Dynamical properties of water and ions at the Quartz (101)âwater

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Dynamical properties of water and ions at the Quartz (101)–water interface at a range of solution conditions: A classical molecular dynamics study Mohammed Bouhadja, and Adam A Skelton J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.7b08214 • Publication Date (Web): 20 Dec 2017 Downloaded from http://pubs.acs.org on December 21, 2017

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The Journal of Physical Chemistry

Dynamical properties of water and ions at the Quartz (101)–water interface at a range of solution conditions: A classical molecular dynamics study M. Bouhadja1.2, A. A. Skelton1* 1

School of Health Sciences, University of KwaZulu-Natal, Durban 4001, South Africa.

2

Department of Physics, University of Picardy Jules Verne, Amiens 80000, France.

*

Corresponding author: [email protected] (A. A. Skelton)

Abstract: The solution conditions such as the ion concentration and pH have a profound effect on the behaviour of the silica/water interface, which dictates many of the surface properties of mesoporous silica nanoparticles (MSNs) and their utility in a range of nanotechnology applications. The interaction of water molecules with a model silica surface, α-quartz (101), at different surface charge densities, is investigated to evaluate the influence of pH on structure (density profile, radial distribution function) and dynamics (diffusion coefficient D) of the interfacial water in the presence of biologically relevant ions, Na+, K+ and Rb+ ions. Classical molecular dynamics were performed using a recently developed force field (Kroutil et al, J. Phys. Chem C, 2015, 119, 9274-9286). Our results show the interfacial water is more structured and the diffusion of interfacial water molecules becomes slower as the surface charge becomes more negatively charged, as we increase the pH from acidic to neutral to basic pH. The self-coefficient diffusion (D) of water molecules and ions decrease with an increase in pH and is affected by concentration and type of ions in the system. The diffusion of water molecules around deprotonated oxygen atoms is slower than the diffusion of water molecules around oxygen protonated. The presence of the ions near to deprotonated oxygen atoms further decreases the diffusion of water molecules.

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Introduction The behaviour of the silica/water interface dictates many of the surface properties of mesoporous silica nanoparticles (MSNs), which is essential for their utility in a range of nanotechnology applications such as drug delivery [1], water treatment [2] and catalysis[3]. In particular, the interfacial water structure and dynamics will control colloidal suspensions by dictating how the MSNs agglomerate or disperse [4] and will directly control the adsorption process of molecules onto their internal pore surfaces [5]. The acid-base chemistry of silica surfaces can be manipulated for pH responsive drug release; one such example is the oral delivery of sulfasalazine in organic functionalized MSNs for oral delivery [6]. The drugs bind to the internal pore surfaces at the acidic pH, of the stomach, where the silanol groups are neutral. At neutral or basic pH, in the small intestine, however, the drug is able to be released due to repulsion between the negatively charged drug and the negatively charged, deprotonated silanols and this allows the drug to bypass the stomach. Similar drug delivery systems can also be used to selectively release drugs in response to changing pH conditions within tumors [6]. The dynamics behavior of interfacial water molecules under these different, pH and ion concentration, conditions should govern the binding and release of the drug molecule. Apart from controlling the drug release, the dynamics of the interfacial water should be critical for the effectiveness of the administered MSN within the body, controlling the in vivo biodistribution and bioavailability [17], which depend on the colloidal properties. Moreover, the interaction the MSNs with biomolecules, such as plasma proteins and lipid molecules within cell membranes, involves mediation by the structured water molecules and ions [8-12]. Similar functionalized MSNs are also being used for water treatment because of their strong affinity to organic pollutant molecules such as dyes, pesticides and pharmaceuticals [13]


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where MSNs should have pH responsive behavior since a decrease in binding at high pH can be used to release the pollutants and enable the FMSNs to be reused. FMSNs have been explored as supports for organic catalysts for chemical reactions [3] where the organic catalyst is the functional group. It is considered that cooperative effects between the reactant and acidic silanol groups are involved in the catalysis process and it is envisaged that factors such as pH and ion concentration that affect dynamics of interfacial water molecules will be crucial in these cooperative effects. The α-quartz (101) surface is the most stable surface cleavage as it contains the lowest surface energy of all the other cleavages of α-Quartz [14], and is commonly used as a model system to study the interaction of silica with water. Quartz contains Si and O atoms where each Si atom is connected to four O atoms forming tetrahedral SiO4 silica units that are connected by bridging Oxygen atoms (BO). On the surface each Si atom is connected with three BOs and one OH group (Q3 groups), known as silanol groups (Si-O-H); there are two types of silanols, outer-silanol (T1) and inner-silanol (T2) [15-18]. The interfacial properties are strongly dependent on hydrogen-bonds between the surface silanol groups and water molecules. At neutral pH, silanols of the α-Quartz surface are deprotonated by the removal of H atoms thereby forming a negative surface charge [15]. A change in the pH will affect the surface charge in a predictable manner [19] and it has been shown that the nature of the interfacial solution such as the electrolyte type and concentration will affect the pH/surface charge relation [20-23]. The behaviour of the silica/water interface should also influence the dissolution of silica, which is the cause of geochemical weathering/erosion of rocks and minerals in Earth’s surface [24]. Quartz dissolution can, therefore, be significant in industrial contexts such as silica dissolution around nuclear waste storage [25]. Many previous experimental studies have reported how the dissolution rates of quartz can be affected by solution conditions [20, 25-



33]; that is, the dissolution rate is dependent on the cation species in solution, [13, 34] and depends heavily upon pH of the solution [36]. It has been reported that the dissolution rate of quartz increases with increasing the concentration of cation solution [27, 35]. The effect of radius of cations on dissolution rates, was investigated by P. Dove et al [27, 28]; the results showed that the dissolution of silica in solutions containing K+ is larger than those containing Na+. Brady et al. [31] showed that, at a temperature of 298 K, the quartz dissolution increases as pH increases between 7 and 12 and is constant in acidic conditions. It is considered that the solution conditions affect the interfacial water structure, which in-turn affects quartz/silica dissolution [36] since dissolution rate (k) follows an Arrhenius type equation as k= A(exp(∆Ea/RT)). The log A term is the pre-exponential factor or so-called collision frequency that should be dependent on the diffusion of water molecules in the vicinity of the surface [36, 37]. The theoretical treatment the electrical double layer (EDL) has been an intense area of research where models, such as the Gouy−Chapman−Stern model [38], have been developed to account for variations in surface charge [39] and electrolyte concentration [40] on the behaviour and structure of the EDL. Furthermore, previous studies have used classical molecular dynamics (CMD) to investigate the molecular origins of the EDL [41], especially for silica-water and quartz–water interfaces [42-52]. Our previous studies involved the 1) [10] and (1010) [53]. Three force interaction of water with two surfaces of quartz, (101 fields, LFF [54], ClayFF [55] and CWCA [56,57] were used and the force fields were compared to AIMD and X-ray reflectivity experiments; ClayFF give the best agreement to AIMD for the water–silanol radial distribution functions. Previously; we modified the original 1)–water interface for different surface force field, ClayFF [15] to study the α-quartz (101 charges, neutral, -0.03 C/m2, -0.06 C/m2 and -0.12 C/m2. The effect of pH on the structure on the structure of the water at the interface was evaluated in the presence of alkali metal ions,


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Na+, Sr2+ and Rb+ ions. It was found that the structural properties of water molecules at the interface were affected by the surface charge density and the absorption of the different ions; that is, the axial density of water hydrogen atoms (Hw) at the interface increased with an increase in the surface charge density. The lateral density of the first layer in the interface of Hw and water oxygen atoms (Ow) is greater around deprotonated oxygen atoms (Si-O-, Od) than protonated silanol groups; the same trend of density was obtained for different ions. The interaction between the water and ions with the surface of α-Quartz (101) and the effect the dynamics properties, such as the diffusion of water molecules and ions, remain poorly understood experimentally and computationally. The aim of this work is to use CMD to study the diffusion of water molecules and ions as a function of surface charge density, different types ions Na+, K+ and Rb+ and ionic strength. For this purpose, we will perform CMD simulations using our recent modified ClayFF force fields to study the α-quartz (101)-water interface for different surface charges, neutral, -0.03 C/m2, -0.06 C/m2 and -0.12 C/m2 and the force field parameters of Na+, K+ and Rb+ were taken from Joung et al. [58]. We will extend our previous work [8] by investigating how the diffusion of water molecules differs as we move away from the surface under different solution conditions. We investigate the effect of hydrogen bonding between water and protonated/deporotonated silanol groups by reporting the diffusion of water molecules that are within the first solvation shell of protonated and deporotonated silanols oxygen atoms. Since ions should be attracted to the surface, we also investigate how these ions affect water diffusion. Lastly, we will investigate the potential implications of the interfacial water dynamics on the action of silica nanoparticles as nanodrug delivery systems, water treatment agents and catalyst supports and experimentally determined quartz/silica dissolution rates and acid-base properties.



Setup and Methodology Bulk quartz was cleaved to create the (101) surface using the surface builder module of Materials Studio 2016 (MS) (BIOVIA Inc, San Diego, CA) with a 4x4x1 supercell from unit cell a = 55.00 Å, b = 39.82 Å and c = 18.00 Å. The vacuum slab between surfaces (101) was filled by 5340 water molecules H2O and ions (Na+, K+, Rb+ and Cl-) using the build layers module of MS. The water molecules were previously created by “Amorphous Cell” Module implemented in MS using universal force field for 10 ps and temperature 298 K with density 1 g/cm3, orthorhombic cell simulation was used with initial a = 55 Å, b = 39.82 Å and c = 90.21 Å. We transferred this simulation cell to VMD software and the ions, Na+, K+, Rb+ and Clwere dissolved by “Add Ions” module implemented in VMD [59]. The concentrations of NaCl, KCl and RbCl solution are 0.4 M. An additional quantity of cations, Na+, K+ or Rb+ was added to balance the number of deprotonated oxygen, Od, and, therefore, maintain overall charge neutrality in the cell. The number of atoms of each unit cell and species is given in Table S1 of Supplementary Information. Both sides of the surface contained 128 silanol groups, and 0, 4, 8 and 16 of these groups (per side) were deprotonated to obtain surface charge densities of 0.00, -0.03, -0.06 and -0.12 C.m-2 corresponding to pH=7, 7.5, 9.5 and 11 respectively (Figure 1). In the second part of our simulation, we made systems with no chloride ions, only adding enough cations to compensate the negative charge from the deprotonated outer silanols. We hereby name these simulations zero Cl- concentration simulations. All CMD simulations were carried out using LAMMPS code [60] to investigate the dynamical properties of water molecules and ions as a function of surface charge density. The SPC/E water model was used to describe interatomic interaction [61]. A modified ClayFF force field was developed recently by our group [15] to account for different surface charge densities 0, -0.03, -0.06 and -0.12 C.m-2 and force field parameters for the cations were taken


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from Joung et al. [58]. ClayFF force field describes columbic interaction and Lennard-Jones terms. There are only two bonds included by this force field, Oh-Hh bond and Sih-Oh-Hh. 1 = − 1 2 1 = − 2 2 The molecular dynamics simulation was performed with Verlet’s algorithm using 1 fs time step in the canonical ensemble (NVT) and isobaric isothermal ensemble (NPT). In all CMD simulations, the particle-particle-particle mesh method (PPPM) was used to treat the long-range electrostatics. In the beginning, CMD was performed for 500 ps with NPT ensemble with pressure controlled by semi-isotropic pressure only in the z-direction at 1 atm pressure and a temperature of 298 K to produce a water density of 1 g/cm3. Since the final cell parameters of the NPT simulation were a = 55 Å, b = 39.82 Å and c = 90.82 Å, the cell parameters were fixed at those values and the simulation was performed for a further 250 ps in the canonical ensemble (NVT). To calculate the diffusion, 17.5 ns NVT simulations were performed. The self-diffusion coefficient (D) was calculated from Mean Square Displacement (MSD) where Equation 3 shows the evolution of the positions ri(t) of the atom i with time t using molecular dynamics simulation. The slope of MSD gives the self-diffusion coefficient using Einstein’s relation Equation 4.

〈

1 〉 = 〈 − = 0〉 3 !

〈 〉 # = lim 4 '→∞ 6



D was calculated for water hydrogen atoms (Hw), water oxygen atoms (Ow) and ions perpendicular to the surface in particular regions, R1, R2, R3, R4, R5 and R6; for example, the first region (R1) is between the first minimum and second minimum of the profile density. For more details about regions R1, R2, R3, R4, R5 and R6 see Figure 1c. The linear behavior of MSD versus time can be affected by poor sampling [62]; this problem was minimized by looping the diffusion coefficient calculation 70 times, with each iteration calculated over 250 ps windows to produce the diffusion of hydrogen water (Hw), oxygen water (Ow) and ions perpendicular to the surface. For each 250 ps window, the atoms within the regions were updated and the final D value was the average of each iteration. We calculated D between 150 ps and 250 ps because it was found that the diffusion of water molecules in nanoconfined systems or ionic solutes will be overestimated, due to “rattling: and “hindered diffusion modes” if calculated over shorter times [63-65]. Due to the necessity of using relatively large windows, there is an opportunity of water molecules that were originally in the particular regions to leave the region during the calculation of D. We monitored the number of water molecules that leave region R1 and R2 (Figures S3 and S4, respectively) during the simulation and found that 6% and 10% of water molecules leave R1 for -0.12 C/m2 and the neutral surface, respectively. 6% and 12% of water molecules leave R2 for -0.12 C/m2 and the neutral surface, respectively. Since the other regions are large, the percentage of water molecules that left the regions was negligible. We consider that the effect of the water leaving R1 and R2 did not significantly change the result especially considering the positive payoff of choosing large time windows for analysis.

Results and Discussion Distribution of ions


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To provide an initial assessment of the composition of the different NaCl solutions and how the surfaces affect the solutions, we have calculated the number of Na+ and Cl- ions in different equidistant regions as a function of density surface charge (Table I). When we move from the surface, we observe with increasing charge densities that the number of Na+ increases and Cl- decreases at the interface (53.75 Å< z < 58.25 Å). In the bulk (62.75 Å < z DHw,Ow(Na+). The behavior can be correlated with the ionic radii of the ions in solution from ref [63] R(Rb+) = 1.49 Å > R(K+) = 1.38 Å > R(Na+) = 1.02 Å; that is the smaller the ionic radius the more water molecules are slowed down. Another notable observation is that the diffusions of water molecules in the system containing Na+ with the neutral surface are more similar to systems containing K+ and Rb+ (lines are closer together) than for systems containing the surface charge -0.12 C/m2 (lines are farther apart). The aforementioned trend can be observed for both Ow (Figures 3a vs 3c) and Hw (Figures 3b vs 3d) diffusions and show that the effect of ions types on the diffusion of water molecules has a greater effect for the surface with a charge density of -0.12 C/m2 than the neutral surface. The reason for this is that the -0.12 C/m2 surface attracts a greater number of interfacial ions than the neutral surface; the greater number of ions have a more pronounced effect on the water diffusion.



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To explain the effect of the ionic radii, the radial distribution function (RDF) was considered for ions (Na+, K+ and Rb+) with Ow and Hw (Figure 2a and b). It should be noted that the greater the height and the shorter the distance of the first peak the stronger the ion–water interaction. The interatomic distances (distances of the first peak of the RDFs), Na+–Ow (2.33 Å) and Na+–Hw (2.33 Å) are greater than K+–Ow (2.58 Å) and K+–Hw (3.20 Å), which are greater than Rb+–Ow (2.89 Å) and Rb+–Hw (3.45 Å); the height of the first peak for K+, Rb+ are lower than Na+. Overall, the aforementioned results indicate that the interaction of the ions with water become weaker with an increasing size of the ion. The reason for the aforementioned trend is that the Lennard Jones sigma value follows the order: Na+ (2.159 Å), K+ (2.8395A,) and Rb+ (3.094A,). A smaller Lennard-Jones value enables the ions to get closer to the water molecules, which means that the electrostatic interaction, which is given by

-. -/ 0./

,

is stronger. The larger electrostatic interaction results in a decrease in the diffusion of water molecules with increasing ionic radii. Details of the diffusion of interfacial water molecules To provide more detail on the effect of the specific interactions on the diffusion of water molecules in the first layer, the diffusion of Hw atoms, in particular regions of the interface, are reported Figure 5. The regions chosen are spheres centred at the Oh and Od atoms with the radii of the spheres as the first minimum of the Oh–Hw and Od–Hw RDFs (Supplementary Information, Figure S2). Figure 5a shows a map of these diffusions of the first layer water molecules above the neutral surface. It can be noticed that the diffusion of Hw around the outer silanol groups is homogeneous since all the silanol groups are protonated and these are shown as high diffusion yellow and green regions. With increasing surface density (Figure 5b to 6d), the diffusion of water molecules became slower around deprotonated silanols and this is shown by the blue region around the Od atoms. Previous work by Kroutil et al. [15] showed


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that the lateral density of Hw and Ow around Od is high and this strong interaction further explains the slower diffusion of water molecules around Od. It should be considered that the water dynamics of molecules around Oh atoms should depend on their proximity to Od atoms; this effect is shown in Table III where we consider the diffusion of water molecules around three types of outer silanol groups; these are, Od atoms themselves (red), Oh atoms that are nearest neighbors of Od, called On (blue), and Oh atoms that have no adjacent Od atoms, called Of, atoms (black), see Figure 5. The results displayed in Table III show that the diffusion of Hw atoms is the slowest around Od (blue region in Figure 5) followed by On (green region in Figure 5) with the greatest for Of (yellow region in Figure 5). We should now compare the numbers in Table III with data in Figure 2. For example, for the -0.06 C/m2 surface charge with Na+, the diffusion around Od is 0.238 A,2/ps, considerably lower than the value for the whole first layer ~ 0.25 A,2/ps; this is because this value is the average over the diffusion of water molecules around Od (0.238 Å2/ps), On (0.252 Å2/ps) and Of (0.261 Å2/ps) atoms that make up the surface. It is notable that the diffusion of water molecules around Od is smaller for solutions containing Na+ than K+, which is smaller than Rb+. This shows the large role of the ions that are adsorbed onto the Od in slowing down the water molecules; it could be argued that this role is more significant. For example, for -0.06 C/m2 surface charge, the difference between diffusions around Od for systems containing Na+ and Rb+ is 0.021 Å2/ps (0.238 Å2/ps – 0.259 Å2/ps) and is comparable to the difference between Od and Of of 0.023 Å2/ps (0.238 Å2/ps – 0.261 Å2/ps); however, for Od, there should still be a significant slowdown even in the presence of K+ and Rb+. To provide more detail on the diffusion at the interface and, in particular, the role of the adsorbed ions on the slowdown of the diffusion we report the percentage of simulation time that Na+ ions spent binding with separate Od atoms (% time), as a function of the diffusion of Hw atoms around the Od, inset of Figure 6, left, shows the Na+ ions binding with Od during



simulation. We define that Na+ is binding with Od atoms if the interatomic distance is less than 3.74 Å is the first minimum of RDF Na-Hw. The % time vs diffusion plot will, therefore, provide the exact effect of adsorbed Na+ on the diffusion. We have looped our simulation 70 times; the duration of each loop is 250 ps and we took the mean of the % time value of each loop. We calculated the % time of 10 Od atoms of surface charge -0.12 C/m2. We see clearly that when Na+ adsorbs to the Od the diffusion of Hw decreases; there is an inverse correlation between % time and Hw diffusion. We confirm now the presence of Na+ ions close to Od is a huge factor to the slowing down of the diffusion of water molecules. Indeed, there is a water diffusion decrease of 0.012 Å2/ps (0.238 Å2/ps – 0.226 Å2/ps) from 0% to 25% time and this difference is approximately half of the corresponding diffusion difference of water molecules around Od and Of atoms. Diffusion coefficient of the ions To provide further detail about the dynamics of the systems, the diffusion profiles of Na+, K+ and Rb+ ions are shown in Figure 7a, b, c. The diffusion trends obtained for ions are similar but of values are lower than those to that of water molecules; that is, the diffusion coefficient of ions close to interface is slowest and this value increases away from the interface. The diffusion coefficient of ions decrease with an increasing charge density and this has an inverse relationship with the axial density profile of ions, which shows an increase in the number of ions located at the interface with increasing surface charge density. The interaction of the ions with Od have an important effect that decrease the diffusion coefficient of ions in the interface. The axial diffusion of ions in the bulk water show the same behavior as the diffusion of water molecules at the interface; that is, there is a decrease in the diffusion coefficient with an increase in the surface charge because the number of ions increase to compensate the number of deprotonated silanols (Od). Figure 7d shows the comparison between the axial density and diffusion for the three ions in systems containing the surface ACS Paragon Plus Environment

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with charge density of -0.12 C/m2; we chose to present this surface charge because the number of ions is greater than the other surface charges and, therefore, the statistical sampling is better. The first observation is that there is a huge difference in diffusion coefficient between Na+ with both K+ and Rb+. Rb+ is only slightly slower than K+ and overall the ions follow the trend of diffusion of water molecules D(Na+) < D(K+) < D(Rb+); this trend is proportional to the Lennard Jones value of sigma as the diffusion coefficient decreases with decreasing value of sigma and the ions became more attractive Na+ (σ = 2.1595 Å) < K+ (σ = 2.8395 Å) < Rb+ (σ = 3.0949 Å). The effect of the concentration of NaCl, KCl and RbCl solutions on the diffusion coefficient of ions is displayed in Figure 7a, b and c, respectively. We calculated the diffusion of ions in systems with zero Cl- concentration only for systems containing a surface charge of -0.12 C/m2 because the number of ions of this surface charge is greater than systems containing other surface charges. We omitted the diffusion of ions in the bulk water because the number of cations in the bulk is almost 0 (Table II). The diffusion coefficient of ions significantly decreases with decreasing solution concentration for systems containing Na+, K+ and Rb+. The likely reason for the decrease is that there are less cations and therefore, less competition for absorption sites; that is, the surface charge isn’t compensated by Na+ ions (Table II), which means that there is a stronger electrostatic interaction between the positive cation and negative surface. In the presence of counterions, however, charge compensation results in an effectively neutral surface, which is less attractive to the ions. Comparison with previous experimental and computational data To gain an understanding of the validity of our data, the diffusion coefficient values are compared with experimental and computational MD values from the literature (Table IV). For the aforementioned comparison, the diffusion coefficient of water molecules and Na+, K+ and Rb+ ions, in the bulk water region (Z = 88.5 Å) of the simulation, containing the neutral ACS Paragon Plus Environment


surface with 0.4 M concentration of NaCl, KCl and RbCl, are used. The calculated diffusion coefficient of the ions show good agreement with experiment and MD simulation results; in particular, the trend in diffusion, Na+< K+ DHw,Ow(K+) > DHw,Ow(Na+). The diffusion of Hw around outer silanols showed that the mobility of water molecules is slowed down around deprotonated silanol groups and the diffusion decreases with increasing surface charge density. The diffusion of water molecules that surround different types of protonated oxygen atoms that depended on their proximity to Od atoms showed that the diffusion of Hw atoms that are adjacent to On are slower than the diffusion of Of atoms that are farther. The presence of ions near to Od further decrease the diffusion of water molecules around Od and there is a quantitative correlation between the diffusion of water around Od and the percentage of time that the ion spends adsorbed to the Od in question. The axial diffusion of ions showed similar behavior as the axial diffusion of molecule water; that is, the diffusion of ions decreasess with the increase of surface charge, the diffusion of ions in the interface is slower than those at the bulk and the diffusion of ions decrease with decreasing concentration of the solution. This article has provided detailed information about the fundamental nature of the quartz/water interface in contact with solutions of NaCl, KCl and RbCl at different pH conditions and different ionic concentrations. This study should help researchers who are interested in improving the theoretical treatment of the electrical double layer, especially those who are developing models to consider the effects of different solution conditions such as pH, ion concentration and ion species. Furthermore, the present study should assist experimental researchers, who are developing nanomaterials, especially mesoporous silica nanoparticles, which rely on the pH and electrolyte concentration responsive adsorption behavior such as



drug-delivery, water treatment and catalysis applications. The dynamics properties of water molecules and solutions should be a key determinant of the adsorption properties and the results of the present study can help those researchers to fine tune the surface modifications and solution conditions used to enhance their utility in the aforementioned applications.

Acknowledgements The HPC resources and services used in this work were provided by Center for High Performance Computing (CHPC) in Cape Town, South Africa. We would like to thank College of Health Sciences at UKZN for providing funding for postdoctoral position of Dr Mohammed Bouhadja.

Supplementary Information Available Supplementary Information contains Number and charges of the atoms/ions used in this paper, Table S1. Also included are the axial density and the diffusion of Hw and Ow for ions K+ and Rb+, Figure S1.

References [2] Slowing, I.I., et al., Mesoporous Silica Nanoparticles for Drug Delivery and Biosensing Applications. Advanced Functional Materials, 2007. 17(8): p. 1225-1236. [3] Salahshoor, Z. and A. Shahbazi, Review of the Use of Mesoporous Silicas for Removing Dye From Textile Wastewater. European Journal of Environmental Sciences, 2014. 4(2): p. 116-130. [4] Margelefsky, E. L., Zeidan, R. K. & Davis, M. E. Cooperative catalysis by silicasupported organic functional groups. Chemical Society Reviews 37, 1118–1126 (2008).


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Tables Surface charge (C/m2) Regions 53.75< Z(Å)

Dynamical properties of water and ions at the Quartz (101)âwater

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Dynamical properties of water and ions at the Quartz (101)âwater