Understanding the effect of chemical modification on water desalination in boron nitride nanotubes via molecular dynamics simulation

Desalination 464 (2019) 84–93

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Engineering advance

Understanding the effect of chemical modification on water desalination in boron nitride nanotubes via molecular dynamics simulation

T

Li Zhanga, , Lingjie Jiaa, Jing Zhanga, Jiachen Lia, Lijun Liangb, Zhe Kongc, Jia-Wei Shend, , Xinping Wanga, Wei Zhanga, Hongbo Wange ⁎

⁎

a

Department of Chemistry, Zhejiang Sci-Tech University, Hangzhou 310018, People's Republic of China College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China c College of Material & Environmental Engineering Science, Hangzhou Dianzi University, Hangzhou, 310018, People's Republic of China d School of Medicine, Hangzhou Normal University, Hangzhou 310016, People's Republic of China e Institute of Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China b

ARTICLE INFO

ABSTRACT

Keywords: Molecular dynamics simulation Water flux Salt rejection Chemical modification Space-steric effect

Boron nitride nanotubes (BNNTs) are potential candidates for water desalination owing to their advantages of higher thermal and chemical stabilities as well as resistance to oxidation. In this work, four different types of functional groups were introduced to the end of BNNT (8,8), and the mechanism of water and ion transportation through functionalized BNNTs were investigated via molecular dynamics simulation. The effect of functional groups on desalination performance of BNNT was discussed. It was found that BNNT (8,8)-COO– and BNNT (8,8)-NH3+ systems show well water flux and high ions rejection due to the space-steric effect and electrostatic interaction. Our study also revealed that the water flux in aligned functionalized BNNTs is much higher than that in reverse osmosis (RO) membranes.

1. Introduction The scarcity of fresh water has become a great concern in our life due to the growth of population and the rapid development of industrialization as well as the global climate change [1–3]. The desalination of salty water provides one way of boosting fresh water supplies [4,5]. In the past half century, the most common method employed in desalination is reverse osmosis (RO) membranes [6]. Desalination techniques have made remarkable achievements in recent decade. Nevertheless, current RO membranes suffer from some drawbacks, such as oxidation, fouling and abrasion, and these drawbacks result in instability and insufficient water flux of RO membranes [7–10]. To solve these issues, researchers have developed different materials as membranes, such as carbon nanotubes (CNTs) [11,12], graphene [13,14], and metal-organic frameworks [15] etc. Hummer et.al reported that CNTs have been considered as unique one-dimensional nanomaterials for water transport [16]. Several results have indicated that the flux of water and gases through membranes constructed by CNT arrays is higher than that through RO membranes [17–21]. For example, Ostrikov et al. reported that the plasma-modified carbon nanotube-based membranes exhibit a remarkably high rejection for desalination [20]. Mitra et al. employed carbon nanotube immobilized

⁎

membrane to improve water permeation, and water flux is as high as 121 kg/m2 h [21]. The rapid water permeation behavior and high water flux in CNT membranes suggests that the excellent salt rejection could be achieved by engineering the diameter of CNTs. Corry et al. have illustrated that ions could be blocked at the entrance of CNT by introducing some functional groups [22]. While the water flux decreased due to the space hindrance and the functional groups [23], its application in efficient desalination was greatly limited. Recently, boron nitride nanotube (BNNT), an analogue of CNT, was considered as one of the most promising materials for molecule sieving owing to their advantages of higher thermal and chemical stabilities as well as resistance to oxidation [24,25]. For example, Won et. al have revealed that BNNTs shown outstanding water permeation properties compared to CNTs with similar pore size and length via molecular dynamics (MD) simulation [26]. Jafar et al. found that BNNT (7,7) can remove heavy metals from water with different ratios [27]. Siria [28] et al. developed a boron nitrogen nanotube membrane to convert the osmotic energy into electrical energy efficiently by taking advantage of osmotic pressure between fresh and salt water. Marichy [29] et al. fabricate BNNT mats by controlling the atomic layer deposition of boron nitride, and the BNNT mat displayed excellent performances for absorption of various organic solvents and oils. In our previous work

Corresponding authors. E-mail addresses: [email protected] (L. Zhang), [email protected] (J.-W. Shen).

https://doi.org/10.1016/j.desal.2019.03.014 Received 7 November 2018; Received in revised form 18 March 2019; Accepted 23 March 2019 Available online 29 April 2019 0011-9164/ © 2019 Elsevier B.V. All rights reserved.

Desalination 464 (2019) 84–93

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signal/noise ratio within nanosecond time scale [15,33–35]. The pressure applied on the graphene 4 is only 0.1 MPa. Four different types of functional groups were introduced to the end of BNNT (8,8) and the number of functional group is only one. These functional groups are carboxyl (eCOOH), carboxylate (eCOO−), amino (eNH2), and amine (eNH3+) group, respectively, and they were introduced to the left end of the BNNTs. The schematic of BNNT (8,8)-COO−,BNNT(8,8)-COOH BNNT(8,8)-NH2, BNNT(8,8)-NH3+ are shown in Fig. 2 from the side views of xy and xz plans. During the simulation, some sodium or chloride ions were added to the simulation systems to deal with the unbalanced systems (BNNT (8,8)-COO−, BNNT(8,8)-NH3+).

[30], BNNT (7,7) arrays exhibited excellent performance on desalination, and the salt rejection decrease with the increasing of radius. Although different researches have provided essential knowledge on BNNTs for desalination, there are still some issues, e.g. the effect of chemical modification of BNNTs on desalination, are still open. The effect of pore size of BNNTs on water flux and salt rejection has been investigated in our previous work [30], whether the desalination performance could be improved by introducing different types of functional groups to BNNTs, as revealed in CNTs [22], is still obscure. Therefore, it is critical to indicate the salt rejection and water flux through the BNNTs would be influenced by how many functional groups. Our previous research indicates that BNNT (7,7) displays excellent desalination performance, and the salt rejection value decreases if the diameter of BNNT increases [30]. The aim of this work is to investigate the influence of chemical modification on water flux and salt rejection in BNNTs and obtain BNNT with both high water flux and salt retention by introducing some functional groups to it. Therefore, BNNTs with different diameter as well as different functional groups were constructed. The averaged water flux and salt rejection in these systems are shown in Table S1 in Supporting Information, it could be found that BNNT (8,8) is the most appropriate one to be modified. In this work, four different functional groups were introduced to the entrance of BNNT (8,8) respectively, the performances of water desalination through different functionalized BNNT (8, 8) were examined based on water flux and salt rejection at first, then the effects of pressure on water permeability were quantified, finally, the application of functionalized BNNT (8,8) in the form of aligned arrays were presented and compared with other membranes.

2.2. Simulation details During the simulation process, both the LJ parameters and charge values for BNNTs and graphene sheets are the same as that reported in our previous work [30]. As to the functional groups, the parameters were taken from the CHARMM27 force field [36]. Amber03 force field is used for Na+ and Cl− [37] and TIP3P model was employed to describe water molecules. Both the LJ parameters and charge values for atoms in functionalized BNNTs as well as graphene were listed in Table S2 in Supporting Information. The Lennard-Jones (LJ) potentials for cross interaction between different atoms were calculated by LorentzBerthelot rule [38]. The long-rang electrostatic interaction is calculated with the method of Particle Mesh Ewald (PME) [39], and the cutoff distance was set to be 13.0 Å. The package of Gromacs 5.0.7 was employed to simulate desalination process, and the time step is set to be 2 fs [40]. Initially, the process for energy minimization and a shorter equilibration were performed, then NEMD runs were performed, and the Nosé-Hoover method was used to couple the temperature at 298 K. Periodic boundary conditions (PBC) were applied in x and y dimensions, and the initial velocities were chosen randomly. In our simulation, each system was performed with 50 ns. The potential of mean force (PMF) for water molecule and ions passing through two types functionalized BNNT (8, 8) were determined by umbrella sampling [41] and generated by weighted histogram analysis method (WHAM) [42]. The force constant of the spring used for pulling is 1000 kJ·mol−1·nm−2. In all PMF calculation, water molecule and ions were located in the center of functionalized BNNT (8,8) along z axis in NVT ensemble, and 176 simulations are generated by increasing 0.2 Å between 119.8 Å < z < 155 Å with 0.2 Å increase, every window were performed to plot the profiles of PMF and the simulation time for each window was 4 ns.

2. Computational methods and details 2.1. Setup of model Membranes composed of functional BNNT (8,8) were modeled following our previous methodology [30] and Aluru's work [31]. As shown in Fig. 1, each BNNT with the diameter of 10.9 Å and length of 50 Å were constructed by visual molecular dynamics (VMD) [32]. Two graphene plates (graphene2 and graphene 3) were employed to hinder water molecules passing through the membranes. There were two boxes containing NaCl solution and pure water, respectively, and the two boxes were separated by functional BNNT. The left box contained 2106 water molecules and the right box contained 1528 water molecules, and the concentration of NaCl in left box is 0.5 M, it is close to the salt concentration in seawater. Additionally, two graphene plates (graphene 1 and graphene 4) were introduced into the end of two boxes, then an external force along +z axis direction was applied on each carbon atom of the graphene 1 and graphene 4 to make it moveable, and the pressures applied vary from 50 to 250 MPa, the value of applied pressure is approximately 1 order of magnitude higher than practical values. Such high pressure is usually employed in non-equilibrium molecular dynamics simulation (NEMD) to reduce thermal noise and enhance the

3. Results and discussion 3.1. Salt rejection and water performance through functionalized BNNTs Water molecules flows from the left box to the right box due to the exerted pressure on NaCl solution at the beginning of the desalination Fig. 1. Simulation system for water desalination through functionalized BNNT (8,8). Two water boxes are separated by functionalized BNNT (8,8). The concentration of NaCl in the left box is 0.5 M and in right box is pure water. Different atoms shown with different colors, B: pink, N: blue, C: cyan, H: white, O: red, Na+: yellow, Cl−: green. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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Fig. 2. The schematic of BNNT(8,8)-COO−,BNNT(8,8)-COOH,BNNT(8,8)-NH2 and BNNT(8,8)-NH3+ from side views in (a) xy plan (b) xz plan.

(a)

Water flux/molecule· ns-1

1600

Nw(t)

1200

800

COOCOOH NH2

400

Water flux Na+ rejection Cl- rejection

NH3+

Salt rejection%

(b)

2000

0 0

10

20

30

40

50

BNNT(8,8)-COO-BNNT(8,8)-COOHBNNT(8,8)-NH2BNNT(8,8)-NH3

t (ns) Fig. 3. (a) The Number of transferred water molecules through functionalized BNNTs from NaCl solution to pure water boxes as a function of simulation time. (b) The averaged water flux (red bar), Na+ rejection (blue bar) and Cl− rejection (green bar) with its error bar in BNNT (8,8) modified by different functional groups in 200 MPa. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

process. Graphene1 moves from the left to the right under applied pressure, correspondingly, graphene4 moves to the right when water molecules flow from the left box to the right box, while graphene2 and graphene3 are stationary during the simulations. Some ions (Na+ or Cl−) would pass through the functionalized BNNTs during the desalination process. Fig. 3(a) shows the net number of water molecules transferred through different functionalized BNNTs under applied pressure of 200 MPa. From Fig. 3a, it could be found that the number of transferred water molecules through all functionalized BNNTs almost linearly increased during first ~20 ns, then the increase are slow down and reach to platforms after ~40 ns, which suggests that the transfer speed of water molecules would be slow down due to the increase of osmotic pressure. With more and more water molecules transfer from the left box to the right box, the concentration of NaCl reach to ~4 M, and the osmotic pressure in the system is about 200 bar according to the work of Roux et.al [43], but it is still smaller than the applied pressure, and the transfer behavior would not be stopped unit most water molecules transfer to the right box. Therefore, the water flux and salt rejection could be calculated according to the trajectory before 20 ns. In order to assess the effect of functional groups on desalination integratedly, both the water flux and the salt rejection rate were calculated according to Eqs. (1) and (2)

water flux =

Nt2 t2

salt rejection% = Cinitial =

Nt 1 t1 Cinitial

Tion , C(pass) TH2 O

(1)

Cpass

Cinitial P = ion PH2 O

(2)

where Nt2/Nt1 represent the total number of water molecules in the left box at different time. Tion and TH2O represent the total number of ions and water molecules in the left box, respectively. Pion and PH2O represent the number of ions and water molecules passing through the BNNT (8,8) before 20 ns. Firstly, the water flux and the ratio of salt rejection through functionalized BNNT (8,8) as well as under 200 MPa were calculated and listed in Table S3, and the water flux passing through pristine BNNT (8,8) was also listed in Table S3 for comparison. The water flux is about 81.4 molecule per ns in BNNT (8,8)-COO−, and the water flux value in BNNT (8,8)-COOH, BNNT (8,8)-NH2, BNNT (8,8)-NH3+ under the same applied pressure are 94.7, 91.1 and 82.9 molecule per ns, respectively, but all of them are smaller than that in pristine BNNT (8,8) (~98.9 molecule per ns). From Fig. 3b, it could be found that less water molecules pass through BNNTs with charged functional groups. This result 86

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Fig. 4. Snapshot of ions with hydration layer near the entrance of BNNTs at 10 ns from top views. (a) BNNT-COO− , (b) BNNTCOOH, (c) BNNT-NH2 and (d) BNNT-NH3+ systems. The atom detail for functional groups are enlarged and shown in dashed square. B: pink, N: blue, C: cyan, H: white, O: red, Na+: yellow, Cl−: green. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

is similar to that reported in CNT membranes by Corry et.al [22], they reported that the water flux in CNT with two NH3+ group decrease to 67% value of that in pristine CNT, while the salt rejection increases to 100%. They also revealed that there was only small change of water flux in CNT (8,8)-COOH, the largest change occupied in the membranes constructed by nanotubes with charged functional groups [44]. The decrease of water flux in BNNT (8,8) with charged functional group may be attributed to two factors, the first one is the space-steric effect caused by the functional group. The effective diameter of the nanotube would be decreased due to the functional group, some water molecules need to adjust their configuration when move to the entrance of the nanotubes. The second factor is the steric blockages caused by the attractive interaction between ions and charged functional groups, this can be confirmed by the snapshots of ions with hydration layer shown in Fig. 4. The radial distribution functions (RDFs) between water molecules and Na+ and Cl− were calculated and shown in Fig. S1.Water molecules within 0.3 nm of ions are considered as the hydration layer according to the RDFs. Some Na+ and Cl− could be detected around COO– and NH3+ groups owing to the attractive interaction between ions and charged functional groups. This results in the decrease of effective diameter of BNNT and the increase of steric hindrance. Oppositely, due to the strong repulsion interaction between ions and functional groups with the same charge, it is difficult for Cl− and Na+ to pass through BNNT (8,8)-COO– and BNNT (8,8)-NH3+, respectively. The second factor can also be employed to explain why the water flux in BNNT (8,8)-COOH and BNNT (8,8)-NH2 is larger than that in BNNT (8,8)-NH3+ and BNNT (8,8)-COO−. During the simulation, some water molecules were selected to illustrate the water permeation behavior through functionalized BNNTs as discussed in Jiang et al. works [15,45,46]. Fig. 5 shows the z coordinate of some water molecules during the desalination process. The lines with different colors in Fig. 5 represent different water molecules and each colour represents one water molecule, three water molecules are randomly selected to describe their trajectories in z- direction. As shown Fig. 1, the distance between 13 and 18 nm in z-direction corresponds to the nanotube of BNNT, while the distance between 9–13 and 18–21 nm corresponds to the left box and right box, respectively. In BNNT(8,8), BNNT(8,8)-COOH and BNNT(8,8)-NH2 systems, the position of water molecules passing through 12 nm to 18 nm changes in a very short time, that is, the permeation behavior of water molecules is

quickly. However, very clear difference could be found in BNNT (8,8)COO– and BNNT(8,8)-NH3+ systems, water molecule need to spent more time (> 1 ns) to pass through these BNNTs. From the trajectory of water molecules in BNNT (8, 8)-COO– and BNNT(8, 8)-NH3+ systems, water molecules would oscillate around the entrance of the tube (12–14 nm), i.e. water molecules need to adjust their configuration to enter the nanotube owing to the strong electronic interaction between water molecules and COO–/NH3+ groups as well as the space-steric effect caused by the functional group. In order to understand the interaction mechanism between water molecules and the charged functional groups, the average number of hydrogen bonds (H-bonds) between NH3+/-COO– groups and water molecules were calculated and plotted in Fig. 6. A geometrical criterion of hydrogen bond [47] concerning the oxygen‑oxygen, oxygen‑hydrogen distances as well as the bond angle was employed in this work. Two molecules are considered to be hydrogen bond if the hydrogen bond described in forms of XeHeY and the following two conditions are fulfilled at the same time. (1) The distance between XeY is smaller than 3.5 Å. (2) The bond angle between XeH and HeY directions, θ, must be < 30°. More H-bonds could be found at the entrance of BNNT (8,8)-NH3+ and BNNT (8,8)-COO−, which suggests that certain water molecules would be trapped around the functional group. This is agreed with the snapshots shown in Fig. 7, where two or three hydrogen bonds between functional groups and water molecules could be observed. The H-bond network existed around the functional group would reduce the number of water molecules passing through the functionalized BNNTs, this can be attributed to the relative strong interaction between water molecules and functional groups. In order to confirm this viewpoint, the autocorrelation function c(t) as well as the lifetime of H-bonds in BNNT(8,8)-COO−, BNNT(8,8)-NH3+, BNNT(8,8) systems were calculated and plotted in Supporting Information (Fig. S2). The lifetime of H-bonds in BNNT(8,8)-COO−, BNNT(8,8)-NH3+ systems suggests the relative strong interaction between water molecules and functional groups. On the other hand, the transfer dynamics would be slow down, some water molecules need to adjust their configuration owing to the steric blockage. The averaged salt rejection values and its error bar for each functionalized BNNT under 200 MPa was also plotted in Fig. 3(b), It could be found that the salt rejection would be improved by introducing functional groups, as shown in Fig. 3(b) and Table S3, the salt rejection 87

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(a)

(b)

(c) BNNT(8,8)-COOH-water

21

21

18

18

18

15

Z(nm)

21

Z(nm)

Z(nm)

BNNT(8,8)-water

15

12

12

0

5

10

15

9 0

20

5

10

15

0

5

10

20

+

BNNT(8,8)-NH3 -water

-

BNNT(8,8)-COO -water

15

t (ns)

(e)

(d)

21

18

Z(nm)

18

Z(nm)

20

t (ns)

t (ns)

21

15

12

9

9

BNNT(8,8)-NH2-water

15

15

12

12

9

9 0

5

10

15

0

20

5

10

15

20

t (ns)

t (ns)

Hydrogen bonds number

Fig. 5. Trajectories of randomly selected water molecules passing through functionalized BNNTs in 200 MPa.

in pristine BNNT (8,8) is 85.1%, while this value in BNNT (8,8)-COOH and BNNT (8,8)-NH2 systems increase to 88.6% and 92.8%, respectively. The averaged Na+ and Cl− rejection ratio in BNNT (8,8)-COOH is 90.4% and 91.7%, respectively. The different rejection value for Na+ and Cl− ions is influenced by the functional group at some moment accidentally. More strikingly, the salt rejection in BNNT (8,8)-COO– and BNNT (8,8)-NH3+ systems can reach 100%. This is also confirmed by the averaged number density profiles for ions in z direction under 200 MPa, as shown in Fig. 8, no ions could be detected in right box (18–22 nm) in BNNT (8,8)-COO– and BNNT (8,8)-NH3+ systems. This indicates that no ions could pass through BNNT (8,8)-COO– and BNNT (8,8)-NH3+. While some Na+ and Cl− ions could be detected in the right box of BNNT (8,8), BNNT (8,8)-COOH and BNNT (8,8)-NH2 systems, i.e a few of ions could pass through these nanotubes. Three ions(shown with different colour in Fig. 8) are randomly selected to describe their trajectories in z direction, the relationship between z coordinate of three ions and simulation time in BNNT (8,8)-NH3+ and BNNT (8,8)-COO– systems were also illustrated in Fig. 9. All ions were blocked from the nanotube during the desalination process, this result is also consist with

BNNT(8,8) + BNNT(8,8)-NH3

5

BNNT(8,8)-COO

-

4 3 2 1 0 0

3

6

9

12

time (ns) Fig. 6. The averaged number of hydrogen bonds between -NH3+/-COO– groups of BNNT (8,8) and water molecules.

Fig. 7. Snapshot of the water molecules near the COO– group(a) and the NH3+ group(b) in the systems, the red dashed lines represents the hydrogen bonds formed between water molecules and functional groups as well as between water molecules.

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(a) 3

(b)

+

Na

Cl

BNNT(8,8)

-

BNNT(8,8) BNNT(8,8)-COOBNNT(8,8)-COOH BNNT(8,8)-NH2

3

-

BNNT(8,8)-COO BNNT(8,8)-COOH BNNT(8,8)-NH2

2

BNNT(8,8)-NH3+

+

2

Nd (Z)

Nd (Z)

BNNT(8,8)-NH3

1

1

0

0 9

12

15

18

9

21

12

15

18

21

Z (nm)

Z (nm)

Fig. 8. The number density distributions of (a) Na+ and (b) Cl− ions at 15 ns. Two ends of the BNNTs were represented by dashed lines (z = 13 and 18 nm).

(a)

21

+

Na + Na + Na

-

BNNT(8,8)-COO -ions

+

+

Na + Na + Na

BNNT(8,8)-NH3 -ions 18

Z(nm)

Z(nm)

18

(b) 21

-

Cl Cl Cl

15

12

-

Cl Cl Cl

15

12

9

9

0

5

10

15

20

0

5

10

15

20

t (ns)

t (ns)

Fig. 9. Trajectories of randomly selected Na+ and Cl− through BNNT (8,8)-COO– and BNNT (8,8)-NH3+ systems.

the salt rejection listed in Fig. 2b and Table S2. It could be found that some ions were trapped around the entrance of nanotubes in BNNT (8,8)-COO– and BNNT (8,8)-NH3+ systems from Fig. 4, this can be attributed to the attractive interaction between ions and charged functional groups, which results in the decrease of effective diameter of BNNT and the increase of steric hindrance. Consequently, it is hard for Cl− and Na+ ions passing through BNNT (8,8)-COO– and BNNT (8,8)NH3+ systems. This can also be confirmed by the relationship between water molecules and simulation time shown in Fig. 3a, the increase are slow down and reach to platforms after ~40 ns, which suggests that the transfer speed of water molecules would be slow down due to the

confinement of ions and the increase of osmotic pressure. As discussed in our previous work [30], the salt rejection is closely related to applied pressures, therefore, different applied pressures were selected to reveal the desalination efficiency of functionalized BNNT (8,8) in this manuscript. The averaged water flux as well as the salt rejection under different applied pressures were calculated and displayed in Fig. 10. The water flux in functionalized BNNT (8,8) increases linearly with the increase of pressure, for example, the water flux in BNNT (8,8)-COO– increased from 21.9 to 100.4 molecules per ns when the pressure increased from 50 Mpa to 250 Mpa. As to the BNNT (8,8)NH3+ system, the water flux increased from 21.7 to 108.1 molecules

Pressure (MPa)

Water flux Na+ rejection Cl- rejection

Salt rejection%

Water flux Na+ rejection Cl- rejection

Water flux/molecule· ns-1

(b)

Salt rejection%

Water flux/molecule· ns-1

(a)

Pressure (MPa)

Fig. 10. The water permeation and salt rejection in functionalized BNNT (8,8) with different applied pressures: (a) BNNT (8,8)-COO– and (b) BNNT (8,8)-NH3+. 89

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(a)

(b) 50 Water + Na Cl

Water + Na Cl

40

PMF(kJ/mol)

PMF(kJ/mol)

40

50

30

20

10

30

20

10

0

0 -3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

-3.5

0.0

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

Reaction coordinate /nm

Reaction coordinate /nm

Fig. 11. Potential of mean force of water molecules and ions passing through functionalized BNNT (8,8). (a) BNNT (8,8)-COO−; (b) BNNT (8,8)-NH3+. The reaction coordinate is along the central axis of BNNT (8,8). The green dashed lines represent the location of the functional group. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

per ns, and it could be found that the water flux in BNNT (8,8)-COO– is very similar to that in BNNT (8,8)-NH3+systems. On the other hand, the salt rejection for Na+ and Cl− ions are close to 100% in all different applied pressures except for that under 250 MPa, there is only one Na+ and Cl - passing through the (8,8)-COO– system at 250 MPa. This can be attributed to directional applied force act on graphene sheets in NEMD, which makes the transportation of ions through BNNT nanopores become easier and the rejection of ions decrease. The averaged water flux and the salt rejection under different applied pressure indicate that BNNT (8,8)-NH3+ could achieve efficient desalination with high salt rejection.

BNNT(8,8) (only 8), this can be employed to explain why the salt rejection would be improved from thermodynamics. Besides, it is also found that free energy for ions (Na+/Cl−) inside BNNT (8,8)-COO– is much larger than that outside of BNNT (8,8). This result indicates that ions would like to stay in the outside of BNNT (8,8)-COO– rather than in its pore channel. From the PMF profile for Na+ ion shown in Fig. 11(a), a small decrease can be detected if the sodium ion moves close to the entrance of BNNT (8,8)-COO−, this can be attributed to the attractive interaction between Na+ and COO– group. On the contrary, the increase of free energy at the entrance of BNNT (8,8)-COO– could be detected in PMF profile for Cl− due to the repulsive interaction between COO– group and Cl−. These results can be employed to explain the trapping phenomenon shown in Fig. 4. The PMF profiles of water molecule in BNNT (8,8)-NH3+ is quite similar to that in BNNT (8,8)-COO−. Small difference in PMF profiles for ions in BNNT (8,8)-NH3+ and BNNT (8,8)-COO– systems still could be detected. The PMF profile for Cl− shows a small decrease near the entrance owing to the attractive interaction, but the free energy would be increase once the chlorine ion enter into the nanotube, since Cl− needs to overcome the attractive interaction between Cl- and NH3+ group. Correspondingly, the free energy increases near the entrance due to the repulsive interaction between Na+ and the functional group of NH3+ . In short summary, the transfer bebavior of ions in BNNT (8,8) modified with charged functional groups is unfavorable in terms of thermodynamics and dynamics owing to the larger free energy gap between water molecules and ions as well as the decrease of effective diameter caused by the trapped phenomena, therefore, the salt rejection and desalination performance would be improved.

3.2. The mechanism of desalination of BNNT (8,8)-COO– and BNNT (8,8)NH3+ To further investigate the mechanism of desalination, the PMF which describes the free energy profile of water molecule and ions passing through functionalized BNNT (8, 8) were calculated and provided in Fig. 11(a) and (b). The position of the functional groups was defined as the entrance of the nanotube (green dashed lines) in PMF profile. The geometrical center of BNNTs was 0 of reaction coordinate. The direction from left to right is the direction of water and ions entering into the BNNTs. It could be found that the free energy barrier for water molecule passing through BNNT (8, 8)-COO– (from left to right in x-axis, as shown in Fig. 11) is around 10 kJ/mol, while the free energy barriers for Na+ and Cl− are ~40.0 kJ/mol. The free energy difference between water molecule and ions is ~30 kJ/mol, in other words, ions have to overcome relative higher energy barriers if they pass through the functionalized BNNT (8,8). As discussed in our previous work [30], the reaction rate constants for H2O and ions (k(H2O)/k(Na+/Cl−)) passing through BNNT (8,8) with chemical modification could be assumed by the free energy difference according to the transition state theory [48], which are expressed by Eq. (3), where k is the reaction rate constant, T is temperature, and R is molar gas constant (8.314 J·mol−1·K−1). The reaction rates for H2O and Na+ passing through BNNT can be supposed to be proportional to their reaction rate constants, then the selectivity of water molecules over Na+/Cl− ions can be estimated by k(H2O)/k(Na+/Cl−).

k (H2 O)

e

k (H2 O ) k (Na+)

e

G (H2 O ) , RT

k (Na+)

G (Na+)

e

G (H2 O ) RT

G (Na+) RT

3.3. The application of functionalized BNNT (8,8) array in desalination Based on the desalination behavior of salty water in functionalized BNNTs, BNNT (8,8)-COO– and BNNT (8,8)-NH3+ were selected to construct aligned BNNT arrays (shown in Fig. 12(a) and (b)), the averaged water flux and salt rejection through functionalized BNNT (8,8) arrays under different applied pressure were also calculated and plotted in Fig. 12(c) and (d), it could be observed that the averaged water flux through BNNT (8,8) -NH3+ array and BNNT (8,8) –COO– array is about 38–40 L·cm−2·day−1·MPa−1 under different applied pressure. The salt rejection for Cl− in the aligned BNNT(8,8)-COO– arrays could reach 100%. The Na+ rejection decrease with the applied pressure increase, the different Na+ and Cl− rejection values in BNNT(8,8)COO– system are caused by the strong repulsive/attractive interaction between Cl−/Na+ and COO– groups. As shown in Fig. 11, there are nine

(3) (4)

In this manuscript, the selectivity of water molecules over Na+/Cl− ions is approximately 181,451 owing to the relative higher free energy difference(~30 kJ/mol); while this value is much larger than that in 90

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(d)

Salt rejection %

Water flux/L· cm-2·day-1·MPa-1

Water flux/L· cm-2·day-1·MPa-1

60

Water flux Na+ rejection Cl- rejection

CO

50

100

40 30

80

20 60 10 0

M M M M 0M ay-50- array-100- array-15 - rray-200 - rray-250 -a -a O O O O O O O O C C C C

40

-50M 150M 100M 200M 250M array + -array- + -array- + -array- + -arrayNH 3 NH 3 NH 3 NH 3

r O -ar -

120

Water flux Na+ rejection Cl- rejection

Salt rejection %

(c)

+3

Fig. 12. Schematic of aligned BNNT (8,8) array with chemical modification and graphene membrane in top view (a)-COO– (b) -NH3+. The averaged salt rejection and water flux through functionalized BNNT (8,8) array in different applied pressures (c) -COO– (d)-NH3+. + and Cl− rejection vamovement of Na+ . The difference between Na lues would be enhanced when the applying pressure increases during the non-equilibrium molecular dynamics simulations. The similar phenomenon in aligned BNNT (8,8)-NH3+ array could be explain with the same reason. Fig. 13 illustrates the performances of functionalized BNNT (8, 8) arrays as well as existing commercial RO and nanofiltration membrane reported in the literature [49,50]. In order to make sure the water flux in different pressure and materials present a fair comparison, both the applied pressure and surface area have been divided. It is found that the water flux of functionalized BNNT (8, 8) array would be two orders of magnitude larger than that in commercial seawater RO and nanofiltration membranes. Moreover, the salt rejection can reach 100% under pressure of 100 MPa. From Fig. 13, it could be found that the aligned functionalized BNNT (8, 8) arrays are predicted to possess superior performance, and it could be considered as one of the potential promising nanomaterials for water desalination owing to their well performance (high water flux and excellent salt rejection) under different applied pressures.

105

RO membrane

Salt rejection %

100

+

BNNT(8,8)-NH3 -array Graphene

Nanofitration 95

-

BNNT(8,8)-COO -array

90 85 80

MFI Zeolite 75 70 1E-5

1E-4

1E-3

0.01

0.1

1

10

100

1000

Water flux/L·cm-2·day-1·MPa-1 Fig. 13. Performance chart for BNNT (8,8) array with chemical modification versus existing technologies (MFI zeolite, RO membrane and nanofiltration [49], graphene [50]).

4. Conclusions

–COO– groups at the entrance of pore in BNNT-COO– array, and it led to strong repulsive electrostatic interaction, which makes Cl− hardly passing through the BNNT-COO– array. On the contrary, the attractive interaction between Na+ and COO– groups would accelerate the

In this work, molecular dynamics simulation were employed to investigate the water desalination through functionalized BNNTs from thermodynamics and dynamics Our results revealed that the water flux 91

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through BNNT (8,8)-COO– and BNNT (8,8)-NH3+ decreased 20% in comparison with the pristine BNNT (8,8). This can be attributed to the space-steric effect caused by the functional groups as well as the steric blockages caused by the ions around the entrance of the tube. Our study also shows 100% salt rejection could be obtained by introducing 1 NH3+ group or 1 COO– group to BNNT (8,8). Ions could be blocked outside from the entrance of BNNTs due to space-steric effect as well as the electrostatic repulsion between ions and charged functional groups. This is also confirmed by the free energy profiles for water molecule and ions passing through the functionalized BNNT (8, 8), and it is found that ions have to overcome a relative high energy barrier to pass through the functionalized BNNT (8,8). BNNT (8,8)-COO– and BNNT (8,8)-NH3+ were selected to construct aligned BNNT arrays, and the water flux in these two membranes was enhanced remarkably. The water flux in aligned BNNT (8,8)-NH3+ could reach 40 L·cm−2·day−1·MPa−1 and the salt rejection is as high as 100%. The water flux in functionalized BNNT (8, 8) arrays is two orders of magnitude higher than the current generation of RO membranes. Our results would give some ideas for the experimenter to synthesize more nanomaterials with excellent desalination performance.

porous graphene, Nat. Nanotechnol. 7 (2012) 728–732. [14] K. Sint, B. Wang, P. Král, Selective ion passage through functionalized graphene nanopores, J. Am. Chem. Soc. 130 (2008) 16448. [15] K.M. Gupta, K. Zhang, J. Jiang, Water desalination through zeolitic imidazolate framework membranes: significant role of functional groups, Langmuir 31 (2015) 13230–13237. [16] G. Hummer, J.C. Rasaiah, J.P. Noworyta, Water conduction through the hydrophobic channel of a carbon nanotube, Nature 414 (2001) 188–190. [17] J.K. Holt, H.G. Park, Y. Wang, M. Stadermann, A.B. Artyukhin, C.P. Grigoropoulos, A. Noy, O. Bakajin, Fast mass transport through Sub-2-nanometer carbon nanotubes, Science 312 (2006) 1034–1037. [18] B. Corry, Designing carbon nanotube membranes for efficient water desalination, J. Phys. Chem. B 112 (2008) 1427–1434. [19] J. Shen, Z. Kong, L. Zhang, L. Liang, Controlled interval of aligned carbon nanotubes arrays for water desalination: a molecular dynamics simulation study, Desalination 395 (2016) 28–32. [20] H.Y. Yang, Z.J. Han, F. Yu, K.L. Pey, K. Ostrikov, R. Karnik, Carbon nanotube membranes with ultrahigh specific adsorption capacity for water desalination and purification, Nat. Commun. 4 (2013) 2220. [21] M. Bhadra, S. Roy, S. Mitra, A bilayered structure comprised of functionalized carbon nanotubes for desalination by membrane distillation, ACS Appl. Mater. Interfaces 8 (2016) 19507–19513. [22] B. Corry, Water and ion transport through functionalised carbon nanotubes: implications for desalination technology, Energy Environ. Sci. 4 (2011) 751–759. [23] J. Liu, G. Shi, P. Guo, J. Yang, H. Fang, Blockage of water flow in carbon nanotubes by ions due to interactions between cations and aromatic rings, Phys. Rev. Lett. 115 (2015) 164502. [24] A.P. Suryavanshi, M.F. Yu, J. Wen, C. Tang, Elastic modulus and resonance behavior of boron nitride nanotubes, Appl. Phys. Lett., 84 (2004) 2527–2529. [25] C. Zhi, Y. Bando, C. Tang, D. Golberg, R. Xie, S. Takashi, Erratum: “phonon characteristics and cathodolumininescence of boron nitride nanotubes” [Appl. Phys. Lett.86, 213110 (2005)], Appl. Phys. Lett. 86 (2005) 1561. [26] C.Y. Won, N.R. Aluru, Water permeation through a subnanometer boron nitride nanotube, J. Am. Chem. Soc. 129 (2007) 2748–2749. [27] J. Azamat, A.R. Khataee, W.J. Sang, Removal of heavy metals from water through armchair carbon and boron nitride nanotubes: a computer simulation study, RSC Adv. 5 (2015) 25097–25104. [28] A. Siria, P. Poncharal, A.L. Biance, R. Fulcrand, X. Blase, S.T. Purcell, L. Bocquet, Giant osmotic energy conversion measured in a single transmembrane boron nitride nanotube, Nature 494 (2013) 455–458. [29] W. Hao, C. Marichy, A. Brioude, W. Hao, C. Marichy, A. Brioude, W. Hao, C. Marichy, A. Brioude, Promising properties of ALD boron nitride nanotube mat for water purification, Environ. Sci. Nano (2017) 10–1039. [30] L. Liang, J.C. Li, L. Zhang, Z. Zhang, J.W. Shen, L. Li, J. Wu, Computer simulation of water desalination through boron nitride nanotubes, Phys. Chem. Chem. Phys. 19 (2017). [31] Y. Wu, L.K. Wagner, N.R. Aluru, Hexagonal boron nitride and water interaction parameters, J. Chem. Phys. 144 (2016) 1034. [32] W. Humphrey, A. Dalke, K. Schulten, VMD: visual molecular dynamics, J. Mol. Graph. 14 (1996) 33–38. [33] Z. Hu, Y. Chen, J. Jiang, Zeolitic imidazolate framework-8 as a reverse osmosis membrane for water desalination: insight from molecular simulation, J. Chem. Phys. 134 (2011) 2317. [34] M. Heiranian, A.B. Farimani, N.R. Aluru, Water desalination with a single-layer MoS2nanopore, Nat. Commun. 6 (2015). [35] W. Li, Y. Yang, J.K. Weber, Z. Gang, R. Zhou, Tunable, strain-controlled nanoporous MoS2 filter for water desalination, ACS Nano 10 (2016) 1829. [36] A.D. MacKerell Jr., D. Bashford, M. Bellott, R.L. Dunbrack Jr., J.D. Evanseck, M.J. Field, S. Fischer, J. Gao, H. Guo, S. Ha, All-atom empirical potential for molecular modeling and dynamics studies of proteins, J. Phys. Chem. B 102 (1998) 3586–3616. [37] Y. Duan, C. Wu, S. Chowdhury, M.C. Lee, G. Xiong, W. Zhang, R. Yang, P. Cieplak, R. Luo, T. Lee, A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations, J. Comput. Chem. 24 (2003) 1999–2012. [38] J.O. Hirschfelder, C.F. Curtiss, R.B. Bird, Molecular Theory of Gases and Liquids, Wiley, New York, 1954. [39] T. Darden, D. York, L. Pedersen, Particle mesh Ewald: an N·log(N) method for Ewald sums in large systems, J. Chem. Phys. 98 (1993) 10089–10092. [40] B. Hess, C. Kutzner, D.S.D. Van, E. Lindahl, GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation, J. Chem. Theory Comput. 4 (2008) 435–447. [41] B. Roux, The calculation of the potential of mean force using computer simulations, Comput. Phys. Commun. 91 (1995) 275–282. [42] S. Kumar, J.M. Rosenberg, D. Bouzida, R.H. Swendsen, P.A. Kollman, The weighted histogram analysis method for free-energy calculations on biomolecules. I. The method, J. Comput. Chem. 13 (1992) 1011–1021. [43] Y. Luo, B. Roux, Simulation of osmotic pressure in concentrated aqueous salt solutions, J. Phys. Chem. Lett. 1 (2009) 183–189. [44] M. Thomas, B. Corry, A computational assessment of the permeability and salt rejection of carbon nanotube membranes and their application to water desalination, Phil. Trans. R. Soc. A 374 (2016) 20150020.

Acknowledgments This work was financially supported by the National Natural Science Foundation of China (Grant Nos. 51702073, 21674032, 21503186, 61602142). It was also supported by the Project Grants 521 Talents Cultivation of Zhejiang Sci-Tech University and supported by the Young Researchers Foundation of Zhejiang Provincial Top Key Academic Discipline of Chemical Engineering and Technology (ZYG2017001). This work was also supported by the Key Fostering Project of Scientific Research of Hangzhou Normal University (2018PYXML006) and the High Level Returned Overseas Chinese Innovation Projects in Hangzhou. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.desal.2019.03.014. References [1] T. Hillie, M. Hlophe, Nanotechnology and the challenge of clean water, Nat. Nanotechnol. 2 (2007) 663–664. [2] Q. Schiermeier, Water: purification with a pinch of salt, Nature 452 (2008) 260–261. [3] J. Eliasson, The rising pressure of global water shortages, Nature 517 (2015) 6. [4] R.F. Service, Desalination freshens up, Science (New York, N.Y.) 313 (2006) 1088. [5] M. Elimelech, W.A. Phillip, The future of seawater desalination: energy, technology, and the environment, Science 333 (2011) 712–717. [6] Y. Zhang, J.L. Sargent, B.W. Boudouris, W.A. Phillip, Nanoporous membranes generated from self-assembled block polymer precursors: Quo Vadis? J. Appl. Polym. Sci. 132 (2015). [7] C. Fritzmann, J. Löwenberg, T. Wintgens, T. Melin, State-of-the-art of reverse osmosis desalination, Desalination 216 (2007) 1–76. [8] H. El-Saied, A.H. Basta, B.N. Barsoum, M.M. Elberry, Cellulose membranes for reverse osmosis part I. RO cellulose acetate membranes including a composite with polypropylene, Desalination 159 (2003) 171–181. [9] K.P. Lee, T.C. Arnot, D. Mattia, A review of reverse osmosis membrane materials for desalination—development to date and future potential, J. Membr. Sci. 370 (2011) 1–22. [10] K.M. Gupta, Z. Qiao, K. Zhang, J. Jiang, Seawater pervaporation through zeolitic imidazolate framework membranes: atomistic simulation study, ACS Appl. Mater. Interfaces 8 (2016) 13392. [11] K. Zhao, H. Wu, Fast water thermo-pumping flow across nanotube membranes for desalination, Nano Lett. 15 (2015) 3664. [12] J.K. Holt, H.G. Park, Y. Wang, M. Stadermann, A.B. Artyukhin, C.P. Grigoropoulos, A. Noy, O. Bakajin, Fast mass transport through sub-2nm carbon nanotubes, Science 312 (2006) 1034–1037. [13] S.P. Koenig, L. Wang, J. Pellegrino, J.S. Bunch, Selective molecular sieving through

92

Desalination 464 (2019) 84–93

L. Zhang, et al.

[48] Y. Kang, Z. Zhang, H. Shi, J. Zhang, L. Liang, Q. Wang, H. Ågren, Y. Tu, Na+ and K+ ion selectivity by size-controlled biomimetic graphene nanopores, Nanoscale 6 (2014) 10666–10672. [49] M.T.M. Pendergast, E.M.V. Hoek, A review of water treatment membrane nanotechnologies, energy environ, Sci. 4 (2011) 1946–1971. [50] D. Cohentanugi, J.C. Grossman, Water desalination across nanoporous graphene, Nano Lett. 12 (2012) 3602–3608.

[45] X. Kong, J. Jiang, Porous organic cage membranes for water desalination: a simulation exploration, Phys. Chem. Chem. Phys. 19 (2017) 18178–18185. [46] Q. Shi, K. Zhang, R. Lu, J. Jiang, Water desalination and biofuel dehydration through a thin membrane of polymer of intrinsic microporosity: atomistic simulation study, J. Membr. Sci. 545 (2018) 49–56. [47] M. Ferrario, M. Haughney, I.R. Mcdonald, M.L. Klein, Molecular-dynamics simulation of aqueous mixtures: methanol, acetone, and ammonia, J. Chem. Phys. 93 (1990) 5156–5166.

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