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Selective Removal of Technetium from Water using Graphene Oxide Membranes Christopher David Williams, and Paola Carbone Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b06032 • Publication Date (Web): 08 Mar 2016 Downloaded from http://pubs.acs.org on March 9, 2016

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Environmental Science & Technology

Selective Removal of Technetium from Water using Graphene Oxide Membranes

*Christopher D. Williams and Paola Carbone

School of Chemical Engineering and Analytical Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, U.K.

*Corresponding author: Christopher D. Williams School of Chemical Engineering and Analytical Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, U.K. (+44)7735302862 [email protected]

Keywords: Graphene, membranes, polyanions, technetium, molecular dynamics

1 Environment ACS Paragon Plus



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1

ABSTRACT

2

The effective removal of radioactive technetium (99Tc) from contaminated water is of

3

enormous importance from an environmental and public health perspective, yet many

4

current methodologies are highly ineffective. In this work, however, we demonstrate

5

that graphene oxide membranes may remove

6

pertechnetate (TcO4−), from water with a high degree of selectivity, suggesting they

7

provide a cost-effective and efficient means of achieving

8

results were obtained by quantifying and comparing the free energy changes

9

associated with the entry of the ions into the membrane capillaries (∆Fperm), using

10

molecular dynamics simulations. Initially, three capillary widths were investigated

11

(0.35, 0.68 and 1.02 nm). In each case, the entry of TcO4− from aqueous solution into

12

the capillary is associated with a decrease in free energy, unlike the other anions

13

(SO42−, I− and Cl−) investigated. For example, in the model with a capillary width of

14

0.68 nm, ∆Fperm(TcO4−) = −6.3 kJ mol−1, compared to ∆Fperm(SO42−) = +22.4 kJ

15

mol−1. We suggest an optimum capillary width (0.48 nm) and show that a capillary

16

with this width results in a difference between ∆Fperm(TcO4−) and ∆Fperm(SO42−) of 89

17

kJ mol−1. The observed preference for TcO4− is due to its weakly hydrating nature,

18

reflected in its low experimental hydration free energy.

99

Tc, present in the form of

99

19 20

TOC/Abstract Figure:

21 22


Tc decontamination. The


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23

INTRODUCTION

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The global desire to reduce an over-reliance on fossil fuels whilst simultaneously

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fulfilling the increasing demand for affordable energy has resulted in renewed

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impetus in many national nuclear power programs. The nuclear fission of

27

generates a multitude of radioactive fission products with contrasting chemistries and

28

half-lives. Poor management of the waste products can result in the eventual release

29

of radioisotopes and subsequent migration within the hydrosphere.1-5 Such

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environmental contamination poses a direct radiation risk to the public as well as

31

undermining confidence in the construction of reactors for new nuclear energy

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generation. Previous examples of contamination include the discharge of effluent

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from the Sellafield and La Hague reprocessing plants,2 the leaking waste tanks at the

34

Hanford site in Washington State1 and the accidents that occurred at the Fukushima

35

Daiichi power plant in the aftermath of the Tōhuku earthquake and tsunami in 2011.3

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The scale of the radiological threat to the public due to contaminated water will

37

depend on the activities and half-lives of the radioisotopes released and the extent to

38

which they are able to migrate from the source of contamination in their hydrated

39

form.

40

In the years immediately after waste generation the intermediate half-life

41

90

42

Once these species have largely decayed (after approximately 100 years) two of the

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major contributing isotopes to the total radioactivity are 99Tc and 129I. 99Tc has a half-

44

life of 2.12 × 105 years and readily forms a tetrahedral oxyanion, known as

45

pertechnetate (TcO4−), in aqueous solution, across a broad range of conditions.6

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has a half-life of 1.57 × 107 years and its monovalent anion (I−) has been shown to be

47

the dominant species in many surface waters.7, 8

137

235

U

Cs and

Sr isotopes are expected to dominate the total radioactivity of the waste inventory.


129

I

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There is an obvious requirement for materials that can be used for the complete

49

removal of these radioactive species from contaminated water in an efficient and

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environmentally friendly manner. Many natural and synthetic materials have

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previously been tested for this purpose. Anions do not typically adsorb strongly to the

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mineral components of soils and sediments due to electrostatic repulsion from their

53

surfaces.6 In addition, the presence of environmentally ubiquitous competing anions

54

(e.g. Cl−, SO42− and NO3−) at much higher concentrations than the typical trace levels

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of radioactive TcO4− and I− can inhibit adsorption to any cationic sites that do exist.9

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Due to competition, many traditional remediation materials, such as anion exchange

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resins, have also been shown to have a relatively low affinity for these species.10

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Immobilization by chemical reduction has also been studied (e.g. Tc7+ to Tc4+ using

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zerovalent iron11) but such methods are sensitive to subtle changes in conditions

60

which may result in the return of the contaminant to solution.12 One class of materials

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that have shown some promise for the removal of both TcO4− and I− are activated

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carbons,12, 13 although their low density of surface active sites and slow kinetics can

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limit their potential as effective adsorbents. Improved methods for the removal of

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contaminant radioactive ions from solution are therefore required.

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There has been considerable recent interest in the use of carbonaceous nanomaterials

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for environmental remediation, due to their high surface area to volume ratios,

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controllable pore size distributions and fast adsorption kinetics.14 One example is

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graphene oxide (GO). The GO membrane structure consists of a series of intercalated

69

graphene layers that have regions of oxygen-containing functionalities, predominantly

70

epoxy and hydroxyl groups, and hydrophobic non-oxidized regions.15 When

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immersed in water, the GO membranes are known to swell, forming a layered

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capillary-like structure, allowing fast water transport over the non-oxidized regions of



73

the surface.16 Joshi et al.17 reported that the membranes selectively permit the entry of

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ions according to a size-exclusion mechanism. As well as acting as spacer groups that

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can be used to control the capillary width, the surface functionalities may also provide

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adsorption sites for ionic contaminants.18 The combination of selective ion transport,

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fast water permeability, good mechanical properties and the regular intersheet spacing

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of GO membranes makes them a highly appealing prospect for water purification

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applications, either as a separation membrane or as an adsorbent.19, 20 To exploit the

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potential of GO membranes as a powerful tool for these applications, an improved

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understanding of the entrance and permeation of ions through the membranes is

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required.

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The primary motivation of this work was to establish the potential of GO membranes

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for the cleanup of the problematic TcO4− and I− in the presence of competing anions

85

(SO42− and Cl−) using molecular dynamics (MD) simulations. An umbrella sampling

86

procedure21, 22 was used to generate potentials of mean force (PMF) that describe the

87

entry of the individual anions into the graphene capillaries. The effect of changing the

88

capillary diameter was investigated and the observed entrance barriers in the PMF

89

were rationalized in the context of the hydrated properties of the anions, using the

90

individual simulation trajectories.

91

COMPUTATIONAL METHODS

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Force Field Parameters

93

In our simulations non-bonded interactions were evaluated as the sum of the Coulomb

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interaction and Lennard-Jones 12-6 potential


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 12  6  σ σ Uij ( rij ) = + 4εij  ij  −  ij    rij   rij   4πε 0rij  

96

where qi and qj are the charges of atoms i and j, rij is the interatomic distance and ε0 is

97

the vacuum permittivity. The cross terms, σij and εij, were calculated using the

98

Lorentz-Berthelot combining rules. Carbon atoms in the graphene sheet were modeled

99

as neutral, non-polarizable Lennard-Jones spheres, for which the parameters were

100

taken from an MD study in which the force field was optimized (σc = 0.3214 nm and

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εc = 0.4899 kJ mol−1)23 to reproduce the experimentally observed contact angle for

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water droplets on an uncontaminated graphite surface.24 Bonded parameters were

103

taken from Patra and Wang.25 For the anions we chose parameters, compatible with

104

the SPC/E water model, that have been primarily optimized to match experimental

105

hydration free energies and hydrated radii, but also give a reasonable agreement with

106

diffusion coefficients at infinite dilution.26, 27

107

Model Preparation

108

A model that includes both the graphene capillary and a water reservoir in the same

109

simulation cell is required, so that the process of anion entry into the capillary from its

110

fully hydrated state in the reservoir can be studied. Since the fast water transport in

111

GO membranes is proposed to occur over the hydrophobic regions of the surface,16

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the capillary walls were modeled as pristine graphene sheets, with no oxygen-

113

containing functionalities. Models of the GO membrane were prepared by stacking 12

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parallel sheets (2.21 nm × 3.83 nm) in the z-direction, with an inter-sheet distance of

115

0.335 nm, followed by deletion of either every other, every other two or every other

116

three sheets to generate models with intersheet distances, d, of 0.670, 1.005 and 1.340

117

nm. The effective widths of the capillaries, deff, were 0.349, 0.684 and 1.019 nm,

qi q j


(1)


118

obtained by subtracting the diameter of carbon atoms in our model, σc (0.321 nm),

119

from the distance between the centres of adjacent graphene sheets. The size of the

120

water reservoir was chosen to approximately match the volume used in the hydration

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free energy simulations in our previous work.27 The initial side lengths of the

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simulation cell were therefore Lx = 6.71 nm, Ly = 3.83 and Lz = 4.02 nm. SPC/E water

123

molecules were added to any unoccupied space in the capillaries and reservoir.

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Simulation Protocol

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In all of the simulations the classical equations of motion were integrated using the

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leap-frog algorithm28 with a 1 fs time step. A constant temperature of 298.15 K was

127

maintained using the Nose-Hoover coupling scheme29,

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relaxation time. Electrostatic interactions were evaluated using the Particle-mesh

129

Ewald (PME) summation31, 32 and the 12-6 potential was smoothly turned off between

130

1.0 nm and 1.2 nm using a switch function. The rigid geometry of SPC/E water

131

molecules was constrained using the SETTLE algorithm.33 The systems were

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equilibrated in the canonical ensemble for 100 ps prior to a 5 ns simulation in the

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isothermal-isobaric ensemble. In reality, oxygen-containing functionalities on the

134

basal place of graphene are thought to prevent the aggregation of sheets and stabilize

135

the capillary-like structure when GO is immersed in water.16 Since these functional

136

groups are unaccounted for in our model, we employed harmonic restraints, applied to

137

the initial position of every carbon atom in the graphene sheets using a force constant

138

of 100 kJ mol−1 nm−2, in order to maintain a constant capillary diameter. In the

139

absence of these artificial restraints, the graphene sheets attract each other and force

140

the water out of the capillaries and into the reservoir. A constant pressure of 1 atm

141

was applied in the x-direction; i.e. anisotropic pressure coupling allowed only Lx to

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change, using the Parrinello-Rahman scheme,34 with a relaxation time constant of 1.0

30


with a 5.0 ps thermostat

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ps. The approach is similar to Algara-Siller et al.35 and ensures that the graphene

144

capillaries are completely filled with water.

145

Potential of Mean Force Simulations

146

An umbrella sampling procedure was employed to generate PMFs that describe the

147

process of anions entering the model capillary.21, 22 Umbrella sampling can be used to

148

extend the range of sampling in configuration space by dividing up the chosen

149

reaction coordinate into smaller segments, known as ‘windows’, and modifying the

150

potential energy function in the window with a biasing weight function, w. The

151

reaction coordinate accessible to each window is then sampled in an individual

152

simulation, producing a set of biased probability distributions. The PMF can be

153

generated by unbiasing and recombining the individual biased distributions to obtain a

154

global probability distribution using the weighted histogram analysis method

155

(WHAM).36 For our purposes, the x-coordinate of the centre of mass of the ion was

156

chosen as the reaction coordinate for the PMFs, since x = 0 corresponds to the ion in

157

its fully hydrated state in the centre of reservoir and x = Lx/2 corresponds to a position

158

in the centre of the graphene capillary. The reaction coordinate was divided into

159

windows at increments of 0.1 nm. In each window, w takes the form of a harmonic

160

potential,

161

2 1 w ( x ) = kx ( x − xeq ) 2

(2)

162

where the force constant, kx, is set to 1000 kJ mol−1 nm−2 and xeq is the target position

163

for that window. To generate the starting configurations one water molecule in the

164

centre of the reservoir was chosen at random and swapped for the anion of interest

165

before gradually pulling the anion through the cell in the x-direction at a rate of 0.01



166

nm ps−1. The simulation trajectory was analyzed and the frames in which the anion

167

centre of mass was closest to each window’s xeq were chosen as the initial

168

configurations. In order to obtain PMFs for capillaries of fixed widths, the coordinates

169

of carbon atoms in the sheets were frozen. In each window, w, the initial

170

configuration was relaxed by steepest descents minimization, followed by a 5 ns

171

simulation in the canonical ensemble. The PMFs for anion entry, W(x), were obtained

172

from the final 4 ns of simulation time, using WHAM, as implemented in the

173

GROMAC-4.5.4 g_wham tool.37 This tool was also used to check that there was

174

sufficient sampling overlap in adjacent windows along x. The statistical uncertainty in

175

the PMF was evaluated using a bootstrap analysis approach.

176

RESULTS AND DISCUSSION

177

After a 5 ns isothermal-isobaric MD simulation, the configurations of the three GO

178

membrane models are shown in Figure 1. During model preparation the length of the

179

simulation cell in the x-direction, Lx, decreased due to the influx of water into pore

180

space and this is most pronounced in the narrowest capillary model. The reservoir

181

shrinks to the greatest extent in this model due to the high water density inside the

182

capillary relative to the wider pores. The density profiles in the z-direction for each

183

model are shown in Figure 2. The peaks immediately adjacent to the pore walls are

184

the most intense. The narrowest capillary (deff = 0.349 nm) can only accommodate a

185

monolayer of water and since the hydrogen and oxygen peaks are centred on the same

186

z-position the water molecules must be aligned so that the O – H bonds are parallel to

187

the capillary wall. In the next widest capillary (deff = 0.684 nm) there is enough room

188

for a bilayer of water and many of the molecules are oriented to point one O – H bond

189

into the centre of the capillary. In the widest capillary (deff = 1.019 nm) there were

190

approximately three to four water layers. 10 Environment ACS Paragon Plus

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191 192

Figure 1.

193

and 1.019 nm (bottom) after capillary filling. Although the capillary length in each

194

model is the same, there are slight differences in Lx, resulting from the shrinkage of

195

the water reservoirs due to the fact that the simulations were performed at constant

196

pressure (discussed in ‘simulation protocol’).

GO membrane models with deff = 0.349 nm (top), 0.684 nm (centre)



197 198

Figure 2.

199

graphene capillaries with deff = 0.349 nm (top), 0.684 nm (middle) and 1.019 nm

200

(bottom).

201

Previous simulations have shown that alkali metal cations readily enter into the

202

capillary.17 The entry of an ionic solution can be assumed to be limited by the larger

203

anions allowing the selectivity to be deduced from the single anion PMFs. Since the

204

simulations were conducted in the canonical ensemble, the Helmholtz free energy

205

barrier to anion entry, ∆Fperm, was calculated from the difference in W(x) at x = 0 and

206

x = Lx/2. The observed barriers were rationalized by examination of the various

207

potential energy contributions. The changes in the ion – graphene interaction energy,

208

∆UiC, and the ion – water interaction energy, ∆Uiw, were calculated from the

209

difference between the average interaction energies in the simulation windows at x =

210

0 and x = Lx/2. The changes in hydration numbers along the entrance pathway are

211

shown in Figure 3. The hydration numbers at the primary, n1, and secondary, n2,

z-density profiles of water (O = solid lines, H = dashed lines) in the


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shells were defined as the integrals of the ion – water radial distribution function at

213

the first and second minima. Figure 3 shows that several Å inside each capillary (at

214

approximately x = 2.2 nm) there are no further changes in the primary or secondary

215

coordination numbers for any of the ions, since the distance to the reservoir is greater

216

than the distance from the centre of the ion to its first (r1) or second (r2) hydration

217

shells. Since the focus of this study is on the quantification of the energy barriers

218

associated with ion entry, rather than transport through the membrane, this justifies

219

our use of a relatively short capillary. For each capillary, the barriers and hydration

220

numbers at Lx/2 are given in Table 1.

221 222

Figure 3.

223

hydration numbers along the anion entry pathway (Cl− = red, circles; I− = green,

224

squares; SO42− = blue, diamonds; TcO4− = orange, triangles) for deff = 0.349 nm (top),

225

0.684 nm (middle) and 1.019 nm (bottom) wide capillaries.

The change in primary (open symbols) and secondary (filled symbols)

226 13 Environment ACS Paragon Plus


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227

deff (nm)

Bulk27 Anion

0.349

0.684

1.019

n1

n2

∆Fperm

n1

n2

∆Fperm

n1

n2

∆Fperm

n1

n2

Cl−

7.3

32.0

47.5(8)

5.3

13.6

9.7(4)

7.3

23.4

6.1(4)

7.4

30.0

I−

7.4

35.1

-

-

-

13.5(4)

7.5

24.5

7.4(3)

7.5

30.9

SO42−

14.2

42.3

-

-

-

22.4(7)

12.3

28.7

3.3(6)

14.4

38.8

TcO4−

5.8

37.6

-

-

-

−6.3(6)

5.6

24.4

−4.9(4)

5.2

28.1

Anion entrance barriers (kJ mol−1) and hydration numbers at x = Lx/2. The numbers in brackets show the uncertainty in the final

228

Table 1.

229

digit of ∆Fperm. The cut-off distances for the determination of hydration numbers, obtained using the radial distribution functions published in

230

our previous work,27 are n1 = 0.389 nm (Cl−), 0.415 nm (I−), 0.478 nm (SO42−), 0.428 nm (TcO4−) and n2 = 0.618 nm (Cl−), 0.648 nm (I−), 0.677

231

nm (SO42−), 0.670 nm (TcO4−).

232

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The potential of mean force for Cl− entering the 0.349 nm capillary is shown in Figure

234

4, as well as the density profile of water in the x-direction of the simulation cell. The

235

profile shows that in the middle of the reservoir (x = 0) the experimental density of

236

bulk water is reproduced. In this region the potential of mean force profile is flat. The

237

density of water in these capillaries (x > 2.0 nm) is slightly higher (1060 kg m−3),

238

using our definition of deff. Peaks in the density profile as the capillary entrance is

239

approached are indicative of interfacial ordering and the position of the capillary

240

entrance can be identified using the position of the most intense peak. At the point of

241

entry, the free energy increases before reaching a plateau inside the capillary,

242

resulting in a large entrance barrier (∆Fperm = 47.5 kJ mol−1). The corresponding

243

changes in interaction energy are ∆UiC = −9.9 kJ mol−1 and ∆Uiw = 94.6 kJ mol−1. The

244

unfavorable ∆Uiw corresponds to significant decreases in n1 and n2, demonstrating that

245

anion dehydration due to confinement in the z-direction is the principal cause of the

246

free energy barrier (Figure 3). The interaction energies cannot be quantitatively

247

compared to the free energy barriers, which include other contributions such as

248

entropy. However, the sum of ∆UiC and ∆Uiw is larger than the free energy barrier,

249

suggesting that there is also a significant entropic contribution to entry, associated

250

with the release of water from the ordered hydration shells of the anion into bulk

251

solution. Once Cl− is inside the capillary n1 decreases from 7.3 to 5.3 and the

252

remaining waters are all coordinated in the plane of the capillary.



253 PMF for Cl− anion entry into a capillary with deff = 0.349 nm. The

254

Figure 4.

255

black dashed line is the density profile of water in the x-dimension of the simulation

256

cell for a single capillary.

257

A reliable potential of mean force could not be obtained for the other anions entering

258

into this capillary using the employed umbrella potential force constant. The Cl− ion

259

is small enough to enter this capillary (the radius of the bare ion, rH, is 0.181 nm)27.

260

However, for the other anions, rH is much greater than deff/2 (rH = 0.220, 0.230 and

261

0.250 nm for I−, SO42− and TcO4−, respectively),27 so they are prevented from entering

262

the capillary due to size-exclusion. Free energy barriers could be obtained using

263

umbrella potentials with higher force constants but many more sampling windows

264

would be required to ensure sufficient sampling overlap in adjacent windows.

265

The two larger capillaries modeled can instead accommodate all of the anions

266

considered. Figure 5 shows that for all anions other than TcO4−, anion entry into a

267

capillary with an effective diameter of 0.684 nm is unfavorable (∆Fperm > 0). The

268

capillary is wide enough to accommodate the bare anions, but not necessarily their

269

primary hydration shells (r1 = 0.318, 0.352, 0.370 and 0.381 nm for Cl−, I−, SO42− and

270

TcO4−, respectively)27. The barriers result from the positive energy of dehydration

271

(∆Uiw = 17.9, 14.3 and 83.5 kJ mol−1 for Cl−, I− and SO42−, respectively) outweighing


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272

the energy gain from the interaction between the anion and the graphene sheet (∆UiC =

273

−10.1, −9.5 and −39.4 kJ mol−1 for Cl−, I− and SO42−, respectively). Even in the case

274

of the smallest anion (Cl−), n2 decreases from 30.0 in bulk solution to 23.4 in the

275

center of the capillary. Although n2 decreases significantly, the halide anions are

276

small enough to retain their primary hydration shells in this capillary and therefore

277

have smaller free energy barriers than SO42− (∆Fperm = 22.4 kJ mol−1); n1 decreases

278

from 14.2 to 12.3.

279 280

Figure 5.

281

nm). The black dashed line is the density profile of water along the x-dimension of the

282

simulation cell.

283

On the contrary, there is a significant minimum in the TcO4− potential of mean force

284

upon moving from bulk solution to the entrance of the capillary (at x = 1.65 nm).

285

Surprisingly, there is a further decrease in free energy once inside the capillary

286

(∆Fperm = −6.3 kJ mol−1), suggesting that TcO4− has an affinity for the hydrophobic

287

pristine graphene surface. The magnitude of the favourable ion – graphene interaction

288

(∆UiC = −35.3 kJ mol−1) is greater than the penalty for anion dehydration (∆Uiw = 12.5

289

kJ mol−1). This suggests that TcO4− readily enters into the capillary due to its weakly

290

hydrating nature compared to the other anions, despite being a larger anion. Although

PMFs for anion entry into the intermediate width capillary (deff = 0.684



291

low entrance barriers for weakly hydrating anions (e.g. NO3−) entering narrow

292

hydrophobic channels have previously been observed,38, 39 TcO4− appears to be so

293

weakly hydrating that it prefers to be partially dehydrated inside the capillary relative

294

to its fully hydrated state in solution.

295

Figure 6 shows that the entry of most anions into the widest capillary is still

296

unfavourable (∆Fperm > 0), but the entry barriers are smaller in comparison to the

297

narrower capillaries. The anions are attracted to the centre of the capillary in order to

298

retain their primary hydration shells, made possible because deff/2 is greater the

299

distance to the first hydration shell. n1 actually increases relative to bulk solution,

300

since the distance to the first hydration shell from the position of the ion in the center

301

corresponds to the peaks in the z-density profile of water in the capillary. This is

302

shown in Figure 7, in which the Cl− – oxygen radial distribution function obtained in

303

bulk solution has been overlaid onto the water density profile in one capillary. This

304

capillary, however, is not wide enough to accommodate the second hydration shell (r2

305

= 0.510, 0.531, 0.593 and 0.445 nm for Cl−, I−, SO42− and TcO4−, respectively),27 so n2

306

decreases as the ions enter the capillary. For Cl−, the increase in n1 and decrease in n2

307

cancel out so that ∆Uiw = 0. The entrance barrier for SO42− decreases relative to the

308

halide anions, due to n1 increasing from 14.2 to 14.4, which compensates for partial

309

dehydration of the secondary hydration shell (n2 decreases from 42.8 to 38.8) and

310

∆Uiw is favourable (−5.1 kJ mol−1). This demonstrates that the order of preference of

311

anions in a given capillary has a rather subtle dependency on the specific hydrated

312

structure of the individual anions. The free energy minimum at the capillary entrance

313

(x = 1.75 nm) becomes more pronounced for more weakly hydrating anions.


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314 315

Figure 6.

316

density profile of water along the x-dimension of the simulation cell is shown with a

317

dashed line.

PMFs for anion entry into the wide capillary (deff = 1.019 nm). The

318 319

Figure 7.

320

(black, dashed line) with the radial distribution function for the Cl− and water oxygen

321

pair (red, solid line).

322

Once again, TcO4− entry is favourable (∆Fperm = −4.9 kJ mol−1), unlike the other other

323

anions. The density profiles in Figure 8 show that TcO4− does not remain in the centre

324

of the capillary as it enters, but is instead attracted to the graphene surface, decreasing

325

n1 relative to the fully hydrated state, and resulting in a much larger reduction in n2

326

compared to SO42−. Although TcO4− must be equally attracted to either capillary wall,

Comparison of the density profile of water in the 1.019 nm capillary



327

the density profile suggests that there is an energetic barrier associated with crossing

328

center of the capillary to the other side. ∆Fperm is more favourable in the slightly

329

narrower capillary because of the cooperative interaction between TcO4− and both

330

graphene sheets. In this capillary, ∆UiC and ∆Uiw were −26.4 kJ mol−1 and 12.6 kJ

331

mol−1, respectively.

332 333

Figure 8.

334

(black, dashed line) and the SO42− (blue) and TcO4− (orange) oxyanions.

335

Finally, we seek to find a capillary width that maximizes the selectivity for TcO4−,

336

based on our explanation that dehydration controls the selectivity in the GO

337

membrane. A membrane model with deff = 0.479 nm was constructed by adjusting the

338

initial positions of the graphene sheets of the deff = 0.684 nm capillary and preparing

339

the initial configuration in the same manner. This value of deff was chosen because it

340

is equal to double the radius of the bare TcO4− ion.27 The capillary is wide enough to

341

accommodate a bilayer of water and the PMFs for TcO4− and SO42− are shown in

342

Figure 9. The PMFs show a significant increase in the free energy change for SO42−

343

(∆Fperm = +82.6 kJ mol−1) relative to the 0.684 nm capillary, whereas the free energy

344

change for TcO4− is approximately the same (∆Fperm = −6.1 kJ mol−1). This represents

Density profiles in one capillary of the 1.019 nm wide model for water


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345

a difference of 89 kJ mol−1, and implies an extremely high selectivity for TcO4− over

346

SO42−. The features in the TcO4− PMF inside the capillary are due to small ripples in

347

the graphene sheets and are more pronounced in this model because the capillary is

348

narrower.

349 350

Figure 9.

351

nm). The density profile of water along the x-dimension of the simulation cell is

352

shown with a dashed line.

353

Joshi et al. showed that membranes with an effective capillary diameter of 0.9 nm

354

allow the entry of ions providing that their effective radius is less than 0.45 nm,17

355

suggesting that hydrated GO membranes reject ions species based on size-exclusion.

356

Since the anions studied in this work are relatively small, they are only rejected by

357

narrowest capillary investigated (0.349 nm). Even the smallest anion, Cl−, has a

358

significant free energy barrier to entry in this model. In the wider capillaries (0.684

359

and 1.019 nm) the simulation results suggest that anion entry is energetically

360

unfavourable, due to dehydration caused by confinement. However, the small anions

361

investigated here have low energy barriers so permeation is unlikely to be hindered by

362

entrance effects, consistent with the high flux reported experimentally.17 When the

363

entrance barriers are small, the experimentally observed flux of ions is likely to be

PMFs for anion entry with the optimum capillary width (deff = 0.479



364

strongly dependent on the diffusion of ions within the capillary. In these wider

365

capillaries, ∆Fperm has a more subtle dependence on the anion’s hydration free energy

366

and the specific structure of water in its hydration shells. Although the differences in

367

∆Fperm between I− and Cl− may be too small to effectively separate them using GO

368

membranes purely by controlling the capillary diameter, the simulations predict better

369

control over the selectivity of larger ions.

370

The difference in ∆Fperm between TcO4− and the other anions (especially deff = 0.479

371

nm) suggests that the graphene capillaries are highly selective for TcO4−, despite

372

being larger (rH = 0.250 nm) than the other ions investigated. We found that this is

373

due to the unique attraction of the anion to the surface as a result of its very low

374

hydration free energy. These predictions are consistent with the experimental

375

evidence that TcO4− has a high affinity for porous carbons.13 It has also been shown

376

that activated carbons that have a nanopore diameter of 1 nm are highly efficient

377

TcO4− adsorbents.40 In addition, Galambos et al. observed that only weakly hydrating

378

anions such as ClO4− and NO3− effectively inhibit TcO4− adsorption to this material,

379

whereas more strongly hydrating anions such as Cl− and SO42− do not, supporting our

380

proposed mechanism.41 The capillary widths of GO are similar to the activated carbon

381

nanopore diameters, suggesting that GO could also be used as an effective TcO4−

382

adsorbent. Our results suggest that for certain capillary diameters, TcO4− would be

383

attracted to pristine regions of the graphene sheet, whilst the narrow capillary

384

structure inhibits the entry of more strongly hydrating anions, due to their large

385

dehydration energy barriers. In addition, other workers have observed a high

386

adsorption affinity of the perchlorate anion (which has a similar hydration free energy

387

and hydrated size to TcO4−) to pristine graphene sheets.42


Page 22 of 28

Page 23 of 28


388

Since we have restricted our study to single ion quantities our conclusions can only be

389

deemed valid for dilute ionic solutions. The entry of ions from ionic solution into a

390

GO membrane capillary is also likely to be influenced by cooperative effects between

391

ions and the nature of the counterion. Nevertheless, dilute solutions are considered

392

appropriate for the very low concentrations of radioactive anions typically found in

393

contaminated groundwater. The results suggest that GO offers great potential for the

394

clean up of very weakly hydrating anionic radioactive contaminants, such as TcO4−,

395

but not necessarily more strongly hydrating contaminant anions, such as I−.

396

ACKNOWLEDGMENTS

397

We thank the Engineering and Physical Sciences Research Council (EPSRC) for

398

funding this research, the University of Manchester for use of the Computational

399

Shared Facility and Andrew Masters for helpful discussions during manuscript

400

preparation.

401

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Selective Removal of Technetium from Water ... - ACS Publications

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