Skip to main content
Log in

Molecular Simulation of Pervaporation of a Lennard-Jones Mixture Using a Crystalline Membrane

  • Published:
Theoretical Foundations of Chemical Engineering Aims and scope Submit manuscript

Abstract

Numeric simulation of the pervaporation process is carried out using molecular dynamics. Various conditions of the separation of an ideal binary Lennard-Jones mixture using a crystalline membrane are considered. Components of separated mixtures differ in regards to the energy of interaction with molecules of the membrane. As a result of simulation, fields of concentrations and densities along the cell, as well as flux values of components, are obtained. In addition, coefficients of the diffusion of components in the membrane are computed. It is shown that the correspondence of numeric simulation data to macroscopic mass transfer equations are observed in all cases. It can be concluded that the behavior of molecules in a nonequilibrium system with a scale of several dozens of molecule diameters corresponds to transfer equations of linear nonequilibrium thermodynamics. Results of numeric simulation show the selectivity of a membrane in regard to the component with a larger interaction energy. It is shown that molecular simulation is able to predict the main characteristics of membrane separation (fluxes, selectivity, adsorption, and diffusion coefficients).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.

Similar content being viewed by others

REFERENCES

  1. Bell, C.M., Gerner, F.J., and Strathmann, H., Selection of polymers for pervaporation membranes, J. Membr. Sci., 1988, vol. 36, pp. 315–329. https://doi.org/10.1016/0376-7388(88)80025-5

    Article  CAS  Google Scholar 

  2. Kagramanov, G.G. and Farnosova, E.N., Scientific and engineering principles of membrane gas separation systems development, Theor. Found. Chem. Eng., 2017, vol. 51, no. 1, pp. 38–44. https://doi.org/10.1134/S0040579517010092

    Article  CAS  Google Scholar 

  3. Akberov, R.R., Fazlyev, A.R., Klinov, A.V., Malygin, A.V., Farakhov, M.I., Maryakhina, V.A., and Kirichenko, S.M., Dehydration of diethylene glycol by pervaporation using HybSi ceramic membranes, Theor. Found. Chem. Eng., 2014, vol. 48, no. 5, pp. 650–655. https://doi.org/10.1134/S0040579514030014

    Article  CAS  Google Scholar 

  4. Babak, V.N., Didenko, L.P., Kvurt, Y.P., and Sementsova, L.A., The recovery of hydrogen from binary gas mixtures using a membrane module based on a palladium foil taking into account the deactivation of the membrane, Theor. Found. Chem. Eng., 2018, vol. 52, no. 3, pp. 371–385. https://doi.org/10.1134/S0040579518020021

    Article  CAS  Google Scholar 

  5. Babak, V.N., Didenko, L.P., Kvurt, Yu.P., and Sementsova, L.A., Studying the operation of a membrane module based on palladium foil at high temperatures, Theor. Found. Chem. Eng., 2018, vol. 52, no. 2, pp. 181–194. https://doi.org/10.1134/S004057951802001X

    Article  CAS  Google Scholar 

  6. Wijmans, J.G. and Baker, R.W., The solution-diffusion model: A review, J. Membr. Sci., 1995, vol. 107, nos. 1–2, pp. 1–21. https://doi.org/10.1016/0376-7388(95)00102-I

    Article  CAS  Google Scholar 

  7. Krishna, R., Diffusion in porous crystalline materials, Chem. Soc. Rev., 2012, vol. 41, no. 8, pp. 3099–3118. https://doi.org/10.1039/C2CS15284C

    Article  CAS  PubMed  Google Scholar 

  8. Oulebsir, F., Vermorel, R., and Galliero, G., Diffusion of supercritical fluids through single-layer nanoporous solids: Theory and molecular simulations, Langmuir, 2018, vol. 34, no. 2, pp. 561–571. https://doi.org/10.1021/acs.langmuir.7b03486

    Article  CAS  PubMed  Google Scholar 

  9. Hinkle, K., Wang, X., Gu, X., Jameson, C., and Murad, S., Computational molecular modeling of transport processes in nanoporous membranes, Processes, 2018, vol. 6, no. 8, p. 124. https://doi.org/10.3390/pr6080124

    Article  CAS  Google Scholar 

  10. Wang, L., Dumont, R.S., and Dickson, J.M., Nonequilibrium molecular dynamics simulation for studying the effect of pressure difference and periodic boundary conditions on water transport through a CNT membrane, Mol. Phys., 2017, vol. 115, no. 8, pp. 981–990. https://doi.org/10.1080/00268976.2017.1298862

    Article  CAS  Google Scholar 

  11. MacElroy, J.M.D., Computer simulation of diffusion within and through membranes using nonequilibrium molecular dynamics, Korean J. Chem. Eng., 2000, vol. 17, no. 2, pp. 129–142. https://doi.org/10.1007/BF02707134

    Article  Google Scholar 

  12. Cao, W., Tow, G.M., Lu, L., Huang, L., and Lu, X., Diffusion of CO2/CH4 confined in narrow carbon nanotube bundles, Mol. Phys., 2016, vol. 114, nos. 16–17, pp. 2530–2540. https://doi.org/10.1080/00268976.2016.1177665

    Article  CAS  Google Scholar 

  13. Richard, R., Anthony, S., and Aziz, G., Pressure-driven molecular dynamics simulations of water transport through a hydrophilic nanochannel, Mol. Phys., 2016, vol. 114, no. 18, pp. 2655–2663. https://doi.org/10.1080/00268976.2016.1170219

    Article  CAS  Google Scholar 

  14. Heffelfinger, G.S. and van Swol, F., Diffusion in Lennard-Jones fluids using dual control volume grand canonical molecular dynamics simulation (DCV-GCMD), J. Chem. Phys., 1994, vol. 100, no. 10, pp. 7548–7552. https://doi.org/10.1063/1.466849

    Article  CAS  Google Scholar 

  15. Firouzi, M. and Sahimi, M., Molecular dynamics simulation of transport and separation of carbon dioxide-alkane mixtures in a nanoporous membrane under sub- and supercritical conditions, Transp. Porous Media, 2016, vol. 115, no. 3, pp. 495–518. https://doi.org/10.1007/s11242-016-0638-6

    Article  CAS  Google Scholar 

  16. Arya, G., Chang, H.-C., and Maginn, E.J., A critical comparison of equilibrium, non-equilibrium and boundary-driven molecular dynamics techniques for studying transport in microporous materials, J. Chem. Phys., 2001, vol. 115, no. 17, pp. 8112–8124. https://doi.org/10.1063/1.1407002

    Article  CAS  Google Scholar 

  17. Cracknell, R.F., Nicholson, D., and Quirke, N., Direct molecular dynamics simulation of flow down a chemical potential gradient in a slit-shaped micropore, Phys. Rev. Lett., 1995, vol. 74, no. 13, pp. 2463–2466. https://doi.org/10.1103/PhysRevLett.74.2463

    Article  CAS  PubMed  Google Scholar 

  18. Thompson, A.P., Ford, D.M., and Heffelfinger, G.S., Direct molecular simulation of gradient-driven diffusion, J. Chem. Phys., 1998, vol. 109, no. 15, pp. 6406–6414. https://doi.org/10.1063/1.477284

    Article  CAS  Google Scholar 

  19. Kazemi, M. and Takbiri-Borujeni, A., Flow of gases in organic nanoscale channels: A boundary-driven molecular simulation study, Energy Fuels, 2016, vol. 30, no. 10, pp. 8156–8163. https://doi.org/10.1021/acs.energyfuels.6b01456

    Article  CAS  Google Scholar 

  20. Jin, Z. and Firoozabadi, A., Flow of methane in shale nanopores at low and high pressure by molecular dynamics simulations, J. Chem. Phys., 2015, vol. 143, no. 10, p. 104315. https://doi.org/10.1063/1.4930006

    Article  CAS  PubMed  Google Scholar 

  21. Kazemi, M. and Takbiri-Borujeni, A., Modeling and simulation of gas transport in carbon-based organic nano-capillaries, Fuel, 2017, vol. 206, pp. 724–737. https://doi.org/10.1016/j.fuel.2017.04.033

    Article  CAS  Google Scholar 

  22. Kirchofer, A., Firouzi, M., Psarras, P., and Wilcox, J., Modeling CO2 transport and sorption in carbon slit pores, J. Phys. Chem. C, 2017, vol. 121, no. 38, pp. 21018–21028. https://doi.org/10.1021/acs.jpcc.7b06780

    Article  CAS  Google Scholar 

  23. Wang, S., Yu, Y., and Gao, G., Non-equilibrium molecular dynamics simulation on pure gas permeability through carbon membranes, Chin. J. Chem. Eng., 2006, vol. 14, no. 2, pp. 164–170. https://doi.org/10.1016/S1004-9541(06)60054-2

    Article  CAS  Google Scholar 

  24. Firouzi, M. and Wilcox, J., Slippage and viscosity predictions in carbon micropores and their influence on CO2 and CH4 transport, J. Chem. Phys., 2013, vol. 138, no. 6, p. 064705. https://doi.org/10.1063/1.4790658

    Article  CAS  PubMed  Google Scholar 

  25. Klinov, A.V., Anashkin, I.P., and Akberov, R.R., Molecular dynamics simulation of pervaporation of an ethanol-water mixture on a hybrid silicon oxide membrane, High Temp., 2018, vol. 56, no. 1, pp. 70–76. https://doi.org/10.1134/S0018151X18010091

    Article  CAS  Google Scholar 

  26. Allen, M.P. and Tildesley, D.J., Computer Simulation of Liquids, Oxford: Clarendon, 1989.

    Google Scholar 

  27. Pronk, S., Pall, S., Schulz, R., Larsson, P., Bjelkmar, P., Apostolov, R., and Lindahl, E., GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit, Bioinformatics, 2013, vol. 29, no. 7, pp. 845–854. https://doi.org/10.1093/bioinformatics/btt055

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Abraham, M.J., Murtola, T., Schulz, R., Pall, S., Smith, J.C., Hess, B., and Lindahl, E., GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers, SoftwareX, 2015, vols. 1–2, pp. 19–25. https://doi.org/10.1016/j.softx.2015.06.001

    Article  Google Scholar 

  29. Berendsen, H.J.C., van der Spoel, D., and van Drunen, R., GROMACS: A message-passing parallel molecular dynamics implementation, Comput. Phys. Commun., 1995, vol. 91, nos. 1–3, pp. 43–56. https://doi.org/10.1016/0010-4655(95)00042-E

    Article  CAS  Google Scholar 

  30. GitHub: The World’s Leading Software Development Platform. https://github.com/KSTU/gromem. Accessed November 28, 2018.

  31. GitHub: The World’s Leading Software Development Platform. https://github.com/KSTU/articles/tree/master/ membrane-simple-lj. Accessed November 28, 2018.

  32. Medvedev, O.O., Diffusion Coefficients in Multicomponent Mixtures, Copenhagen: Technical Univ. of Denmark, 2004.

    Google Scholar 

  33. Shewmon, P.G., Diffusion in Solids, Warrendale, Pa.: Minerals, Metals & Materials Society, 1989.

    Google Scholar 

  34. Meier, K., Laesecke, A., and Kabelac, S., Transport coefficients of the Lennard-Jones model fluid. II Self-diffusion, J. Chem. Phys., 2004, vol. 121, no. 19, pp. 9526–9535. https://doi.org/10.1063/1.1786579

    Article  CAS  PubMed  Google Scholar 

  35. Johnson, J.K., Zollweg, J.A., and Gubbins, K.E., The Lennard-Jones equation of state revisited, Mol. Phys., 1993, vol. 78, no. 3, pp. 591–618. https://doi.org/10.1080/00268979300100411

    Article  CAS  Google Scholar 

  36. Hwang, S.T. and Kammermeyer, K., Membranes in Separations, New York: Wiley, 1975.

    Google Scholar 

  37. Shen, Y. and Lua, A.C., Effects of membrane thickness and heat treatment on the gas transport properties of membranes based on P84 polyimide, J. Appl. Polym. Sci., 2010, vol. 116, no. 5, pp. 2906–2912. https://doi.org/10.1002/app.31810

    Article  CAS  Google Scholar 

  38. Koops, G.H., Nolten, J.A.M., Mulder, M.H.V., and Smolders, C.A., Selectivity as a function of membrane thickness: Gas separation and pervaporation, J. Appl. Polym. Sci., 1994, vol. 53, no. 12, pp. 1639–1651. https://doi.org/10.1002/app.1994.070531210

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. V. Klinov.

Additional information

Translated by K. Gumerov

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Klinov, A.V., Anashkin, I.P., Razinov, A.I. et al. Molecular Simulation of Pervaporation of a Lennard-Jones Mixture Using a Crystalline Membrane. Theor Found Chem Eng 53, 472–486 (2019). https://doi.org/10.1134/S0040579519040201

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0040579519040201

Keywords:

Navigation