Journal of Molecular Modeling

, 25:280 | Cite as

Modeling water purification by an aquaporin-inspired graphene-based nano-channel

  • A. LohrasebiEmail author
  • T. Koslowski
Original Paper


Understanding the mechanism of water and particle transport through thin-film membranes is essential to improve the water permeability and the salt rejection rate of the purification progress. In this research, mimicking from the structure and operation of the aquaporin channel, graphene-based nano-channels were designed to be used as a water filter. The effects of variation of the channel’s main elements, such as the width of the bottleneck and charges attached to the channel on its efficiency, were investigated via molecular dynamics simulations. We observe that the water flow through the channel decreases by increasing the charge, while the ion rejection rate of the channel is enhanced. Moreover, we find that the geometry and shape of the bottleneck part of the channel can affect the channel water flow and its selectivity. Finally, the pressure and the flow velocity in the channel were considered by using finite element models, and the results indicate that they are high at the entrance of the channel. The outcomes of this study can be used to improve the molecular knowledge of water desalination, which might be helpful in designing more efficient membranes.

Graphical abstract

As the piston pushed the solution to pass through the nano-channel, positive and negative ions are remained in the first box, by sensing electric field generated from the attached charges to the bottleneck part of the channel. Atomistic structure of channel is shown in the right part of the figure and the generated electric field is shown in the left part of the figure.


Water desalination Aquaporin Graphene-based channel Molecular dynamics simulation 


Supplementary material

894_2019_4160_MOESM1_ESM.docx (614 kb)
ESM 1 (DOCX 614 kb)


  1. 1.
    Preston GM, Carroll TP, Guggino WB, Agre P (1992) Appearance of water channels in Xenopus oocytes expressing red-cell CHIP28 protein. Science 256:385–387CrossRefGoogle Scholar
  2. 2.
    Murata K, Mitsuoka K, Hirai T, Walz T, Agre P, Heymann JB, Engel A, Fujiyoshi Y (2000) Structural determinants of water permeation through aquaporin-1. Nature 407:599–605CrossRefGoogle Scholar
  3. 3.
    Tajkhorshid E, Nollert P, Jensen MØ, Miercke LJW, O’Connell J, Stroud RM, Schulten K (2002) Control of the selectivity of the aquaporin water channel family by global orientational tuning. Science 296:525–530CrossRefGoogle Scholar
  4. 4.
    Vidossich P, Cascella M, Carloni P (2004) Dynamics and energetic of water permeation through the aquaporin channel. Proteins 55:924–931CrossRefGoogle Scholar
  5. 5.
    Aponte-Santamaría C, Fischer G, Båth P, Neutze R, de Groot BL (2017) Temperature dependence of protein-water interactions in a gated yeast aquaporin. Sci. Rep. 7(1):4016CrossRefGoogle Scholar
  6. 6.
    Saboe PO, Rapisarda C, Kaptan S, Hsiao YS, Summers SR, Zorzi RD, Dukovski D, Yu J, de Groot BL, Kumar M, Walz T (2017) Role of pore-lining residues in defining the rate of water conduction by aquaporin-0. Biophys. J. 112(14):953–965CrossRefGoogle Scholar
  7. 7.
    de Groot BL, Grubmuller H (2001) Water permeation across biological membranes: mechanism and dynamics of aquaporin-1 and GlpF. Science 294:2353–2357CrossRefGoogle Scholar
  8. 8.
    Lohrasebi A, Rafii-Tabar H (2008) Computational modeling of an ion-driven nanomotor. Journal of Molecular Graphics and Modeling 27:116–123CrossRefGoogle Scholar
  9. 9.
    Gong X, Li J, Lu H, Wan R, Li J, Hu J, Fang H (2007) A charge-driven molecular water pump. Nature 2:709–712Google Scholar
  10. 10.
    Chen M, Zang J, Xiao D, Zhang C, Liu F (2009) Nanopumping molecules via a carbon nanotube. Nano Res. 2:938–944CrossRefGoogle Scholar
  11. 11.
    Lohrasebi A, Feshanjerdi M (2012) A rotary nano ion pump: a molecular dynamics study. J. Mol. Model. 18:4191–4197CrossRefGoogle Scholar
  12. 12.
    Rikhtehgaran S, Lohrasebi A (2015) Water desalination by a designed nano filter of graphene-charged carbon nanotube: a molecular dynamics study. Desalination 365:176–181CrossRefGoogle Scholar
  13. 13.
    Surwade SP, Smirnov SN, Vlassiouk IV, Unocic RR, Veith GM, Dai S, Mahurin SM (2015) Water desalination using nanoporous single-layer graphene. Nat. Nanotechnol. 10:459–464CrossRefGoogle Scholar
  14. 14.
    Wu K, Chen Z, Li J, Li X, Xu J, Dong X (2017) Wettability effect on nanoconfined water flow. PNAS 114:3358–3363CrossRefGoogle Scholar
  15. 15.
    Cohen-Tanugi D, Grossman JC (2015) Nanoporous graphene as a reverse osmosis membrane: recent insights from theory and simulation. Desalination 366:59–70CrossRefGoogle Scholar
  16. 16.
    Sun P, Wang K, Zhu H (2016) Recent developments in graphene-based membranes: structure. Mass-Transport Mechanism and Potential Applications, Advanced Materials 28:2287–2310PubMedGoogle Scholar
  17. 17.
    Lohrasebi A, Rikhtehgaran S (2018) Ion separation and water purification by applying external electric field on porous graphene membrane. Nano Res. 11(4):2229–2236CrossRefGoogle Scholar
  18. 18.
    Cohen-Tanugi D, Lin LC, Grossman JC (2016) Multilayer nanoporous graphene membranes for water desalination. Nano Lett. 16:1027–1033CrossRefGoogle Scholar
  19. 19.
    Neek-Amal M, Lohrasebi A, Mousaei M, Radha B, Peeters FM (2018) Fast water flow through graphene nanocapillaries: a continuum model approach involving the microscopic structure of confined water. Appl. Phys. Lett. 113(8):083101–083106CrossRefGoogle Scholar
  20. 20.
    Kargar M, Khasheii F, Lohrasebi A (2018) Influence of electric fields on the efficiency of multilayer graphene membrane. J. Mol. Model. 24:241CrossRefGoogle Scholar
  21. 21.
    Qiu H, Zeng XC, Guo W (2015) Water in inhomogeneous nanoconfinement: coexistence of multilayered liquid and transition to ice nanoribbons. ACS Nano 9:9877–9884CrossRefGoogle Scholar
  22. 22.
    Joly L, Tocci G, Merabia S, Michaelides A (2016) Strong coupling between nanofluidic transport and interfacial chemistry: how defect reactivity controls liquid–solid friction through hydrogen bonding. J. Phys. Chem. Lett. 7(7):1381–1386CrossRefGoogle Scholar
  23. 23.
    Walther JH, Ritos K, Cruz-Chu ER, Megaridis CM, Koumoutsakos P (2013) Barriers to superfast water transport in carbon nanotube membranes. Nano Lett. 13(5):1910–1914CrossRefGoogle Scholar
  24. 24.
    Kargar M, Lohrasebi A (2019) Water flow modeling through the graphene-based nanochannel: theory and simulation. Phys. Chem. Chem. Phys. 21:3304–3309CrossRefGoogle Scholar
  25. 25.
    Chakraborty S, Kumar H, Dasgupta C, Maiti PK (2017) Confined water: structure, dynamics, and thermodynamics. Acc. Chem. Res 50(9):2139–2146CrossRefGoogle Scholar
  26. 26.
    Giri AK, Teixeira F, Natália M, Cordeiro DS (2019) Salt separation from water using graphene oxide nanochannels: a molecular dynamics simulation study. Desalination 460:1–14CrossRefGoogle Scholar
  27. 27.
    Giri AK, Teixeira F, Natália M, Cordeiro DS (2018) Structure and kinetics of water in highly confined conditions: a molecular dynamics simulation study. J. Mole. Liq. 268:625–636CrossRefGoogle Scholar
  28. 28.
    Cheng C, Jiang G, Garvey CJ, Wang Y, Simon GP, Liu JZ, Li D (2016) Ion transport in complex layered graphene-based membranes with tuneable interlayer spacing. Sci. Adv. 2:1501272CrossRefGoogle Scholar
  29. 29.
    Hong S, Constans C, Surmani Martins MV, Seow YC, Guevara Carrió JA, Garaj S (2017) Scalable graphene-based membranes for ionic sieving with ultrahigh charge selectivity. Nano Lett. 17:728–732CrossRefGoogle Scholar
  30. 30.
    Zhou X, Wu F, Kou J, Nie X, Liu Y, Lu H (2013) Vibrating-charge-driven water pump controlled by the deformation of the carbon nanotube. J. Phys. Chem. B 117(39):11681–11686CrossRefGoogle Scholar
  31. 31.
    Wan X, Steudle E, Hartung W (2004) Gating of water channels (aquaporins) in cortical cells of young corn roots by mechanical stimuli (pressure pulses): effects of ABA and of HgCl 2. J. Exp. Bot. 55(396):411–422CrossRefGoogle Scholar
  32. 32.
    Abraham J, Vasu KS, Williams CD, Gopinadhan K, Su Y, Cherian CT, Dix J, Prestat E, Haigh SJ, Grigorieva IV, Carbone P, Geim AK, Nair RR (2017) Tuneable sieving of ions using graphene oxide membranes. Nat. Nanotechnol. 12(6):546–550CrossRefGoogle Scholar
  33. 33.
    Plimpton S (1995) Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 117:1–19CrossRefGoogle Scholar
  34. 34.
    SJ Tuart, AB Tutein, JA Harrison (2000) A reactive potential for hydrocarbons with intermolecular interactions, J. Chem. Phys. 112, 6472–6486Google Scholar
  35. 35.
    Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79:926–935CrossRefGoogle Scholar
  36. 36.
    Allen M, Tildesley DJ (1987) Computer simulation of liquids. Oxford University Press, New YorkGoogle Scholar
  37. 37.
    COMSOL Multiphysics. Key: citeulike: 3255057Google Scholar
  38. 38.
    Conway BE (1981) Ionic hydration in chemistry and biophysics. Elsevier Science, Ltd.Google Scholar
  39. 39.
    Zeidel ML, Ambudkar SV, Smith BL, Agre P (1992) Water permeability of asymmetric planar lipid bilayers. Biochemistry 31:7436–7440CrossRefGoogle Scholar
  40. 40.
    Kumar M, Grzelakowski M, Zilles J, Clark M, Meier W (2007) Highly permeable polymeric membranes based on the incorporation of the functional water channel protein Aquaporin Z. Proc. Natl Acad. Sci. 104:20719–20724CrossRefGoogle Scholar
  41. 41.
    Geng, J. et al. Stochastic transport through carbon nanotubes in lipid bilayers and live cell membranes. Nature514, 612–615 (2014)CrossRefGoogle Scholar
  42. 42.
    Tunuguntla RH et al (2017) Enhanced water permeability and tunable ion selectivity in subnanometer carbon nanotube porins. Science 357:792–796CrossRefGoogle Scholar
  43. 43.
    Garaj S, Hubbard W, Reina A, Kong J, Branton D, Golovchenko JA (2010) Graphene as a subnanometre trans-electrode membrane. Nature 467:190–194CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of PhysicsUniversity of IsfahanIsfahanIran
  2. 2.School of Nano-ScienceInstitute for Research in Fundamental Sciences (IPM)TehranIran
  3. 3.Institute for Physical ChemistryUniversity of FreiburgFreiburgGermany

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