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Graphene-based materials have aroused great interest for their potential applications in water desalination and purification membranes attributed to their ultrathin thickness, high mechanical strength, and anti-foiling properties. Reverse osmosis (RO) technology is currently the most progressive, energy-saving and efficient separation technology by membranes, therefore the new materials with high strength, strong pollution resistance and excellent performance are urgently needed. The ability of porous graphene to serve as a kind of novel advanced RO membrane is due to two major potential strengths of this atomically thin two-dimensional material, i.e., ultrahigh permeability and super selectivity. Thus, the reverse osmotic properties of the porous graphene membranes should be further investigated theoretically. In this paper, classical molecular dynamics method is used to investigate the reverse osmosis characteristics of brine in hydrogenated porous graphene reverse osmosis membrane. The results show that the water permeation rate increases with the driving force, pore size and temperature increasing, for the pore diameter larger than the hydration radius. The ion rejection rate decreases with the driving force and temperature increasing. Interestingly, as the porous graphene moves in the tangential direction to perform a shearing process, the interception rate of the salt ions can be effectively improved and the concentration difference polarization phenomenon can be reduced with the tangential velocity increasing, although the water flux decreases slightly. The influence mechanism of each parameter on permeability and on water flux are explored by analyzing the hydrogen bond distribution, the ionic hydration in feed solution, and the energy barrier of the water molecules in penetrating process. In order to further evaluate the effects of various parameter changes on the benefits of reverse osmosis membranes, both the selectivity and permeability are calculated to evaluate the tradeoff between permeability and selectivity, indicating that the increase of the pore diameter can obtain both high permeability and selectivity under the shearing circumstance of the membrane. The research results in this paper will provide a theoretical understanding of porous graphene-based desalination membrane and also may be helpful in designing the shearing graphene-based water filtration devices.
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Keywords:
- porous graphene /
- reverse ssmosis /
- hydrogen bond /
- molecular dynamics
[1] Boretti A, Al-Zubaidy S, Vaclavikova M, Al-Abri M, Castelletto S, Mikhalovsky S 2018 npj Clean Water 1 1
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Google Scholar
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Google Scholar
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Google Scholar
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Google Scholar
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Google Scholar
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Google Scholar
[26] Zhang Z Q, Zhang H, Zheng Y, Wang L, Wang J 2008 Phys. Rev. B 78 035439
Google Scholar
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Google Scholar
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Google Scholar
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Google Scholar
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Google Scholar
[30] Pendergast M M, Hoek E M V 2011 Energy Environ. Sci. 4 1946
Google Scholar
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图 1 (a) 压力驱动作用下以氢化多孔石墨烯为反渗透膜的反渗透分子动力学模型图 (其中灰色球为反渗透膜中的碳原子, 中间的红色、白色、紫色、绿色球分别代表盐水中的氧原子、氢原子、钠离子、氯离子, 左侧棕色球是用来提供驱动压力的单层石墨烯, 右侧粉色球是单层石墨烯挡板); (b) 氢化多孔石墨烯反渗透膜模型示意图(其中白色和黄色球分别表示带相同电量正电荷和负电荷的氢原子和碳原子, 其余灰色碳原子不带电)
Figure 1. (a) Molecular dynamics model for pressure-driven reverse osmosis by a hydrogenated porous graphene. The dark gray particles are carbon atoms of grapheme. The red, white, purple, and green spheres represent the oxygen atoms, hydrogen atoms, sodium ions, and chloride ions in the brine, respectively. The monolayer graphene at the left side is used to provide driving pressure, while the one at the right side is rigid boundary to confine the solvent. (b) A hydrogenated porous graphene reverse osmosis membrane model. The white and yellow particles are hydrogen and carbon atoms with the same positive and negative charges, respec-tively.
图 2 不同压力、温度、速度条件下孔径为1.2 nm的盐离子截留率和水通量的关系
Figure 2. Salt rejection versus water permeability for the porous grapheme with pore diameter of 1.2 nm under different pressure, temperature and shearing speed conditions.
图 3 在盐水区距离石墨烯膜1 nm范围内盐离子占总盐离子的占比随速度的变化; (b) 当剪切速度为400 m/s时, 盐水区氢键和速度的z向分布
Figure 3. (a) Proportion ratio of salt ions in the brine zone to the total salt ion in the range of 1 nm of the membrane; (b) the z-directional distribution of hydrogen bonds (HB) and velocity in brine zone when the shearing speed is 400 m/s.
图 4 盐水区平均每个水分子氢键数和端口水分子数及其氢键平均数的z向分布关系图 (a) 在不同剪切速度下; (b) 在不同温度下
Figure 4. The z-directional distribution relationship between the number of hydrogen bonds per water molecule and the number of port water molecules and their hydrogen bond average in the feed solution: (a) Different shearing speeds; (b) different temperatures.
图 5 (a) 驱动力为200 MPa无剪切作用时, 水分子沿z轴方向转移的能障随温度的变化; (b) 驱动力为200 MPa时, 水分子沿z轴方向转移的能障随剪切速度的变化
Figure 5. (a) The PMF of water molecules along the z-axis at different temperatures for the membrane without shearing; (b) the PMF of water molecules along the z-axis for different shear speeds. The driving pressure in feed solution is 200 MPa.
图 6 (a) 不同驱动压力下, 水分子和盐离子径向分布函数G(r); (b) 不同温度下, 水分子和盐离子径向分布函数G(r)
Figure 6. (a) Radial distribution function G(r) of water molecules and salt ions under different driving pressures; (b) radial distri-bution function G(r) of water molecules and salt ions at different temperatures.
图 7 (a)不同温度和(b)不同剪切速度下的水合状态图, 其中包含第一水合层水分子平均数(黑色)、第一水合层水分子氢键平均数(红色)、第二水合层水分子平均数(蓝色)和第二水合层(紫色)水分子氢键平均数
Figure 7. (a) Hydration state diagram at different temperatures; (b) hydration state diagram at different shear velocities. Black square: The number of water molecules in first hydration shell. Red square: HB in first hydration shell. Blue square: The number of water molecules in second hydration shell. Purple square: HB in second hydration shell.
图 8 (a) 不同驱动力、温度、速度条件下, 孔径为1.6 nm的氢化多孔石墨烯盐离子截留率和水通量的关系; (b) 在温度为298 K、剪切速度为0的条件下, 孔径为0.82 nm的不同驱动力的水通量
Figure 8. (a) Salt rejection versus water permeability for pore diameter of 1.6 nm under different conditions of pressure, temperature and speed; (b) water permeability as a function of driving pressure for the pore diameter of 0.82 nm at the temperature of 298 K and the shearing speed of 0.
表 1 LJ势能参数
Table 1. LJ potential parameters.
Elements C (sp2) CCH HCH Ow Hw Na+ Cl– ε/kcal·mol–1 0.0859 0.046 0.0301 0.16275 0 0.1684 0117 σ/Å 3.3997 2.985 2.42 3.16435 0 2.2589 5.1645 q/e 0 –0.115 0.115 –1.0484 0.5252 1 –1 
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表 2 孔径为1.2 nm下选择性和渗透性效益权衡
Table 2. Trade-offs between selectivity and permeability with pore diameter of 1.2 nm.
τ = 200 MPa, v = 0 T = 298 K, v = 0 T = 298 K, τ = 200 MPa T/K τ/MPa v/m·s–1 275 298 325 350 100 150 250 300 100 200 300 400 Q 0.72 0.84 0.87 0.88 0.76 0.97 0.87 0.78 0.88 0.83 0.84 0.83
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表 3 孔径为1.6 nm下选择性和渗透性效益权衡
Table 3. Trade-offs between selectivity and permeability with pore diameter of 1.6 nm.
τ = 200 MPa, v = 0 T = 298 K, v = 0 T = 298 K, τ = 200 MPa T/K τ/MPa v/m·s–1 275 298 325 350 100 150 250 300 100 200 300 400 Q 0.65 0.73 0.70 0.69 0.96 0.85 0.66 0.61 0.63 0.65 0.60 0.60
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[1] Boretti A, Al-Zubaidy S, Vaclavikova M, Al-Abri M, Castelletto S, Mikhalovsky S 2018 npj Clean Water 1 1
Google Scholar
[2] Mehrdad M, Moosavi A 2019 Polymer 175 310
Google Scholar
[3] Kim J, Park K, Yang D R, Hong S 2019 Appl. Energy 254 113652
Google Scholar
[4] Greenlee L F, Lawler D F, Freeman B D, Marrot B, Moulin P 2009 Water Res. 43 2317
Google Scholar
[5] Cohen-Tanugi D, Grossman J C 2012 Nano Lett. 12 3602
Google Scholar
[6] Werber J R, Osuji C O, Elimelech M 2016 Nat. Rev. Mater. 1 1
Google Scholar
[7] Sun P, Wang K, Zhu H 2016 Adv. Mater. 28 2287
Google Scholar
[8] Surwade S P, Smirnov S N, Vlassiouk I V, Unocic R R, Veith G M, Dai S, Mahurin S M 2015 Nat. Nanotechnol. 10 459
Google Scholar
[9] Xu P T, Yang J X, Wang K S, Zhou Z, Shen P W 2012 Sci. Bull. 57 2948
Google Scholar
[10] Plimpton S 1995 J. Comput. Phys. 117 1
Google Scholar
[11] Azamat J 2016 Phys. Chem. Chem. Phys. C 120 23883
Google Scholar
[12] Azamat J, Khataee A, Joo S W 2015 Chem. Eng. Sci. 127 28
Google Scholar
[13] Yu T, Xu Z, Liu S, Liu H, Yang X 2018 J. Membr. Sci. 550 510
Google Scholar
[14] Wang Y, He Z, Gupta K M, Shi Q, Lu R 2017 Carbon 116 120
Google Scholar
[15] Li Y, Xu Z, Liu S, Zhang J, Yang X 2017 Comput. Mater. Sci. 139 65
Google Scholar
[16] Baker R W 2012 Membrane Technology and Applications (Vol. 3) (California Newark: John Wiley & Sons) pp15–96
[17] Zhang Z Q, Zhang F J, Liu Z, Cheng G G, Wang X D, Ding J N 2018 Nanomaterials (Basel) 8 805
Google Scholar
[18] Xu Q, Zhang W 2016 Adv. Carbon Nanostruct. 28 6391
Google Scholar
[19] Horn H W, Swope W C, Pitera J W, Madura J D, Dick T J, Hura G L, Teresa H G 2004 J. Chem. Phys. 120 9665
Google Scholar
[20] Hummer G, Rasaiah J C, Noworyta J P 2001 Nature 414 188
Google Scholar
[21] Xu H, Berne B J 2001 J. Phys. Chem. B 105 11929
Google Scholar
[22] Luzar A, Chandler D 1996 Phys. Rev. Lett. 76 928
Google Scholar
[23] Chen B, Ivanov I, Klein M L, Parrinello M 2003 Phys. Rev. Lett. 91 215503
Google Scholar
[24] Todorova T, Seitsonen A P, Hutter J, Kuo I F, Mundy C J 2006 J. Phys. Chem. B 110 3685
Google Scholar
[25] Zaidi S M J, Fadhillah F, Khan Z, Ismail A F 2015 Desalination 368 202
Google Scholar
[26] Zhang Z Q, Zhang H, Zheng Y, Wang L, Wang J 2008 Phys. Rev. B 78 035439
Google Scholar
[27] Xie M, Gray S R 2016 Sep. Purif. Technol. 167 6
Google Scholar
[28] Li T, Tu Q, Li S 2019 Desalination 451 182
Google Scholar
[29] 张忠强, 李冲, 刘汉伦, 葛道晗, 程广贵, 丁建宁 2018 67 056102
Google Scholar
Zhang Z Q, Li C, Liu H L, Ge D J, Cheng G G, Ding J N 2018 Acta Phys. Sin. 67 056102
Google Scholar
[30] Pendergast M M, Hoek E M V 2011 Energy Environ. Sci. 4 1946
Google Scholar
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