For pH dependent sorption, 1 × 10⁻⁵ mol·dm⁻³ solutions of NiCl₂ were prepared, and the pH was adjusted from 4 to 11, with intervals of 0.6 to 0.8 on the pH scale using NaOH_(aq) and HCl_(aq). Different concentrations of pH adjusting solutions were made from very weak to very strong acid or base. This was important, to be able to vary the pH without significantly altering the concentration of the Ni solution. To move the pH to a lower pH value of about 4, a strong acid was preferred since very little volume of the acid was required thus, minimising the impact on the overall concentration of the solution. 0.1 g of every sample were weighed into a 20 cm³ vial and 20 cm³ of pH-adjusted solutions were added. 0.1 cm³ of spike solution was added. After shaking the batch was allowed to equilibrate over a period of 5 to 7 days. The effect of ionic strength was investigated by the addition of different amounts of NaCl in the bulk NiCl₂ solutions to give ionic strengths of 0.05 and 0.1 mol·dm⁻³ NaCl solutions. Sample separation was performed as described above and counting was performed for Ni using the scintillation counter. Packard TRI-CARB 2750 TR/LL Liquid Scintillation Counter: Used for Ni sorption studies, counting from 0 to 67 keV to 2σ (i.e. 95% of the counts fall within the confidence interval) for 20 min, and for measurements of calibration standards for the work on autoradiography. One powerful technique in radionuclide detection is Liquid Scintillation Counting (LSC). Although the technique is sensitive to alpha and, to a lesser extent, gamma emitting radionuclides, LSC is most extensively used for the determination of beta-emitters. The main advantage of LSC as compared to solid state detectors is its high-detection efficiency, and ability to detect low-energy beta emitters. However, as with any spectrometric technique used for beta assay, only limited spectral information is obtained as beta energy spectra are continuous from zero to the maximum energy value ( Mellado et al., 2005 ).

Three sets of experiments were performed, to study the influence of pH and ionic strength on Graphic Granite (GG), Granite Adamellite (GA) and Rapakivi Granite (RG). Results have been plotted as sorption isotherms at varying pH, following experimental protocol described in section 2. As the isotherms showed a similar pattern for the different granitic rocks considered, GG is presented.

Using Ni speciation results for the three systems studied ( Figures 1(A)-(C) ) above pH 8.5 precipitation of Ni occurred. However, immobilisation mechanisms can include precipitation of the metal on solid surfaces ( Jedináková-Křižová, 1998 ). Thus, precipitation occurring at high pH values in the present of solid is considered as immobilisation in this work. Deductions from experimental results for Ni sorption to GG thus, include:

1) pH had no significant effect in the NaCl free solution below pH 8.5 and above pH 8.5.

2) Sorption varied with pH and equilibrium state is attained after pH 8 for sorption in 0.05 mol·dm⁻³ NaCl.

3) Sorption in 0.1 mol dm^-3 NaCl showed the same sorption profile as that in 0.05 mol·dm⁻³ NaCl. This is evident from the JChess speciation diagrams ( Figure 1 and Figure 2 ). Speciation of Ni in the two NaCl systems studied did not vary, with Ni²⁺ as the main species.

Figure 1. A, B and C: Ni²⁺ aqueous speciation, showing the variation of Ni metal concentration with pH in different NaCl systems. The expanded Y-axis for the speciation above pH 8 is shown in the figure below, with the major species being, Ni(OH)₂ and Ni(OH)³⁻ ( van der Lee, 2003 ).

Granitic rocks are composed of silanol and aluminol sites with a PZC between 4 and 5 ( Sposito, 1984 ). Thus, the mineral surfaces will be negatively charged across the pH range studied. However, sorption showed pH dependency in 0.05 and 0.1 mol·dm⁻³ NaCl solutions. However, in the pH region 4 to 6, there was no steep rise in sorption with pH for GG, GA, or RG. The absence of a steep increase in sorption in the pH range 4 to 6 is often interpreted as being due to cation exchange on the permanently charged planar sites ( Bradbury & Baeyens, 2009 ).

Sorption in 0.05 and 0.1 mol·dm⁻³ NaCl systems was affected by the presence of Na⁺ ions competing for the sorption sites. This is obvious based on the fact sorption in the absence of Na⁺ ions; sorption was independent of pH within the entire pH range studied. Thus, despite the large charge to volume ratio of Ni, sorption is suppressed in the presence of Na⁺ ions below pH 7 for sorption in NaCl systems. However, above pH 8, no difference in the sorption profiles of the three systems is observed. Traditionally, ionic strength dependent sorption is used to distinguish between specific and non-specific sorption. Outer sphere complexes involve only weak electrostatic interactions and are strongly affected by the ionic strength of the aqueous phase, whilst inner sphere complexes involve much stronger covalent or ionic binding and are only weakly affected by the ionic strengths ( Scheidegger et al., 1996 ). From Figures 3-5 , the sorption process is affected by ionic strength. For solutions containing NaCl, sorption can be said to be inner-sphere at pH > 7. At pH > 7, there is a significant rise in sorption and sorption is not affected by pH. As seen in section 1.1, the mass action law can be applied to the surface complexation process with the stated assumptions. Thus, plotting Log Rd as a function of {pH + Log [≡SOH]} yields a linear relationship, the slope of which gives the proton stoichiometry of the reaction and the intercept defines the equilibrium constant, as shown in the figure below.

Plotting Log R_d as a function of {pH + Log [≡SOH]} assumes that the activity (concentration) of the sorption sites is 1 ( Hayes & Katz, 1996 ). From Figure 4 and Figure 5 the region of significant (steep) rise in sorption (the sorption edge) is defined between pH 7 to 8. From the gradient of the plot, the Proton Stoichiometry (PS) is determined ( Hayes & Katz, 1996 ). Thus, from Figure 4 , and Figure 5 , the proton stoichiometry is 1.9 and the sorption edge is between 7 and 8. When sorption is not affected by variation in pH, the model used above (the Kurbatov model) is not applicable, since there is no region of significant rise in sorption with pH, under the stated experimental conditions.

The relationship (Equation (1)) is applicable in the region of steep rise in adsorption with pH ( Kanungo, 1994 ). Values of “x” greater than unity suggest a mixed reaction type. Analysing the results based on the above model yielded proton stoichiometry values for Ni sorption to granitic rocks.

From the results shown in Table 2 some conclusions can be reached.

1) There is no region of steep rise in sorption, for NaCl free solution for all granitic rocks studied;

2) Sorption to Biotite Granite (BG) and Grey Granite did not vary with pH for all three systems studied since there is no region of steep rise in sorption with pH;

3) The concentration of Na⁺ ions affected the sorption of Ni²⁺ in 0.05 and 0.1 mol dm³ NaCl solutions below the sorption edge.

SE pH = sorption edge pH; PS = proton stoichiometry; K_e = the equilibrium constant for the reactions that lead to the protonation/deprotonation reaction as applied in the electric double layer model.

Understanding the sorption behaviour and properties of granitic rocks is complex. Sorption of metallic ions on to granitic surfaces will depend on the mineralogical composition of the granitic rock; rocks with high quartz content will be low sorbing, based on the low sorption capacity of quartz as seen by Ticknor ( Ticknor, 1994 ). The complexity of the sorption process to heterogeneous materials such as granite will depend amongst other parameters on the net surface charge, which in itself depends on the point of zero charge of the individual minerals of the bulk sample, and the structure of the granitic sample in general. This will affect the diffusion of particles (non-electrostatic sorption) into the microstructure, as such affecting the net retention property of the granitic rock. Due to the lack of literature data on work relating to the sorption of Ni to bulk samples such as granitic rocks across the pH range, it has not been possible to compare the results obtained. However, sorption data obtained for the rest of the experiments in this work has been treated following the same approach, but in some only the sorption parameters are shown.

Quartz, feldspar, and mica are the major constituent minerals of most granitic rocks ( Table 3 ). However, due to their structural and chemical differences, radionuclide retardation on the surfaces of these minerals might vary. As shown in previous work by Ebong and Nick ( Ebong & Nick, 2012 ; Ebong & Nick, 2011 ; Ebong & Nick, 2008 ) quartz is low sorbing compared to mica at constant pH. As the pH of the solution changes, the potential for OH groups on the mineral surfaces to be protonated or deprotonated changes. This process of protonation/deprotonation depends on the point of zero charge of the mineral. Quartz constitutes about 25 to 50% by weight composition depending on the granite type ( Allard et al., 1980 ; Muuronen et al., 1985 ). SiO₂ is the main constituent of quartz. Quartz has been reported to sorb radionuclides very weakly compared to other minerals such as feldspars and biotite ( Anderson et al., 2007 ). Biotite has one of the four silicon atoms substituted by an aluminium atom, creating a negative charge which is balanced by potassium cations which hold adjacent layers together ( Cresser et al., 1993 ). Feldspars are anhydrous three-dimensional aluminosilicates of linked SiO₄ and AlO₄ tetrahedra that contain cavities that can hold mono and divalent cations to maintain electrical neutrality ( Sparks, 2002 ). They can be divided into two main groups; alkali feldspars ranging from K aluminosilicates (Orthoclase Feldspars) and Na to Ca aluminosilicates (Plagioclase Feldspars).

In the surface complexation model, the surface sites are treated as amphoteric groups. Protonation or deprotonation reactions occur on the surface groups resulting in charged surfaces onto which metal ions bind. Consider the sorption of Ni to a mineral with surface ≡SOH, the following are possible:

$\equiv \text{SOH}\rightleftharpoons {\text{SO}}^{-}+{\text{H}}^{+}\to \text{deprotonation}$

$\equiv \text{SOH}+{\text{H}}^{+}\rightleftharpoons {\text{SOH}}_2^{+}\to \text{protonation}$

Surface complexation equation for the deprotonation reaction will be written as:

$\equiv \text{SOH}+{\text{Ni}}^{2+}\rightleftharpoons \equiv {\text{SONi}}^{+}+{\text{H}}^{+}$

The equilibrium constant for the reaction can thus, be written as

$K=\left[\equiv {\text{SONi}}^{+}\right]\left[{\text{H}}^{+}\right]/\left[\equiv \text{SOH}\right]\left[{\text{Ni}}^{2+}\right]$

The equilibrium constant defined above is thus, corrected for electrostatic interactions to obtain the intrinsic equilibrium constant as shown below ( Guo et al., 2010 ).

$K_S=\frac{\left[\equiv {\text{SONi}}^{+}\right]}{\left[\equiv \text{SON}\right]}-\frac{\left[{\text{H}}^{+}\right]}{\left[{\text{Ni}}^{2+}\right]}\frac{\left[{\gamma }_{\text{H}}^{+}\right]}{\left[{\gamma }_{\text{Ni}}^{2+}\right]}{e}^{\left(F\phi /RT\right)}$

where S is the surface, F is the Faraday constant (magnitude of electric charge per mol of electron C·mol⁻¹), ψ is the surface potential (V), R is the real gas constant (J·K⁻¹·mol⁻¹), and T is the temperature (K), γNi²⁺ and γH⁺ are the activity coefficients of Ni and H⁺ respectively. Most methods by which the intrinsic equilibrium constant for the surface complexation of metal ions to mineral surfaces is determined involves, the application of geochemical codes such as PHREEQC, MINTEQA2 and JChess ( Guo et al., 2010 , Bradbury & Baeyens, 2009 ; van der Lee, 2003 ). In this work JChess geochemical code by Ecole de Mines de Paris France ( van der Lee, 2003 ) provided by Loughborough University has been used. Results from sorption experiments are presented in the following sections. Experimental results are accompanied in some cases by surface complexation based predictive models.

Rose Quartz (RQ) as in Figure 6 , Figure 7 and Figure 7 was chosen as a representative sample of quartz. Ni sorption to RQ showed that below pH 8, sorption was low (mean R_d values below pH of 8 were < 5 cm³·g⁻¹, while above pH > 8 the mean R_d was 1.7 cm³·g⁻¹) and not affected by pH Na⁺ ions did not affect the sorption capacity below pH of 8. The observed low sorption capacity can be due to ions bind. A steep rise in sorption is observed above pH of 8. Sorption parameters are shown in Table 4 . Proton stoichiometry (proton stoichiometry is the number of protons released or adsorbed the surface sites to form ≡SO⁻ or ≡SOH²⁺) values close to 2 are calculated for MM and RQ, for sorption in 0.1 mol·dm⁻³ NaCl solution.

Titrimetric experiments were conducted to determine the proton exchange capacity for different minerals. measured equivalence points from titrimetric measurements with NaOH. The surface charge was calculated, using BET surface area measurements. Surface complexation input parameters, such as; proton exchange capacity, particle radius, temperature, equilibration time and pH were used in the surface complexation modelling. Using the data obtained from the JChess code, to plot sorption isotherms required corrections to be made to the output data. The output data are given in mol·dm⁻³ (fixed concentration). However, the data were converted to mol·g⁻¹ as used in plotting the sorption isotherms in the sections that follow. In using the surface complexation model, the denticity of the process is used. Denticity is defined here as the number of Ni ions that are bonded to the surface site. As such, mono and bidentate bonding refers to Ni atoms bonded to one of more surface sites. Figure 8 is the varying pH sorption isotherms for Ni sorption to Rose Quartz, showing data obtained from experiment and modelling, using JChess using Log K = −7 for mono and bidentate binding. Output parameters were collected and are stated in Table 5 .

Surface complexation modelling in NaCl free system, 0.05 mol·dm⁻³ NaCl system, and 0.1 mol·dm⁻³ NaCl system were carried out. Figure 9 shows predicted and experimental fits for the SCM in NaCl free system. Comparing the modelled and experimental isotherms ( Figure 8 ), both sets of data showed similarities within the limits of error as stated below:

Sorption did not vary with pH for both modelled and experimental data, below pH 8:

Despite the similarities in the experimental and theoretical model, two major differences are apparent:

1) The models differed in the maximum amount of Ni bound. From the isotherms, the maximum amounts of Ni bound at the region of steep rise in sorption are 1.3 × 10⁻⁶ and 2.2 × 10⁻⁶ mol·g⁻¹ for experimental and theoretical models respectively.

2) The JChess model showed that sorption decreases to zero at pH 11, whereas for the experimental data, sorption showed saturation.

The reason for the difference between the two models can be due to the purity of the mineral. Quartz (Rose Quartz) found in environmental samples can contain impurities such as titanium, iron and manganese, in the crystal structure (mindat.org 2012). These impurities can affect the overall sorption capacity of the mineral. Another reason can be due to sorption due to non-electrostatic forces (as in SC models); impurities in the crystal structure of the mineral can alter the SiO₄ tetrahedra structure, resulting in intraparticle diffusion. From the speciation of Ni, above pH 8 the main species present in solution are Ni(OH)₂ and $\text{Ni}{\left(\text{OH}\right)}_3^{-}$ ( Figure 1 and Figure 2 ). These species will not favour the sorption by electrostatic interaction because of the neutrality of [Ni(OH)₂] and negative charge of Ni(OH)₃⁻. The neutrality and charge of Ni(OH)₂ and $\text{Ni}{\left(\text{OH}\right)}_3^{-}$ do not affect intraparticle diffusion, which has not been accounted for in this work. Despite the electronic neutrality and negative charge on some of the Ni species, sorption can occur though other mechanisms such as ligand exchange with partially deprotonated silanol groups ( Schindler et al., 1976 ; Stumm, 1995 ). Another reason can be due to the non-attainment of equilibrium or steady state in the experimental.

Modelling the experimental data required the adjustment of input parameters, such as the mineral composition, the Log K values for the metal-solid complex formation taking into consideration the fact that two types of complexes may be formed (monodentate and bidentate) and the particle radius. Thus, the complexation constants are obtained from fitting the JChess data to the experimental model. For the simple case (NaCl free solution), the following input parameters were used; exchange capacity 5 × 10⁻² µmol·m⁻² calculated from titrimetric experiments with 0.1 g of Rose Quartz (particle size of 46 to 250 microns) and Log K values of −5 for both monodentate (Quartz-O-Ni⁺) and bidentate (Quartz-O)2Ni. Based on the calculation from JChess, the output console showed the concentration of Ni to be 1.8 × 10⁻¹¹ and 4.9 × 10⁻²² mol·dm⁻³ for monodentate and bidentate binding respectively. The implication is that at the determined Log K values for monodentate and bidentate formation, the sorption of Ni to quartz is overwhelmingly monodentate.

The effect of NaCl on the complexation of Ni to quartz is summarised (for NaCl free, 0.05 and 0.1 mol·dm⁻³ NaCl) in terms of the number of Ni bonded sites present in the system, as shown in Table 5 , using the same Log K value of −7 for mono and bidentate formations, as was used for Ni sorption to quartz in NaCl free system.

$\equiv \text{Quartz}-\text{OH}+{\text{Ni}}^{2+}\rightleftharpoons \equiv \text{Quartz}-{\text{ONi}}^{+}\text{LogK}=-7$

$\equiv \text{Quartz}-\text{OH}+{\text{Ni}}^{2+}\rightleftharpoons {\left(\equiv \text{Quartz}-\text{O}\right)}_2\text{Ni LogK}=-7$

From Table 5 the most probable sorption mechanism can be determined based on the concentration of the sites. From the table, a monodentate complexation with Ni is the most likely to form in solution. The table also shows the effect of Na⁺ on the available sorption sites. Comparing modelled data for the three systems, results show that the maximum amount bound was in the order: 9.4 × 10⁻⁶ mol·g⁻¹ (NaCl free) > 6.5 × 10⁻⁶ (0.05 mol·dm⁻³ NaCl) > 3.2 × 10⁻⁶ (0.1 mol·dm⁻³ NaCl), all values at the pH of maximum sorption. Thus, it can be concluded that the presence of NaCl in solution affected the sorption capacity of quartz.

Feldspars are anhydrous three-dimensional aluminosilicates of linked SiO₄ and AlO₄ tetrahedra that contain cavities that can hold mono and divalent cations to maintain electrical neutrality ( Sparks, 2002 ). They can be divided into two main groups; alkali feldspars ranging from K aluminosilicates (Orthoclase Feldspars) and Na to Ca aluminosilicates (Plagioclase Feldspars). Feldspar minerals are thermodynamically unstable in the near-surface environment and their surfaces are well known to react readily with aqueous solutions, leading to incongruent dissolution at low pH values, but congruent dissolution at neutral and high pH values ( Chardon et al., 2008 ). Orthoclase Feldspar (OF) is chosen as a representative sample of feldspar. Orthoclase is a common constituent of most granitic rocks. Typically, the pure potassium end-member of orthoclase forms a solid solution with albite, (plagioclase feldspar mineral).

Results obtained from varying pH experiments in three different NaCl environments are shown in the isotherms Figure 8 . From the results regions of significant rise in sorption are observed for the three systems, from which proton stoichiometry are defined as shown in Table 4 . Between pH of 3.5 and 7.5, sorption showed a gentle increase, governed by cation exchange process. However, sorption showed a significant increase between pH 7.5 to 9.5 as shown in Figure 10 . The effect of NaCl is not clearly seen. The fact that Ni sorption to feldspar showed similar pattern in the three systems studied ( Figure 10 ) is supported by modelled data presented in Table 6 . Sorption parameters are shown in Table 4 .

Granitic rocks mineral particles can be represented as a semi-infinite homogeneous porous solid which bears a permanent negative charge uniformly distributed, resulting from isomorphic substitution in the structure ( Kraepiel, 1999 ). Thus, granitic minerals such as feldspars may sorb radionuclides in a large pH range, as seen in Figure 10 . Sorption spans a large pH range with no clearly defined region of steep rise in sorption, indicating that sorption can be dominated by cation exchange mechanism and surface complexation, involving both weak and strong sites (The “strong sites,” have a high affinity for metals, and are responsible for adsorption at low metal concentrations, and the “weak sites,” play a role only at high pH or high metal concentrations, when the strong sites are saturated ( Kraepiel, 1999 ). The proton stoichiometry was calculated in the range 0.5 to 1 highlighting low deprotonation involved in the system. The proton stoichiometry relates to the number of protons released in the solid-metal complexation process. Highly deprotonating systems will have proton stoichiometry > 1, as such the metal-solid complex formation will be controlled by the pH of the system. Thus, from the results obtained for Ni sorption to feldspar, it can be concluded that no single mechanism (CEC and SCM) is solely applicable to the sorption results obtained.

Surface complexation modelling was performed with feldspar in the presence of 0.1 mol·dm⁻³ Na⁺ ions. The proton exchange capacity for OF was calculated as 3.1 × 10⁻² µmol·m⁻² from titration 0.1 g of feldspar with 2 M NaOH and particle radius of 2.7 nm. Running the program with stated output parameters, the concentration of fixed Ni was calculated at different pH values. Setting Log K values at −1 and −1.5 for monodentate and bidentate respectively, the data obtained were compared with the experimental data as shown in Figure 11 . The JChess isotherm was the best fit for the stated condition.

$\equiv \text{Feldspar}-\text{OH}+{\text{Ni}}^{2+}\rightleftharpoons \equiv \text{Feldspar}-{\text{ONi}}^{+}\text{LogK}=-1.0$

$\equiv \text{Feldspar}-\text{OH}+{\text{Ni}}^{2+}\rightleftharpoons {(\equiv \text{Feldspar}-\text{O})}_2\text{Ni LogK}=-1.5$

Figure 11 shows the sorption profile for Ni²⁺ in 0.05 mol·dm⁻³ NaCl. The results from the JChess model and the experimental data did not show any major differences. The conclusion is that there was a region of steep rise in sorption, and sorption increased gently with pH.

From Figure 11 , it can be concluded that the modelled data fitted the experimental data and sorption could be described thermodynamically using the assigned Log K values of −1 and −1.5 for mono and bidentate binding respectively, for Ni sorption in 0.05 mol·dm⁻³ NaCl systems.

JChess was used to model the effect of NaCl in the system, by running the program for NaCl free, 0.05 mol·dm⁻³ NaCl systems and 0.1 mol·dm⁻³ NaCl systems. Experimental results obtained for Ni²⁺ sorption to feldspar in the three systems ( Figure 8 ) showed that the sorption profiles for the three systems did not vary, despite the presence of different amounts of NaCl in solution. Thus, this section aims to model sorption in the three systems and to observe the effect of NaCl using the concentration of sorption sites (Ni-Solid and Na-Solid) for the three systems. The concentration of sorption sites present is directly related to the sorption capacity.

Comparing the three systems (NaCl free, 0.05 and 0.1 mol·dm⁻³ NaCl) based on output report from JChess; results showed that Na⁺ did not affect the sorption in all three systems. No complexation of Na⁺ with the surface was observed at the stated conditions. The results agree with observation from the experimental data ( Figure 10 , no major difference is observed in the sorption profile for all three systems).

From Table 6 above the following conclusions can be drawn;

1) NaCl did not affect the sorption of Ni, in all three systems. This has been shown experimentally (see Figure 8 ) and by surface complexation modelling.

2) The most probable complexation mode is by Si-O-Ni complex (i.e. monodentate binding.

Varying pH sorption experiments for Mica as in Figure 12 were performed in similar manner as those of quartz and feldspar. Analysing the data within the pH range studied showed that the sorption capacity did not vary. The sorption capacity (2 × 10⁻³ mol·g⁻¹) did not vary from low to high pH. Layered silicates contain two types of surface adsorption sites: those with a permanent charge, formed because of isomorphic substitution in the crystal structure, and with a pH-dependent charge appearing because of protonation or deprotonation of hydroxyl groups on the basal or edge surfaces of the tetrahedral or octahedral layers. Ion exchange reactions usually take place on the basal surface, where sites with an unbalanced structural charge are located. For mica, this charge is negative, and the sorption of cations on these sites only slightly depends on the pH value of the solution ( Maslova et al., 2004 ). One other reason for the constancy in the sorption capacity from low to high pH can be due to the position on the point of zero charge (pH at which the net surface charge is zero) on the pH scale. With PZC for silicate minerals reported to be close to 2, and 4 to 6 for alumina minerals ( Mahĕ et al., 2008 ), it is expected that PZC for mica will be <4. At PZC < 4 the surfaces will be negatively charged when present in a pH environment > 4, resulting in constancy in the sorption capacity.

In varying pH systems, adsorption sites are concentrated at edges ending with aluminol or silanol groups, which can accept or donate a hydrogen ion causing the appearance of an unbalanced surface charge. In contrast to ion exchange, surface complexation is determined by the pH value of the medium ( Maslova et al., 2004 ). Maslova et al. (2004) studying the surface properties of cleaved mica, showed that only 5 to 10% of the total charge at pH 7 is due to pH-dependent adsorption sites. Hence, the ion exchange can take place at higher pH values. Thus, the following conclusions can be made:

1) Ni sorption is not affected by pH.

2) Ni sorption is not affected by the presence of NaCl.

3) Sorption is not affected by competition with Na ions.

4) Cation exchange represents the major sorption mechanism.

The high sorption capacity at low pH can be attributed to the mica structure; cations found in the interlayer hold the sheets together. In solutions, there is dissolution of the cations holding the layers together, resulting in excess permanent changes on the mica surfaces ( Hans-Jurgen et al., 2004 ). This excess permanent negative charge is responsible for the high sorption capacity at low pH.

Results from surface complexation modelling-Mica

The presence of permanent negative charge on the mica surface will cause surface complexation with metal ions. JChess geochemical code was used to model the sorption of Ni to Muscovite Mica (composition provided by JChess data base) as a representative sample of mica. The proton exchange capacity for Muscovite Mica (MM) was calculated as 70.4 µmol·m⁻² from titration of 0.1 g of MM with 1 M NaOH and particle radius of 2.8 nm. Running the program with stated output parameters, the concentration of fixed Ni was calculated at different pH values. Setting Log K value at Log K = 5 for mono and bidentate. The data obtained were compared with the experimental data as shown in Figure 12 .

$\equiv \text{Muscovite}-\text{OH}+{\text{Ni}}^{2+}\rightleftharpoons \equiv \text{Muscovite}-{\text{ONi}}^{+}\text{LogK}=5$

$\equiv \text{Muscovite}-\text{OH}+{\text{Ni}}^{2+}\rightleftharpoons {(\equiv \text{Muscovite}-\text{O})}_2\text{Ni LogK}=5$

Results showed no major difference between the experimental and the model. The following conclusions can be made:

1) Sorption takes place from low to high pH, for both predicted and experimental models.

2) The same sorption capacity is attained for both modelled and experimental data.

Running the JChess program in the presence of different concentrations of NaCl produced the data shown in Table 7 .

The results shown in Table 7 indicated that NaCl did not influence the sorption based on the total number of sorption sites. These results confirm experimental findings that showed NaCl had no effect on the sorption of Ni to mica.