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Removal of nitrate ion from water using boron nitride nanotubes: Insights from molecular dynamics simulations
Accepted Manuscript Removal of nitrate ion from water using boron nitride nanotubes: Insights from molecular dynamics simulations Jafar Azamat, Alireza Khataee PII: DOI: Reference:
S2210-271X(16)30440-6 http://dx.doi.org/10.1016/j.comptc.2016.11.002 COMPTC 2288
To appear in:
Computational & Theoretical Chemistry
Received Date: Revised Date: Accepted Date:
16 November 2015 23 October 2016 2 November 2016
Please cite this article as: J. Azamat, A. Khataee, Removal of nitrate ion from water using boron nitride nanotubes: Insights from molecular dynamics simulations, Computational & Theoretical Chemistry (2016), doi: http:// dx.doi.org/10.1016/j.comptc.2016.11.002
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Removal of nitrate ion from water using boron nitride nanotubes: Insights from molecular dynamics simulations
Jafar Azamat,a Alireza Khataee a,b,* a
Research Laboratory of Advanced Water and Wastewater Treatment Processes, Department of Applied
Chemistry, Faculty of Chemistry, University of Tabriz, 51666-16471 Tabriz, Iran b
Department of Materials Science and Nanotechnology, Near East University, 99138 Nicosia, North Cyprus,
Mersin 10, Turkey
*
Corresponding author: E–mail address:
[email protected] ([email protected]) Tel.: +98 4133393165; Fax: +98 4133340191
1
Abstract Removal of nitrate ions, as a pollutant, from water using armchair boron nitride nanotubes (BNNTs) was investigated by molecular dynamics (MD) simulations. The investigated system included a BNNT embedded between two graphene sheets as a membrane. This membrane was immersed into a water box containing nitrate ions. For the removal of nitrates, an external pressure was applied to the system. Six types of armchair BNNTs with different diameter including (4,4), (5,5), (6,6), (7,7), (8,8) and (9,9) BNNTs were used. The simulation results showed that the BNNTs with different diameters acted differently relative to permeation of nitrate ions and water molecules. The permeation of nitrate ions through the BNNTs was dependent on the applied pressures and the diameter of nanotubes. The flow rate of water through BNNTs was increased by increasing the diameter of the nanotubes.
Keywords: Boron nitride nanotube; Graphene; Nanostructured membrane; Nitrate.
2
1. Introduction Nitrate ion contamination is made at the nitrification state in nitrogen cycle and is a common ground source of water pollutant resulting from industrial and natural sources. Nitrate ion is a highly soluble form of nitrogen and is a common groundwater pollutant [1]. Natural sources of nitrate are atmospheric precipitation, local mineral deposits such as potassium nitrate and farm animal wastes. Although nitrate ion is a nontoxic ion, it can be the precursor of many carcinogens through reducing to nitrite ion by bacteria [2]. High levels of nitrate contamination are found in shallow groundwater that is used as a source of drinking water [3]. It is known that the levels of nitrate contaminations exceeding 10 mg/L limit is associated with certain health problems. Nitrate ion is relatively nontoxic to adults but it can be fatal to infants under six months of age. In the exposed infants, nitrate is reduced to nitrite, which combines with hemoglobin in the blood to form methemoglobin, and leads to blue baby syndrome [1, 4]. Also nitrates can be combined with amines to form nitrosamines. It is one of the potential carcinogens in human body. Overall, the long-term effect of high nitrate drinking water consumption is unknown, but there are some potential risks against health caused by nitrite. Therefore, removal of nitrate contaminations from water is important, because drinking water supply is one of the main concerns in the world and the drinking of low quality water causes health hazards in the community. On the other hand, nitrate is a stable and highly soluble ion and its co-precipitation or adsorption is difficult. Concerning the nitrate properties, the removal of nitrate from water with conventional water treatment methods such as lime softening and filtration is a challenging problem. Different methods were used to remove nitrate from water; i.e. chemical and electrochemical reduction, ion exchange, biological removal, and reverse osmosis [5, 6]. However, all these methods aren’t applicable in every situation [7, 8]. Up to the present time, many researches have been developed for industrial applications 3
by the removal of nitrate ion from water and separation processes applying nanostructure membranes [9, 10]. One of these nanostructures is single wall boron nitrite nanotube (SWBNNT). BNNTs were first theoretically predicted [11], and soon after its prediction, they were successfully experimentally synthesized [12]. In recent years, most of the studies have been done on the synthesis of BNNTs [13-16]. The tubular structure of these nanotubes was denoted by a pair of indexes (m, n). The m and n are the number of unit vectors of 2D hexagonal boron nitrite (h-BN) sheet, which connects the two crystallographic equivalent sites on the h-BN sheet. Depending on the values of these two indexes, there are three types of BNNTs structures including armchair (m=n), zigzag (m=0), and chiral (m ≠n) nanotubes. Scientists are using BNNTs due to their properties [17-19]. One of the main characteristics of BNNTs is their ion selective property; therefore, they have potential uses in the purification industries. Up to date, BNNTs were used as ion-selective devices [20-24]. The selectivity of BNNTs was reported by Won and coworkers. They used a (10, 10) BNNT to study its ionic selectivity relative to chloride and potassium ions. They indicated that this nanotube could separate chloride ions [20]. Azamat et al. performed molecular dynamics (MD) simulations to investigate the separation of heavy metals from water using BNNTs. Their results showed that the (7,7) and (8,8) BNNTs were exclusively selective to cations and anions [25]. In the other work, Chen has confirmed that BNNTs had interactions with proteins and therefore these nanotubes can be used in biocompatible materials [26]. Nanok and coworkers investigated the structure and dynamics of water molecules confined in BNNTs by theoretical methods [27]. To the best of our knowledge, no study has been reported about the removal of nitrate ions from aqueous solution using the BNNTs. Therefore, in this work, we studied the removal of nitrate ions from aqueous solutions using armchair BNNTs as a membrane under induced pressure using MD simulation method. This method is one of the main fields of 4
nanotechnology that can be used for design, production and scale up of various processes.
2. Simulation methodology and details We used six types of armchair BNNTs with a length of 21 Å and different diameters including (4,4), (5,5), (6,6), (7,7), (8,8), and (9,9) BNNTs as shown in Figure 1. Density functional theory method was used for a full geometric optimization of the electronic ground state of these BNNTs and sodium nitrate. These calculations were carried out by GAMESS package [28] at the B3LYP level of theory using 6-311G basis sets. Partial charges and Lennard-Jones parameters for all type of atoms are summarized in Table 1. The simulation box for all runs was 3×3×8 nm3. As shown in Figure 2, an armchair BNNT is embedded between two graphene sheets in the center of simulation cell. The whole system is immersed in an aqueous solution of sodium nitrate. The BNNT and graphene sheets were fixed during the simulation time. Approximately 1650 water molecules and 10 nitrate ions were in the simulation box. The long range interactions and the short range interactions for atomic species were described with the Coulomb potentials (UC) and the Lennard-Jones potential (Uvdw), respectively. The particle mesh Ewald (PME) method [29] was used to calculate the long range electrostatic interactions. Van der Waals interactions were truncated with a 12 Å spherical cutoff. The cross interaction Lennard-Jones parameters between fragments, ij and
ij , were calculated by the Lorenz-Berthelot mixing rules: ij
where
i j 2
and ij i j
(1)
i , j , i and j are the Lennard-Jones parameters for interactions occurring
between fragments i and j, respectively [30]. The potential energy (U e) of the intermolecular 5
interactions is given by the sum of Uc and Uvdw, as follow:
12 6 ij ij U e = U c + U vdw = + 4 ij - 4πε 0 rij rij rij q i .q j
(2)
where qi and qj are the partial charges assigned to atoms i and j; rij is the distance between species i and j. The interaction parameters of water-BNNT, water-ions and ions-BNNT were derived using the Lorentz-Berthelot combining rules. The MD simulations were done using the NAMD 2.9 program [31] with a 1 fs time step, similar to the previous reports [32-40]. Also, all data analysis were carried out using the VMD 1.9.2 [41]. To represent water molecules, the TIP3P model [42] was employed. Parameters for the graphene were taken as the parameters for sp2like aromatic carbons in the CHARMM27 force field [43, 44] and BNNTs parameters were taken from Azamat et al. [45]. For the parameterization of nitrate ions, the method of Mayne et al. [46] were used. This method is a rapid parameterization method of small molecules using the force field toolkit in VMD [46]. Parameters obtained by this method correspond with other parameters in the scientific literature (see Table 1). The system was minimized with NAMD using 500000 minimization steps at 0 K, and equilibrated for 100000 MD steps via an NVT ensemble at 298 K. Then 5 ns MD simulations were performed for analysis with VMD. The Langevin dynamics method [47] was used to keep the temperature at 298 K. Pressure-driven membrane processes use pressure difference between the water to be treated and a permeate side as the driving force to transport water contaminations through the membrane system. For the separation of nitrate ions, pressure is needed to be applied to the system. For this purpose, a previously established method established by Zhu et al. was used in our system [48, 49]. This method has been used in many works [50-52]. In this method, applied 6
pressure exerted to the selected region of system, as the applied constant force as Eq. (3):
P
n.F A
(3)
where ΔP is the pressure (Pa), n is the number of water molecules in the selected region, F (pN) is the applied force, and A (m2) is the area of the system. The force was applied to the oxygen atom of water molecules in a selected region of the system. The region is within a fixed distance of approximately 0.85 nm from the left or right boundary of the system. These forces cause a pressure gradient through the BNNTs. The applied pressure was up to 200 MPa and it was applied to approximately 540 water molecules.
3. Results and discussion In this work, MD simulations technique was used to investigate the removal of nitrate ions using armchair BNNTs. Six types of armchair BNNTs were used and in each case, the passage or non-passage of water and nitrate were investigated. The results show that in the case of the (4,4) BNNT, due to its small diameter, water molecules and nitrate ions cannot pass through it. Therefore, this type of nanotube is not suitable for the separation of contaminants from water. Water molecules could pass through (5,5) BNNT and larger ones, but nitrate ions could not pass across the (5,5) and (6,6) BNNTs and remained at one side of them. Due to these characteristics of the (5,5) and (6,6) BNNTs, these nanotubes are suitable if we want to keep nitrate ions on one side of the membrane. However, the flow rate of water is low in these types of nanotubes, due to the single file structure of water molecules inside them. In the large BNNTs ((7,7), (8,8) and (9,9)), nitrate ions as well as water molecules can pass through them with different ratios.
7
3.1. Water structure properties Each water molecule can form four hydrogen bonds with other neighboring water molecules in bulk system, but due to space restrictions, this characteristic of water molecules is different from bulk water inside nanotubes. Moreover, this arrangement of water molecules changes with the permeation of nitrate ions through nanotubes. Figure 3 shows different arrangement of water molecules inside the investigated BNNTs. To illustrate this phenomenon, we used the radial distribution function (RDF) parameter between BNNTs and inner water molecules. This parameter is defined as the probability of finding an atom or molecule at a distance of r away from a given reference atom or molecule. The RDF between BNNT-inner water molecules is shown in Figure 4. The characteristics of peak varied in each BNNT due to different arrangements of inner water molecules. As can be seen in Figure 3, in the case of (5,5) and (6,6) BNNTs, arrangement of inner water molecules is as a single structure file which is shown with a peak in their RDFs. The water molecules arrangement is changed to the spiral mode in the (7,7) and (8,8) BNNTs. This change in the structure of inner water molecules is due to the increase in the size of BNNTs diameter. This structure was confirmed via two peaks in RDF. Finally, in the (9,9) BNNT, both the single file structure and spiral mode were detected together. Accordingly, its RDF displayed three peaks; a peak for the single file structure and two peaks for the spiral structure of water molecules.
3.2. Nitrate permeation The number of nitrate ions and water molecules passing across the BNNTs was obtained from the simulation results. With increasing applied pressures to the system, the number of molecules and ions passing across nanotubes was increased. However, due to the size of nitrate ions, passage was not possible through the (4,4), (5,5) and (6,6) BNNTs. But, nitrates are able to pass through the other larger nanotubes (Figure 5). Also water molecules have 8
similar behavior in the case of (4,4) BNNT and do not pass through it. By increasing the applied pressure and diameter of the BNNTs, the number of passing water molecules was increased as shown in Figure 6. As previously mentioned nitrate ions passed through different large BNNTs by applying pressure to the system. Meanwhile time is an important parameter to remove them. With increasing the applied pressure to the system, removal time of nitrates was decreased. Furthermore, this parameter has been downtrended with increasing the size of the BNNTs. In this work, the retention time of nitrate ions, i.e., the time of passing one nitrate across the BNNT, was calculated. The MD results showed that the retention time of nitrates depends on the applied pressures. As shown in Figure 7, the retention time of ions decreases with increasing both the diameter of BNNT and applied pressure. It can be argued that it is easier for the nitrate to pass through the large BNNTs at high pressures. Actually, low and high pressures can affect in the passing time of one ion through the considered BNNTs. Regarding to low pressure, there was an overlap between the passing time of ions; however, in case of a high pressure, this overlap did not exist. In other words, one nitrate enters into BNNT and it doesn’t exit until a second ion enters the nanotube in low pressure; however, in a high pressure, nitrates can exit the nanotube without any help. During the passage of water molecules through the nanotubes, always some water molecules remain inside the nanotube (inner water). Figure 8 shows the number of inner water molecules based on the applied pressures. The number of inner water molecules was slightly changed with increasing the applied pressure. But, this parameter increases by increasing the diameter of BNNTs. Accordingly, the number of hydrogen bonds between the inner water molecules was also raised by increasing the diameter of BNNTs (Figure 9). Also formation of hydrogen bonds between inner water molecules and nitrate ions passing through nanotube was consistent with previous justifications. With increasing the diameter of
9
BNNTs, number of inner water molecules and nitrates were increased. Consequently, the number of hydrogen bonds between them was increased (Figure 10), but the increasing applied pressures, did not significantly impact on this trend.
3.3. Density profile The fluid structure within the nanotube can be best characterized by the density profile. Figure 11 illustrates the density profile of nitrate ions in the BNNTs under different applied pressures. This parameter was obtained from trajectory files of MD simulations in the pressure of 10 MPa for the (8,8) BNNT and 200 MPa for the (6,6) and (9,9) BNNTs. As previously mentioned nitrate ions did not pass across BNNTs with small diameters, such as (5,5) and (6,6) nanotubes, and remain on one side of the cell (blue curve), even at high pressures. In the case of (9,9) BNNT, all nitrates were removed from polluted water (black curve) and finally in the (8,8) BNNT under low pressure (10 MPa), some nitrates were removed from polluted water (pink curve). The non-permeation of nitrate from small BNNT was happened under all ranges of applied pressures. But in the case of (8,8) BNNT, as well as (9,9) BNNT, a full removal of nitrates was happened, in high pressures with different retention times (Figure 7). This time for a specified pressure (such as 200 MPa) for the (9,9) nanotube was less than that of (8,8) nanotube due to easier passage nitrate ions.
4. Conclusion BNNTs with unique physical and chemical properties have a variety of potential applications in nanotechnology especially for water treatment industry. In this research, we studied the removal of nitrate ion using armchair BNNTs embedded between two graphene sheets by MD simulations technique. The separation of nitrate ion from water using BNNTs was happened by applying pressure to the system. The BNNTs with different diameters can 10
remove nitrate ion from aqueous solution. Nitrate ions and water molecules are passed through the large BNNTs with different retention times. In contrast, in the case of small BNNTs, such as (5,5) and (6,6) BNNTs, only water molecules are passed through them, and nitrate ions are filtered. Eventually, it can be maintained that our findings can be used for designing new membranes applicable in water desalination technology.
Acknowledgments Authors thank the University of Tabriz for the support provided. We also acknowledge the support of Iran Science Elites Federation. Jafar Azamat as a postdoc researcher gratefully acknowledges use of the services and facilities of the University of Tabriz.
References [1] A. Kapoor, T. Viraraghavan, Nitrate removal from drinking water-Review, J. Environ. Eng., 123 (1997) 371-380. [2] A.C. Kite-Powell, A.K. Harding, Nitrate contamination in oregon well water: geologic variability and the public’s perception, JAWRA, 42 (2006) 975-987. [3] O. Fenton, K.G. Richards, L. Kirwan, M.I. Khalil, M.G. Healy, Factors affecting nitrate distribution in shallow groundwater under a beef farm in South Eastern Ireland, J. Environ. Manage., 90 (2009) 3135-3146. [4] E.F. Winton, R.G. Tardiff, L.J. McCabe, Nitrate in drinking water, JAWRA, 63 (1971) 95-98. [5] K. Kesore, F. Janowski, V.A. Shaposhnik, Highly effective electrodialysis for selective elimination of nitrates from drinking water, J. Membr. Sci., 127 (1997) 17-24. [6] Biological Denitrification of Water, J. Environ. Eng., 115 (1989) 930-943. [7] A.S. Koparal, Ü.B. Öğütveren, Removal of nitrate from water by electroreduction and electrocoagulation, J. Hazard. Mater., 89 (2002) 83-94. [8] G.E. Dima, A.C.A. de Vooys, M.T.M. Koper, Electrocatalytic reduction of nitrate at low concentration on coinage and transition-metal electrodes in acid solutions, J. Electroanal. Chem., 554–555 (2003) 15-23. 11
[9] J.J. Sardroodi, J. Azamat, A. Rastkar, N.R. Yousefnia, The preferential permeation of ions across carbon and boron nitride nanotubes, Chem. Phys., 403 (2012) 105-112. [10] K. Dhungana, R. Pati, Boron nitride nanotubes for spintronics, Sensors, 14 (2014) 17655. [11] A. Rubio, J.L. Corkill, M.L. Cohen, Theory of graphitic boron nitride nanotubes, Phys. Rev. B: Condens. Matter, 49 (1994) 5081-5084. [12] N.G. Chopra, R.J. Luyken, K. Cherrey, V.H. Crespi, M.L. Cohen, S.G. Louie, A. Zettl, Boron nitride nanotubes, Science, 269 (1995) 966-967. [13] D. Seo, J. Kim, S.-H. Park, Y.-U. Jeong, Y.-S. Seo, S.-H. Lee, J. Kim, Synthesis of boron nitride nanotubes using thermal chemical vapor deposition of ball milled boron powder, J. Ind. Eng. Chem., 19 (2013) 1117-1122. [14] P. Ahmad, M.U. Khandaker, Y.M. Amin, Z.R. Khan, Synthesis of boron nitride microtubes and formation of boron nitride nanosheets, Mater. Manuf. Processes, 30 (2014) 184-188. [15] A. Pan, Y. Chen, Large-scale fabrication of boron nitride nanotubes with high purity via solid-state reaction method, Nanoscale Res. Lett., 9 (2014) 1-6. [16] P. Ahmad, M.U. Khandaker, Y.M. Amin, Synthesis of boron nitride nanotubes by argon supported thermal chemical vapor deposition, Physica E, 67 (2015) 33-37. [17] D. Golberg, Y. Bando, C.C. Tang, C.Y. Zhi, Boron nitride nanotubes, Adv. Mater., 19 (2007) 2413-2432. [18] E.C. Anota, G. Cocoletzi, J.F.S. Ramírez, Armchair BN nanotubes—levothyroxine interactions: a molecular study, J. Mol. Model., 19 (2013) 4991-4996. [19] E. Chigo Anota, G. Cocoletzi, First-principles simulations of the chemical functionalization of (5,5) boron nitride nanotubes, J. Mol. Model., 19 (2013) 2335-2341. [20] C.Y. Won, N.R. Aluru, A chloride ion-selective boron nitride nanotube, Chem. Phys. Lett., 478 (2009) 185-190. [21] D. Tang, D. Kim, Temperature effect on ion selectivity of potassium and sodium ions in solution, Chem. Phys., 428 (2014) 14-18. [22] H. Ebro, Y.M. Kim, J.H. Kim, Molecular dynamics simulations in membrane-based water treatment processes: A systematic overview, J. Membr. Sci., 438 (2013) 112-125. [23] A. Khosrozadeh, Q. Wang, V.K. Varadan, Molecular simulations on separation of atoms with carbon nanotubes in torsion, Comput. Mater. Sci, 81 (2014) 280-283. [24] J. Azamat, J.J. Sardroodi, Ion and water transport through (7, 7) and (8, 8) carbon and boron nitride nanotubes of different electric fields: a molecular dynamics simulation study, J. 12
Comput. Theor. Nanosci., 11 (2014) 2611-2617. [25] J. Azamat, A. Khataee, S. Joo, Separation of a heavy metal from water through a membrane containing boron nitride nanotubes: molecular dynamics simulations, J. Mol. Model., 20 (2014) 1-9. [26] X. Chen, P. Wu, M. Rousseas, D. Okawa, Z. Gartner, A. Zettl, C.R. Bertozzi, Boron nitride nanotubes are noncytotoxic and can be functionalized for interaction with proteins and cells, J. Am. Chem. Soc., 131 (2009) 890-891. [27] T. Nanok, N. Artrith, P. Pantu, P.A. Bopp, J. Limtrakul, Structure and dynamics of water confined in single-wall nanotubes, J. Phys. Chem. A, 113 (2008) 2103-2108. [28] M.W. Schmidt, K.K. Baldridge, J.A. Boatz, S.T. Elbert, M.S. Gordon, J.H. Jensen, S. Koseki, N. Matsunaga, K.A. Nguyen, S. Su, a. et, General atomic and molecular electronic structure system, J. Comput. Chem., 14 (1993) 1347-1363. [29] G. Ciccotti, D. Frenkel, I.R. McDonald, Simulation of liquids and solids: Molecular dynamics and monte carlo methods in statistical mechanics North Holland, New York, 1987. [30] L. Viola, S. Lloyd, Dynamical suppression of decoherence in two-state quantum systems, Phys. Rev. A, 58 (1998) 2733-2744. [31] L. Kalé, R. Skeel, M. Bhandarkar, R. Brunner, A. Gursoy, N. Krawetz, J. Phillips, A. Shinozaki, K. Varadarajan, K. Schulten, NAMD2: Greater scalability for parallel molecular dynamics, J. Comput. Phys., 151 (1999) 283-312. [32] J. Azamat, A. Khataee, S.W. Joo, Functionalized graphene as a nanostructured membrane for removal of copper and mercury from aqueous solution: a molecular dynamics simulation study, J. Mol. Graphics Modell., 53 (2014) 112-117. [33] J. Azamat, J.J. Sardroodi, A. Rastkar, Water desalination through armchair carbon nanotubes: a molecular dynamics study, RSC Adv., 4 (2014) 63712-63718. [34] J. Azamat, A. Khataee, S.W. Joo, Molecular dynamics simulation of trihalomethanes separation from water by functionalized nanoporous graphene under induced pressure, Chem. Eng. Sci., 127 (2015) 285-292. [35] J. Azamat, A. Khataee, S.W. Joo, Removal of heavy metals from water through armchair carbon and boron nitride nanotubes: a computer simulation study, RSC Adv., 5 (2015) 25097-25104. [36] A. Khataee, J. Azamat, G. Bayat, Separation of nitrate ion from water using silicon carbide nanotubes as a membrane: Insights from molecular dynamics simulation, Comput. Mater. Sci, 119 (2016) 74-81. [37] J. Azamat, A. Khataee, F. Sadikoglu, Separation of carbon dioxide and nitrogen gases 13
through modified boron nitride nanosheets as a membrane: insights from molecular dynamics simulations, RSC Adv., 6 (2016) 94911-94920. [38] J. Azamat, A. Khataee, S.W. Joo, Separation of copper and mercury as heavy metals from aqueous solution using functionalized boron nitride nanosheets: A theoretical study, J. Mol. Struct., 1108 (2016) 144-149. [39] J. Azamat, A. Khataee, S.W. Joo, Molecular dynamics simulations of trihalomethanes removal from water using boron nitride nanosheets, J. Mol. Model., 22 (2016) 82. [40] J. Azamat, Functionalized graphene nanosheet as a membrane for water desalination using applied electric fields: Insights from molecular dynamics simulations, J. Phys. Chem. C, 120 (2016) 23883-23891. [41] W. Humphrey, A. Dalke, K. Schulten, VMD: Visual molecular dynamics, J. Mol. Graphics, 14 (1996) 33-38. [42] D.J. Price, C.L. Brooks, A modified TIP3P water potential for simulation with Ewald summation, J. Chem. Phys., 121 (2004) 10096-10103. [43] S.E. Feller, A.D. MacKerell, An improved empirical potential energy function for molecular simulations of phospholipids, J. Phys. Chem. B, 104 (2000) 7510-7515. [44] J.B. Klauda, B.R. Brooks, A.D. MacKerell, R.M. Venable, R.W. Pastor, An ab initio study on the torsional surface of alkanes and its effect on molecular simulations of alkanes and a DPPC bilayer, J. Phys. Chem. B, 109 (2005) 5300-5311. [45] J. Azamat, J. Sardroodi, The permeation of potassium and chloride ions through nanotubes: a molecular simulation study, Monatsh Chem, 145 (2014) 881-890. [46] C.G. Mayne, J. Saam, K. Schulten, E. Tajkhorshid, J.C. Gumbart, Rapid parameterization of small molecules using the force field toolkit, J. Comput. Chem., 34 (2013) 2757-2770. [47] X. Wu, B.R. Brooks, Self-guided Langevin dynamics simulation method, Chem. Phys. Lett., 381 (2003) 512-518. [48] F. Zhu, E. Tajkhorshid, K. Schulten, Pressure-induced water transport in membrane channels studied by molecular dynamics, Biophys. J., 83 (2002) 154-160. [49] F. Zhu, E. Tajkhorshid, K. Schulten, Theory and simulation of water permeation in aquaporin-1, Biophys. J., 86 (2004) 50-57. [50] B. Corry, Designing carbon nanotube membranes for efficient water desalination, J. Phys. Chem. B, 112 (2008) 1427-1434. [51] X. Gong, J. Li, H. Lu, R. Wan, J. Li, J. Hu, H. Fang, A charge-driven molecular water pump, Nat. Nanotechnol., 2 (2007) 709-712. 14
[52] J. Goldsmith, C.C. Martens, Pressure-induced water flow through model nanopores, Phys. Chem. Chem. Phys., 11 (2009) 528-533.
15
Tables Table 1. Partial charges (q) and Lennard-Jones parameters (ε and σ) for all type of atoms. Type of atom
q(℮)
ε (kJ/mol)
σ (Å)
B (BNNT)
+0.4
0.393
3.453
N (BNNT)
-0.4
0.602
3.365
N (nitrate)
+0.95
0.669
1.604
O (nitrate)
-0.65
0.711
1.675
16
Figures
Figure 1. Schematic design of boron nitride nanotubes considered in this research. BNNT (4,4), (5,5), (6,6), (7,7), (8,8), and (9,9).
17
Figure 2. A snapshot of the simulated box with 3×3×8 nm3 size (Black: carbon atoms of graphene sheets; blue: nitrogen atoms of nanotube and nitrate ion; pink: boron atoms of nanotube; yellow: sodium ion; red: oxygen atoms of water and nitrate ion; and white: hydrogen atoms of water).
18
Figure 3. Arrangement of inner water molecules in studied BNNTs. The structure of inner water molecules changes in different nanotubes.
19
35 BNNT(5,5)
BNNT(6,6)
30
BNNT(7,7)
RDF water-BNNT
25
BNNT(8,8) BNNT(9,9)
20 15 10 5 0 0
2
4
6
8
r (Å) Figure 4. RDFs of BNNT- inner water for all systems in the simulation cell.
20
10
Number of nitrates passing through BNNTs
BNNT(9,9)
25
BNNT(8,8) BNNT(7,7) 20
15
10
5
0 0
50
100 Pressure (MPa)
150
200
Figure 5. The number of nitrate ions passing through the (7,7), (8,8) and (9,9) BNNTs. Lines were obtained from a linear regression. Each data point represents the average of five sets of simulations.
21
Number of waters passing through BNNTs
3000 BNNT(9,9) BNNT(8,8)
2500
BNNT(7,7) BNNT(6,6)
BNNT(5,5)
2000
1500
1000
500
0 0
50
100 Pressure (MPa)
150
200
Figure 6. The number of water molecules passing through the BNNTs. Lines were obtained from a linear regression. Each data point represents the average of five sets of simulations.
22
0.7 BNNT(7,7)
0.6 BNNT(8,8) BNNT(9,9)
Retention time (ns)
0.5 0.4 0.3 0.2 0.1 0 0
50
100 Pressure (MPa)
150
200
Figure 7. Retention time of nitrate ions across different BNNTs under various applied pressures.
23
Figure 8. Number of inner water molecules under various applied pressures. Each data point represents the average of five sets of simulations.
24
Figure 9. Number of hydrogen bonds between inner water-water molecules under various applied pressures. Each data point represents the average of five sets of simulations.
25
Number of hydrogen bonds between water-nitrate inside BNNTs
4
3
2
BNNT(9,9)
1
BNNT(8,8) BNNT(7,7)
0 0
50
100 Pressure (MPa)
150
200
Figure 10. Number of hydrogen bonds between inner water and nitrates in the (7,7), (8,8) and (9,9) BNNTs under various applied pressures. Lines were obtained from a linear regression. Each data point represents the average of five sets of simulations.
26
0.3 BNNT(9,9) BNNT(8,8)
Density profile
BNNT(6,6)
0.2
0.1
0 -40
-30
-20
-10 0 10 Axial position (Å)
20
30
40
Figure 11. Density profile of nitrate ions in three type of the BNNTs in z direction of simulation cell system (blue: none of nitrates are passed through the (6,6) BNNT under 200 MPa pressure; pink: some of nitrates are removed from water using the (8,8) BNNT under 10 MPa pressure; and black: all nitrates are removed from water using the (9,9) BNNT under 200 MPa pressure).
27
Graphical Abstract
A snapshot of the simulated system, containing boron nitride nanotubes, graphene, ions and water molecules. (Black: graphene sheets; blue: nitrogen atoms of nanotube and nitrate ion; pink: boron atoms of nanotube; yellow: sodium ion; red: oxygen atoms of water and nitrate ion; and white: hydrogen atoms of water). Nitrate and sodium ions are displayed with van der Waals modes.
28
Research Highlights:
BNNTs have the ability to remove nitrate. Amounts of nitrate removal in various BNNTs were different. The removal of nitrate was dependent on the applied pressures.
29
S2210-271X(16)30440-6 http://dx.doi.org/10.1016/j.comptc.2016.11.002 COMPTC 2288
To appear in:
Computational & Theoretical Chemistry
Received Date: Revised Date: Accepted Date:
16 November 2015 23 October 2016 2 November 2016
Please cite this article as: J. Azamat, A. Khataee, Removal of nitrate ion from water using boron nitride nanotubes: Insights from molecular dynamics simulations, Computational & Theoretical Chemistry (2016), doi: http:// dx.doi.org/10.1016/j.comptc.2016.11.002
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Removal of nitrate ion from water using boron nitride nanotubes: Insights from molecular dynamics simulations
Jafar Azamat,a Alireza Khataee a,b,* a
Research Laboratory of Advanced Water and Wastewater Treatment Processes, Department of Applied
Chemistry, Faculty of Chemistry, University of Tabriz, 51666-16471 Tabriz, Iran b
Department of Materials Science and Nanotechnology, Near East University, 99138 Nicosia, North Cyprus,
Mersin 10, Turkey
*
Corresponding author: E–mail address:
[email protected] ([email protected]) Tel.: +98 4133393165; Fax: +98 4133340191
1
Abstract Removal of nitrate ions, as a pollutant, from water using armchair boron nitride nanotubes (BNNTs) was investigated by molecular dynamics (MD) simulations. The investigated system included a BNNT embedded between two graphene sheets as a membrane. This membrane was immersed into a water box containing nitrate ions. For the removal of nitrates, an external pressure was applied to the system. Six types of armchair BNNTs with different diameter including (4,4), (5,5), (6,6), (7,7), (8,8) and (9,9) BNNTs were used. The simulation results showed that the BNNTs with different diameters acted differently relative to permeation of nitrate ions and water molecules. The permeation of nitrate ions through the BNNTs was dependent on the applied pressures and the diameter of nanotubes. The flow rate of water through BNNTs was increased by increasing the diameter of the nanotubes.
Keywords: Boron nitride nanotube; Graphene; Nanostructured membrane; Nitrate.
2
1. Introduction Nitrate ion contamination is made at the nitrification state in nitrogen cycle and is a common ground source of water pollutant resulting from industrial and natural sources. Nitrate ion is a highly soluble form of nitrogen and is a common groundwater pollutant [1]. Natural sources of nitrate are atmospheric precipitation, local mineral deposits such as potassium nitrate and farm animal wastes. Although nitrate ion is a nontoxic ion, it can be the precursor of many carcinogens through reducing to nitrite ion by bacteria [2]. High levels of nitrate contamination are found in shallow groundwater that is used as a source of drinking water [3]. It is known that the levels of nitrate contaminations exceeding 10 mg/L limit is associated with certain health problems. Nitrate ion is relatively nontoxic to adults but it can be fatal to infants under six months of age. In the exposed infants, nitrate is reduced to nitrite, which combines with hemoglobin in the blood to form methemoglobin, and leads to blue baby syndrome [1, 4]. Also nitrates can be combined with amines to form nitrosamines. It is one of the potential carcinogens in human body. Overall, the long-term effect of high nitrate drinking water consumption is unknown, but there are some potential risks against health caused by nitrite. Therefore, removal of nitrate contaminations from water is important, because drinking water supply is one of the main concerns in the world and the drinking of low quality water causes health hazards in the community. On the other hand, nitrate is a stable and highly soluble ion and its co-precipitation or adsorption is difficult. Concerning the nitrate properties, the removal of nitrate from water with conventional water treatment methods such as lime softening and filtration is a challenging problem. Different methods were used to remove nitrate from water; i.e. chemical and electrochemical reduction, ion exchange, biological removal, and reverse osmosis [5, 6]. However, all these methods aren’t applicable in every situation [7, 8]. Up to the present time, many researches have been developed for industrial applications 3
by the removal of nitrate ion from water and separation processes applying nanostructure membranes [9, 10]. One of these nanostructures is single wall boron nitrite nanotube (SWBNNT). BNNTs were first theoretically predicted [11], and soon after its prediction, they were successfully experimentally synthesized [12]. In recent years, most of the studies have been done on the synthesis of BNNTs [13-16]. The tubular structure of these nanotubes was denoted by a pair of indexes (m, n). The m and n are the number of unit vectors of 2D hexagonal boron nitrite (h-BN) sheet, which connects the two crystallographic equivalent sites on the h-BN sheet. Depending on the values of these two indexes, there are three types of BNNTs structures including armchair (m=n), zigzag (m=0), and chiral (m ≠n) nanotubes. Scientists are using BNNTs due to their properties [17-19]. One of the main characteristics of BNNTs is their ion selective property; therefore, they have potential uses in the purification industries. Up to date, BNNTs were used as ion-selective devices [20-24]. The selectivity of BNNTs was reported by Won and coworkers. They used a (10, 10) BNNT to study its ionic selectivity relative to chloride and potassium ions. They indicated that this nanotube could separate chloride ions [20]. Azamat et al. performed molecular dynamics (MD) simulations to investigate the separation of heavy metals from water using BNNTs. Their results showed that the (7,7) and (8,8) BNNTs were exclusively selective to cations and anions [25]. In the other work, Chen has confirmed that BNNTs had interactions with proteins and therefore these nanotubes can be used in biocompatible materials [26]. Nanok and coworkers investigated the structure and dynamics of water molecules confined in BNNTs by theoretical methods [27]. To the best of our knowledge, no study has been reported about the removal of nitrate ions from aqueous solution using the BNNTs. Therefore, in this work, we studied the removal of nitrate ions from aqueous solutions using armchair BNNTs as a membrane under induced pressure using MD simulation method. This method is one of the main fields of 4
nanotechnology that can be used for design, production and scale up of various processes.
2. Simulation methodology and details We used six types of armchair BNNTs with a length of 21 Å and different diameters including (4,4), (5,5), (6,6), (7,7), (8,8), and (9,9) BNNTs as shown in Figure 1. Density functional theory method was used for a full geometric optimization of the electronic ground state of these BNNTs and sodium nitrate. These calculations were carried out by GAMESS package [28] at the B3LYP level of theory using 6-311G basis sets. Partial charges and Lennard-Jones parameters for all type of atoms are summarized in Table 1. The simulation box for all runs was 3×3×8 nm3. As shown in Figure 2, an armchair BNNT is embedded between two graphene sheets in the center of simulation cell. The whole system is immersed in an aqueous solution of sodium nitrate. The BNNT and graphene sheets were fixed during the simulation time. Approximately 1650 water molecules and 10 nitrate ions were in the simulation box. The long range interactions and the short range interactions for atomic species were described with the Coulomb potentials (UC) and the Lennard-Jones potential (Uvdw), respectively. The particle mesh Ewald (PME) method [29] was used to calculate the long range electrostatic interactions. Van der Waals interactions were truncated with a 12 Å spherical cutoff. The cross interaction Lennard-Jones parameters between fragments, ij and
ij , were calculated by the Lorenz-Berthelot mixing rules: ij
where
i j 2
and ij i j
(1)
i , j , i and j are the Lennard-Jones parameters for interactions occurring
between fragments i and j, respectively [30]. The potential energy (U e) of the intermolecular 5
interactions is given by the sum of Uc and Uvdw, as follow:
12 6 ij ij U e = U c + U vdw = + 4 ij - 4πε 0 rij rij rij q i .q j
(2)
where qi and qj are the partial charges assigned to atoms i and j; rij is the distance between species i and j. The interaction parameters of water-BNNT, water-ions and ions-BNNT were derived using the Lorentz-Berthelot combining rules. The MD simulations were done using the NAMD 2.9 program [31] with a 1 fs time step, similar to the previous reports [32-40]. Also, all data analysis were carried out using the VMD 1.9.2 [41]. To represent water molecules, the TIP3P model [42] was employed. Parameters for the graphene were taken as the parameters for sp2like aromatic carbons in the CHARMM27 force field [43, 44] and BNNTs parameters were taken from Azamat et al. [45]. For the parameterization of nitrate ions, the method of Mayne et al. [46] were used. This method is a rapid parameterization method of small molecules using the force field toolkit in VMD [46]. Parameters obtained by this method correspond with other parameters in the scientific literature (see Table 1). The system was minimized with NAMD using 500000 minimization steps at 0 K, and equilibrated for 100000 MD steps via an NVT ensemble at 298 K. Then 5 ns MD simulations were performed for analysis with VMD. The Langevin dynamics method [47] was used to keep the temperature at 298 K. Pressure-driven membrane processes use pressure difference between the water to be treated and a permeate side as the driving force to transport water contaminations through the membrane system. For the separation of nitrate ions, pressure is needed to be applied to the system. For this purpose, a previously established method established by Zhu et al. was used in our system [48, 49]. This method has been used in many works [50-52]. In this method, applied 6
pressure exerted to the selected region of system, as the applied constant force as Eq. (3):
P
n.F A
(3)
where ΔP is the pressure (Pa), n is the number of water molecules in the selected region, F (pN) is the applied force, and A (m2) is the area of the system. The force was applied to the oxygen atom of water molecules in a selected region of the system. The region is within a fixed distance of approximately 0.85 nm from the left or right boundary of the system. These forces cause a pressure gradient through the BNNTs. The applied pressure was up to 200 MPa and it was applied to approximately 540 water molecules.
3. Results and discussion In this work, MD simulations technique was used to investigate the removal of nitrate ions using armchair BNNTs. Six types of armchair BNNTs were used and in each case, the passage or non-passage of water and nitrate were investigated. The results show that in the case of the (4,4) BNNT, due to its small diameter, water molecules and nitrate ions cannot pass through it. Therefore, this type of nanotube is not suitable for the separation of contaminants from water. Water molecules could pass through (5,5) BNNT and larger ones, but nitrate ions could not pass across the (5,5) and (6,6) BNNTs and remained at one side of them. Due to these characteristics of the (5,5) and (6,6) BNNTs, these nanotubes are suitable if we want to keep nitrate ions on one side of the membrane. However, the flow rate of water is low in these types of nanotubes, due to the single file structure of water molecules inside them. In the large BNNTs ((7,7), (8,8) and (9,9)), nitrate ions as well as water molecules can pass through them with different ratios.
7
3.1. Water structure properties Each water molecule can form four hydrogen bonds with other neighboring water molecules in bulk system, but due to space restrictions, this characteristic of water molecules is different from bulk water inside nanotubes. Moreover, this arrangement of water molecules changes with the permeation of nitrate ions through nanotubes. Figure 3 shows different arrangement of water molecules inside the investigated BNNTs. To illustrate this phenomenon, we used the radial distribution function (RDF) parameter between BNNTs and inner water molecules. This parameter is defined as the probability of finding an atom or molecule at a distance of r away from a given reference atom or molecule. The RDF between BNNT-inner water molecules is shown in Figure 4. The characteristics of peak varied in each BNNT due to different arrangements of inner water molecules. As can be seen in Figure 3, in the case of (5,5) and (6,6) BNNTs, arrangement of inner water molecules is as a single structure file which is shown with a peak in their RDFs. The water molecules arrangement is changed to the spiral mode in the (7,7) and (8,8) BNNTs. This change in the structure of inner water molecules is due to the increase in the size of BNNTs diameter. This structure was confirmed via two peaks in RDF. Finally, in the (9,9) BNNT, both the single file structure and spiral mode were detected together. Accordingly, its RDF displayed three peaks; a peak for the single file structure and two peaks for the spiral structure of water molecules.
3.2. Nitrate permeation The number of nitrate ions and water molecules passing across the BNNTs was obtained from the simulation results. With increasing applied pressures to the system, the number of molecules and ions passing across nanotubes was increased. However, due to the size of nitrate ions, passage was not possible through the (4,4), (5,5) and (6,6) BNNTs. But, nitrates are able to pass through the other larger nanotubes (Figure 5). Also water molecules have 8
similar behavior in the case of (4,4) BNNT and do not pass through it. By increasing the applied pressure and diameter of the BNNTs, the number of passing water molecules was increased as shown in Figure 6. As previously mentioned nitrate ions passed through different large BNNTs by applying pressure to the system. Meanwhile time is an important parameter to remove them. With increasing the applied pressure to the system, removal time of nitrates was decreased. Furthermore, this parameter has been downtrended with increasing the size of the BNNTs. In this work, the retention time of nitrate ions, i.e., the time of passing one nitrate across the BNNT, was calculated. The MD results showed that the retention time of nitrates depends on the applied pressures. As shown in Figure 7, the retention time of ions decreases with increasing both the diameter of BNNT and applied pressure. It can be argued that it is easier for the nitrate to pass through the large BNNTs at high pressures. Actually, low and high pressures can affect in the passing time of one ion through the considered BNNTs. Regarding to low pressure, there was an overlap between the passing time of ions; however, in case of a high pressure, this overlap did not exist. In other words, one nitrate enters into BNNT and it doesn’t exit until a second ion enters the nanotube in low pressure; however, in a high pressure, nitrates can exit the nanotube without any help. During the passage of water molecules through the nanotubes, always some water molecules remain inside the nanotube (inner water). Figure 8 shows the number of inner water molecules based on the applied pressures. The number of inner water molecules was slightly changed with increasing the applied pressure. But, this parameter increases by increasing the diameter of BNNTs. Accordingly, the number of hydrogen bonds between the inner water molecules was also raised by increasing the diameter of BNNTs (Figure 9). Also formation of hydrogen bonds between inner water molecules and nitrate ions passing through nanotube was consistent with previous justifications. With increasing the diameter of
9
BNNTs, number of inner water molecules and nitrates were increased. Consequently, the number of hydrogen bonds between them was increased (Figure 10), but the increasing applied pressures, did not significantly impact on this trend.
3.3. Density profile The fluid structure within the nanotube can be best characterized by the density profile. Figure 11 illustrates the density profile of nitrate ions in the BNNTs under different applied pressures. This parameter was obtained from trajectory files of MD simulations in the pressure of 10 MPa for the (8,8) BNNT and 200 MPa for the (6,6) and (9,9) BNNTs. As previously mentioned nitrate ions did not pass across BNNTs with small diameters, such as (5,5) and (6,6) nanotubes, and remain on one side of the cell (blue curve), even at high pressures. In the case of (9,9) BNNT, all nitrates were removed from polluted water (black curve) and finally in the (8,8) BNNT under low pressure (10 MPa), some nitrates were removed from polluted water (pink curve). The non-permeation of nitrate from small BNNT was happened under all ranges of applied pressures. But in the case of (8,8) BNNT, as well as (9,9) BNNT, a full removal of nitrates was happened, in high pressures with different retention times (Figure 7). This time for a specified pressure (such as 200 MPa) for the (9,9) nanotube was less than that of (8,8) nanotube due to easier passage nitrate ions.
4. Conclusion BNNTs with unique physical and chemical properties have a variety of potential applications in nanotechnology especially for water treatment industry. In this research, we studied the removal of nitrate ion using armchair BNNTs embedded between two graphene sheets by MD simulations technique. The separation of nitrate ion from water using BNNTs was happened by applying pressure to the system. The BNNTs with different diameters can 10
remove nitrate ion from aqueous solution. Nitrate ions and water molecules are passed through the large BNNTs with different retention times. In contrast, in the case of small BNNTs, such as (5,5) and (6,6) BNNTs, only water molecules are passed through them, and nitrate ions are filtered. Eventually, it can be maintained that our findings can be used for designing new membranes applicable in water desalination technology.
Acknowledgments Authors thank the University of Tabriz for the support provided. We also acknowledge the support of Iran Science Elites Federation. Jafar Azamat as a postdoc researcher gratefully acknowledges use of the services and facilities of the University of Tabriz.
References [1] A. Kapoor, T. Viraraghavan, Nitrate removal from drinking water-Review, J. Environ. Eng., 123 (1997) 371-380. [2] A.C. Kite-Powell, A.K. Harding, Nitrate contamination in oregon well water: geologic variability and the public’s perception, JAWRA, 42 (2006) 975-987. [3] O. Fenton, K.G. Richards, L. Kirwan, M.I. Khalil, M.G. Healy, Factors affecting nitrate distribution in shallow groundwater under a beef farm in South Eastern Ireland, J. Environ. Manage., 90 (2009) 3135-3146. [4] E.F. Winton, R.G. Tardiff, L.J. McCabe, Nitrate in drinking water, JAWRA, 63 (1971) 95-98. [5] K. Kesore, F. Janowski, V.A. Shaposhnik, Highly effective electrodialysis for selective elimination of nitrates from drinking water, J. Membr. Sci., 127 (1997) 17-24. [6] Biological Denitrification of Water, J. Environ. Eng., 115 (1989) 930-943. [7] A.S. Koparal, Ü.B. Öğütveren, Removal of nitrate from water by electroreduction and electrocoagulation, J. Hazard. Mater., 89 (2002) 83-94. [8] G.E. Dima, A.C.A. de Vooys, M.T.M. Koper, Electrocatalytic reduction of nitrate at low concentration on coinage and transition-metal electrodes in acid solutions, J. Electroanal. Chem., 554–555 (2003) 15-23. 11
[9] J.J. Sardroodi, J. Azamat, A. Rastkar, N.R. Yousefnia, The preferential permeation of ions across carbon and boron nitride nanotubes, Chem. Phys., 403 (2012) 105-112. [10] K. Dhungana, R. Pati, Boron nitride nanotubes for spintronics, Sensors, 14 (2014) 17655. [11] A. Rubio, J.L. Corkill, M.L. Cohen, Theory of graphitic boron nitride nanotubes, Phys. Rev. B: Condens. Matter, 49 (1994) 5081-5084. [12] N.G. Chopra, R.J. Luyken, K. Cherrey, V.H. Crespi, M.L. Cohen, S.G. Louie, A. Zettl, Boron nitride nanotubes, Science, 269 (1995) 966-967. [13] D. Seo, J. Kim, S.-H. Park, Y.-U. Jeong, Y.-S. Seo, S.-H. Lee, J. Kim, Synthesis of boron nitride nanotubes using thermal chemical vapor deposition of ball milled boron powder, J. Ind. Eng. Chem., 19 (2013) 1117-1122. [14] P. Ahmad, M.U. Khandaker, Y.M. Amin, Z.R. Khan, Synthesis of boron nitride microtubes and formation of boron nitride nanosheets, Mater. Manuf. Processes, 30 (2014) 184-188. [15] A. Pan, Y. Chen, Large-scale fabrication of boron nitride nanotubes with high purity via solid-state reaction method, Nanoscale Res. Lett., 9 (2014) 1-6. [16] P. Ahmad, M.U. Khandaker, Y.M. Amin, Synthesis of boron nitride nanotubes by argon supported thermal chemical vapor deposition, Physica E, 67 (2015) 33-37. [17] D. Golberg, Y. Bando, C.C. Tang, C.Y. Zhi, Boron nitride nanotubes, Adv. Mater., 19 (2007) 2413-2432. [18] E.C. Anota, G. Cocoletzi, J.F.S. Ramírez, Armchair BN nanotubes—levothyroxine interactions: a molecular study, J. Mol. Model., 19 (2013) 4991-4996. [19] E. Chigo Anota, G. Cocoletzi, First-principles simulations of the chemical functionalization of (5,5) boron nitride nanotubes, J. Mol. Model., 19 (2013) 2335-2341. [20] C.Y. Won, N.R. Aluru, A chloride ion-selective boron nitride nanotube, Chem. Phys. Lett., 478 (2009) 185-190. [21] D. Tang, D. Kim, Temperature effect on ion selectivity of potassium and sodium ions in solution, Chem. Phys., 428 (2014) 14-18. [22] H. Ebro, Y.M. Kim, J.H. Kim, Molecular dynamics simulations in membrane-based water treatment processes: A systematic overview, J. Membr. Sci., 438 (2013) 112-125. [23] A. Khosrozadeh, Q. Wang, V.K. Varadan, Molecular simulations on separation of atoms with carbon nanotubes in torsion, Comput. Mater. Sci, 81 (2014) 280-283. [24] J. Azamat, J.J. Sardroodi, Ion and water transport through (7, 7) and (8, 8) carbon and boron nitride nanotubes of different electric fields: a molecular dynamics simulation study, J. 12
Comput. Theor. Nanosci., 11 (2014) 2611-2617. [25] J. Azamat, A. Khataee, S. Joo, Separation of a heavy metal from water through a membrane containing boron nitride nanotubes: molecular dynamics simulations, J. Mol. Model., 20 (2014) 1-9. [26] X. Chen, P. Wu, M. Rousseas, D. Okawa, Z. Gartner, A. Zettl, C.R. Bertozzi, Boron nitride nanotubes are noncytotoxic and can be functionalized for interaction with proteins and cells, J. Am. Chem. Soc., 131 (2009) 890-891. [27] T. Nanok, N. Artrith, P. Pantu, P.A. Bopp, J. Limtrakul, Structure and dynamics of water confined in single-wall nanotubes, J. Phys. Chem. A, 113 (2008) 2103-2108. [28] M.W. Schmidt, K.K. Baldridge, J.A. Boatz, S.T. Elbert, M.S. Gordon, J.H. Jensen, S. Koseki, N. Matsunaga, K.A. Nguyen, S. Su, a. et, General atomic and molecular electronic structure system, J. Comput. Chem., 14 (1993) 1347-1363. [29] G. Ciccotti, D. Frenkel, I.R. McDonald, Simulation of liquids and solids: Molecular dynamics and monte carlo methods in statistical mechanics North Holland, New York, 1987. [30] L. Viola, S. Lloyd, Dynamical suppression of decoherence in two-state quantum systems, Phys. Rev. A, 58 (1998) 2733-2744. [31] L. Kalé, R. Skeel, M. Bhandarkar, R. Brunner, A. Gursoy, N. Krawetz, J. Phillips, A. Shinozaki, K. Varadarajan, K. Schulten, NAMD2: Greater scalability for parallel molecular dynamics, J. Comput. Phys., 151 (1999) 283-312. [32] J. Azamat, A. Khataee, S.W. Joo, Functionalized graphene as a nanostructured membrane for removal of copper and mercury from aqueous solution: a molecular dynamics simulation study, J. Mol. Graphics Modell., 53 (2014) 112-117. [33] J. Azamat, J.J. Sardroodi, A. Rastkar, Water desalination through armchair carbon nanotubes: a molecular dynamics study, RSC Adv., 4 (2014) 63712-63718. [34] J. Azamat, A. Khataee, S.W. Joo, Molecular dynamics simulation of trihalomethanes separation from water by functionalized nanoporous graphene under induced pressure, Chem. Eng. Sci., 127 (2015) 285-292. [35] J. Azamat, A. Khataee, S.W. Joo, Removal of heavy metals from water through armchair carbon and boron nitride nanotubes: a computer simulation study, RSC Adv., 5 (2015) 25097-25104. [36] A. Khataee, J. Azamat, G. Bayat, Separation of nitrate ion from water using silicon carbide nanotubes as a membrane: Insights from molecular dynamics simulation, Comput. Mater. Sci, 119 (2016) 74-81. [37] J. Azamat, A. Khataee, F. Sadikoglu, Separation of carbon dioxide and nitrogen gases 13
through modified boron nitride nanosheets as a membrane: insights from molecular dynamics simulations, RSC Adv., 6 (2016) 94911-94920. [38] J. Azamat, A. Khataee, S.W. Joo, Separation of copper and mercury as heavy metals from aqueous solution using functionalized boron nitride nanosheets: A theoretical study, J. Mol. Struct., 1108 (2016) 144-149. [39] J. Azamat, A. Khataee, S.W. Joo, Molecular dynamics simulations of trihalomethanes removal from water using boron nitride nanosheets, J. Mol. Model., 22 (2016) 82. [40] J. Azamat, Functionalized graphene nanosheet as a membrane for water desalination using applied electric fields: Insights from molecular dynamics simulations, J. Phys. Chem. C, 120 (2016) 23883-23891. [41] W. Humphrey, A. Dalke, K. Schulten, VMD: Visual molecular dynamics, J. Mol. Graphics, 14 (1996) 33-38. [42] D.J. Price, C.L. Brooks, A modified TIP3P water potential for simulation with Ewald summation, J. Chem. Phys., 121 (2004) 10096-10103. [43] S.E. Feller, A.D. MacKerell, An improved empirical potential energy function for molecular simulations of phospholipids, J. Phys. Chem. B, 104 (2000) 7510-7515. [44] J.B. Klauda, B.R. Brooks, A.D. MacKerell, R.M. Venable, R.W. Pastor, An ab initio study on the torsional surface of alkanes and its effect on molecular simulations of alkanes and a DPPC bilayer, J. Phys. Chem. B, 109 (2005) 5300-5311. [45] J. Azamat, J. Sardroodi, The permeation of potassium and chloride ions through nanotubes: a molecular simulation study, Monatsh Chem, 145 (2014) 881-890. [46] C.G. Mayne, J. Saam, K. Schulten, E. Tajkhorshid, J.C. Gumbart, Rapid parameterization of small molecules using the force field toolkit, J. Comput. Chem., 34 (2013) 2757-2770. [47] X. Wu, B.R. Brooks, Self-guided Langevin dynamics simulation method, Chem. Phys. Lett., 381 (2003) 512-518. [48] F. Zhu, E. Tajkhorshid, K. Schulten, Pressure-induced water transport in membrane channels studied by molecular dynamics, Biophys. J., 83 (2002) 154-160. [49] F. Zhu, E. Tajkhorshid, K. Schulten, Theory and simulation of water permeation in aquaporin-1, Biophys. J., 86 (2004) 50-57. [50] B. Corry, Designing carbon nanotube membranes for efficient water desalination, J. Phys. Chem. B, 112 (2008) 1427-1434. [51] X. Gong, J. Li, H. Lu, R. Wan, J. Li, J. Hu, H. Fang, A charge-driven molecular water pump, Nat. Nanotechnol., 2 (2007) 709-712. 14
[52] J. Goldsmith, C.C. Martens, Pressure-induced water flow through model nanopores, Phys. Chem. Chem. Phys., 11 (2009) 528-533.
15
Tables Table 1. Partial charges (q) and Lennard-Jones parameters (ε and σ) for all type of atoms. Type of atom
q(℮)
ε (kJ/mol)
σ (Å)
B (BNNT)
+0.4
0.393
3.453
N (BNNT)
-0.4
0.602
3.365
N (nitrate)
+0.95
0.669
1.604
O (nitrate)
-0.65
0.711
1.675
16
Figures
Figure 1. Schematic design of boron nitride nanotubes considered in this research. BNNT (4,4), (5,5), (6,6), (7,7), (8,8), and (9,9).
17
Figure 2. A snapshot of the simulated box with 3×3×8 nm3 size (Black: carbon atoms of graphene sheets; blue: nitrogen atoms of nanotube and nitrate ion; pink: boron atoms of nanotube; yellow: sodium ion; red: oxygen atoms of water and nitrate ion; and white: hydrogen atoms of water).
18
Figure 3. Arrangement of inner water molecules in studied BNNTs. The structure of inner water molecules changes in different nanotubes.
19
35 BNNT(5,5)
BNNT(6,6)
30
BNNT(7,7)
RDF water-BNNT
25
BNNT(8,8) BNNT(9,9)
20 15 10 5 0 0
2
4
6
8
r (Å) Figure 4. RDFs of BNNT- inner water for all systems in the simulation cell.
20
10
Number of nitrates passing through BNNTs
BNNT(9,9)
25
BNNT(8,8) BNNT(7,7) 20
15
10
5
0 0
50
100 Pressure (MPa)
150
200
Figure 5. The number of nitrate ions passing through the (7,7), (8,8) and (9,9) BNNTs. Lines were obtained from a linear regression. Each data point represents the average of five sets of simulations.
21
Number of waters passing through BNNTs
3000 BNNT(9,9) BNNT(8,8)
2500
BNNT(7,7) BNNT(6,6)
BNNT(5,5)
2000
1500
1000
500
0 0
50
100 Pressure (MPa)
150
200
Figure 6. The number of water molecules passing through the BNNTs. Lines were obtained from a linear regression. Each data point represents the average of five sets of simulations.
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0.7 BNNT(7,7)
0.6 BNNT(8,8) BNNT(9,9)
Retention time (ns)
0.5 0.4 0.3 0.2 0.1 0 0
50
100 Pressure (MPa)
150
200
Figure 7. Retention time of nitrate ions across different BNNTs under various applied pressures.
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Figure 8. Number of inner water molecules under various applied pressures. Each data point represents the average of five sets of simulations.
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Figure 9. Number of hydrogen bonds between inner water-water molecules under various applied pressures. Each data point represents the average of five sets of simulations.
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Number of hydrogen bonds between water-nitrate inside BNNTs
4
3
2
BNNT(9,9)
1
BNNT(8,8) BNNT(7,7)
0 0
50
100 Pressure (MPa)
150
200
Figure 10. Number of hydrogen bonds between inner water and nitrates in the (7,7), (8,8) and (9,9) BNNTs under various applied pressures. Lines were obtained from a linear regression. Each data point represents the average of five sets of simulations.
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0.3 BNNT(9,9) BNNT(8,8)
Density profile
BNNT(6,6)
0.2
0.1
0 -40
-30
-20
-10 0 10 Axial position (Å)
20
30
40
Figure 11. Density profile of nitrate ions in three type of the BNNTs in z direction of simulation cell system (blue: none of nitrates are passed through the (6,6) BNNT under 200 MPa pressure; pink: some of nitrates are removed from water using the (8,8) BNNT under 10 MPa pressure; and black: all nitrates are removed from water using the (9,9) BNNT under 200 MPa pressure).
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Graphical Abstract
A snapshot of the simulated system, containing boron nitride nanotubes, graphene, ions and water molecules. (Black: graphene sheets; blue: nitrogen atoms of nanotube and nitrate ion; pink: boron atoms of nanotube; yellow: sodium ion; red: oxygen atoms of water and nitrate ion; and white: hydrogen atoms of water). Nitrate and sodium ions are displayed with van der Waals modes.
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Research Highlights:
BNNTs have the ability to remove nitrate. Amounts of nitrate removal in various BNNTs were different. The removal of nitrate was dependent on the applied pressures.
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