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Modelling of Conductive Nanoporous Membranes with Switchable Ionic Selectivity

Membranes and Membrane Technologies volume 2, pages 10–19 (2020)Cite this article

Abstract

An interesting area of modern membrane science is the development of “smart” membranes, which can affect the transport properties of selected components via external tuning. When the target components are ions, such a tuning can be realized with the help of electric field created by the conductive pore surface. We have proposed in this work a mathematical model of ions transport in a cylindrical nanopore with the electronic charge at the conductive surface and the chemical charge, which is separated from the surface by the Stern layer. The model is based on one-dimensional equations for potential, ion concentrations, and pressure in the diffuse layer. It is applied for describing the membrane potential at zero current, which characterizes the type and strength of ionic selectivity. It is shown that the change of surface potential in the direction from negative to positive results in the continuous change of pore selectivity from cation to anion. The decrease in the Stern layer capacitance and increase in the pore radius lead to the decrease in ionic selectivity. The presence of positive (negative) chemical charge causes the shift of potential value, at which the selectivity is switched, in the direction of negative (positive) values. At this value of potential, the membrane becomes non-selective, the diffusive flux of ions reaches maximum, and the osmotic flow ceases. The suggested model provides a qualitative and quantitative description of experimental results on switchable selectivity of track-etched membranes modified by the gold coating.

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REFERENCES

  1. L. F. Greenlee, D. F. Lawler, B. D. Freeman, B. Marrot, and P. Moulin, Water Res. 43, 2317 (2009).

    Article  CAS  PubMed  Google Scholar 

  2. V. V. Volkov, B. V. Mchedlishvili, V. I. Roldugin, S. S. Ivanchev, and A. B. Yaroslavtsev, Nanotechnol. Russ. 3, 656 (2008).

    Article  Google Scholar 

  3. H. Strathmann, Desalination 264, 268 (2010).

    Article  CAS  Google Scholar 

  4. S. Porada, R. Zhao, A. Van der Wal, V. Presser, and P. M. Biesheuvel, Prog. Mater. Sci. 58, 1388 (2013).

    Article  CAS  Google Scholar 

  5. Y. Tanaka, Ion Exchange Membranes: Fundamentals and Applications (Elsevier, Amsterdam, 2015).

    Book  Google Scholar 

  6. A. B. Yaroslavtsev and V. V. Nikonenko, Nanotechnol. Russ. 4, 137 (2009).

    Article  Google Scholar 

  7. P. Yu. Apel, O. V. Bobreshova, A. V. Volkov, V. V. Volkov, V. V. Nikonenko, I. A. Stenina, A. N. Filippov, Yu. P. Yampolskii, and A. B. Yaroslavtsev, Membr. Membr. Technol. 1, 45 (2019).

    Article  Google Scholar 

  8. R. W. Baker, Membrane Technology and Applications (England: John Wiley & Sons, Chichester, 2004).

    Book  Google Scholar 

  9. J. Bobacka, A. Ivaska, and A. Lewenstam, Chem. Rev. 108, 329 (2008).

    Article  CAS  PubMed  Google Scholar 

  10. W. Sparreboom, A. Berg, and J. C. T. Eijkel, Nature Nanotech. 4, 713 (2009).

    Article  CAS  Google Scholar 

  11. L. Zhang, S. R. Chae, Z. Hendren, J. S. Park, and M. R. Wiesner, Chem. Eng. J. 204–206, 87 (2012).

    Article  CAS  Google Scholar 

  12. M. Tagliazucchi and I. Szleifer, Mater. Today 18, 131 (2015).

    Article  CAS  Google Scholar 

  13. Z. S. Siwy and S. Howorka, Chem. Soc. Rev. 39, 1115 (2010).

    Article  CAS  PubMed  Google Scholar 

  14. X. Hou, W. Guo, and L. Jiang, Chem. Soc. Rev. 40, 2385 (2011).

    Article  CAS  PubMed  Google Scholar 

  15. P. Yu. Apel, I. V. Blonskaya, N. V. Levkovich, and O. L. Orelovich, Petr. Chem. 51, 555 (2011).

    Article  CAS  Google Scholar 

  16. M. Nishizawa, V. P. Menon, and C. R. Martin, Science 268, 700 (1995).

    Article  CAS  PubMed  Google Scholar 

  17. C. R. Martin, M. Nishizawa, K. Jirage, M. Kang, and S. B. Lee, Adv. Mater. 13, 1351 (2001).

    Article  CAS  Google Scholar 

  18. M. Kang and C. R. Martin, Langmuir 17, 2753 (2001).

    Article  CAS  Google Scholar 

  19. P. Gao and C. R. Martin, ACS Nano 8, 8266 (2014).

    Article  CAS  PubMed  Google Scholar 

  20. D. V. Lebedev, A. V. Shiverskiy, M. M. Simunin, V. S. Solodovnichenko, V. A. Parfenov, V. V. Bykanova, S. V. Khartov, and I. I. Ryzhkov, Petr. Chem. 57, 306 (2017).

    Article  CAS  Google Scholar 

  21. V. S. Solodovnichenko, D. V. Lebedev, V. V. Bykanova, A. V. Shiverskiy, M. M. Simunin, V. A. Parfenov, and I. I. Ryzhkov, Adv. Eng. Mater. 19, 1700244 (2017).

    Article  CAS  Google Scholar 

  22. D. V. Lebedev, V. S. Solodovnichenko, M. M. Simunin, and I. I. Ryzhkov, Petr. Chem. 58, 474 (2018).

    Article  CAS  Google Scholar 

  23. W. Guan and M. A. Reed, Nano Lett. 12, 6441 (2012).

    Article  CAS  PubMed  Google Scholar 

  24. H. Zhang, X. Quan, X. Fan, C. Yi, S. Chen, H. Yu, and Y. Chen, Environ. Sci. Technol. 53, 868 (2019).

    Article  CAS  PubMed  Google Scholar 

  25. D. Mattia, H. Leese, and K. P. Lee, J. Membr. Sci. 475, 266 (2015).

    Article  CAS  Google Scholar 

  26. M. Alsawat, T. Altalhi, T. Kumeria, A. Santos, and D. Losic, Carbon 93, 681 (2015).

    Article  CAS  Google Scholar 

  27. M. Sarno, A. Tamburrano, L. Arurault, S. Fontorbes, R. Pantani, L. Datas, P. Ciambelli, and M. S. Sarto, Carbon 55, 10 (2013).

    Article  CAS  Google Scholar 

  28. P. Ramírez, S. Mafé, A. Alcaraz, and J. Cervera, J. Phys. Chem. B 107, 13178 (2003).

    Article  CAS  Google Scholar 

  29. C. Amatore, A. I. Oleinick, and I. Svir, Chem. Phys. Chem. 10, 211 (2009).

    Article  CAS  PubMed  Google Scholar 

  30. A. N. Filippov, Colloid J. 80, 716 (2018).

    Article  CAS  Google Scholar 

  31. R. J. Gross and J. F. Osterle, J. Chem. Phys. 49, 228 (1968).

    Article  CAS  PubMed  Google Scholar 

  32. P. B. Peters, R. Van Roij, M. Z. Bazant, and P.  M. Biesheuvel, Phys. Rev. E. 93, 053108 (2016).

    Article  CAS  PubMed  Google Scholar 

  33. I. I. Ryzhkov, D. V. Lebedev, V. S. Solodovnichenko, A. V. Shiverskiy, and M. M. Simunin, Phys. Rev. Lett. 119, 226001 (2017).

    Article  CAS  PubMed  Google Scholar 

  34. I. I. Ryzhkov, D. V. Lebedev, V. S. Solodovnichenko, A. V. Minakov, and M. M. Simunin, J. Membr. Sci. 549, 616 (2018).

    Article  CAS  Google Scholar 

  35. I. I. Ryzhkov, A. S. Vyatkin, and A. V. Minakov, J. Sib. Fed. Univ.: Math. Phys. 11, 494 (2018).

    Google Scholar 

  36. I. I. Ryzhkov, A. S. Vyatkin, and M. I. Medvedeva, J. Sib. Fed. Univ.: Math. Phys. 12, 579 (2019).

    Google Scholar 

  37. L. Zhang, P. M. Biesheuvel, and I. I. Ryzhkov, Phys. Rev. Appl. 12, 014039 (2019).

    Article  CAS  Google Scholar 

  38. J. Duval, J. Lyklema, J. M. Kleijn, and H. P. Van Leeuwen, Langmuir 17, 7573 (2001).

    Article  CAS  Google Scholar 

  39. J. Duval, J. M. Kleijn, J. Lyklema, and H. P. Van Leeuwen, J. Electroanal. Chem. 532, 337 (2002).

    Article  CAS  Google Scholar 

  40. C. H. Hamman, A. Hamnett, and W. Veilstich, Electrochemistry (Wiley-WCH, 2007).

    Google Scholar 

  41. V. M. Dorokhov, G. A. Martynov, V. M. Starov, and N. V. Churaev, Kolloidn. Zh. 46, 651 (1984).

    CAS  Google Scholar 

  42. V. M. Dorokhov, G. A. Martynov, V. M. Starov, and N. V. Churaev, Kolloidn. Zh. 46, 1088 (1984).

    CAS  Google Scholar 

  43. M. D. Porter, T. B. Bright, D. L. Allara, and C. E. D. Chidsey, J. Am. Chem. Soc. 109, 3559 (1987).

    Article  CAS  Google Scholar 

  44. S. Rentsch, H. Siegenthaler, and G. Papastavrou, Langmuir 23, 9083 (2007).

    Article  CAS  PubMed  Google Scholar 

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Funding

This work was financially supported by the Russian Foundation for Basic Research, project no. 18-38-20046 mol_a_ved.

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Authors and Affiliations

  1. Institute of Computational Modelling, Russian Academy of Sciences, Siberian Branch, Akademgorodok 50-44, 660036, Krasnoyarsk, Russia

    I. I. Ryzhkov, A. S. Vyatkin & E. V. Mikhlina

  2. Siberian Federal University, Svobodny pr. 79, 660041, Krasnoyarsk, Russia

    I. I. Ryzhkov

Authors
  1. I. I. Ryzhkov
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  2. A. S. Vyatkin
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  3. E. V. Mikhlina
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Corresponding author

Correspondence to I. I. Ryzhkov.

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Translated by V. Avdeeva

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Ryzhkov, I.I., Vyatkin, A.S. & Mikhlina, E.V. Modelling of Conductive Nanoporous Membranes with Switchable Ionic Selectivity. Membr. Membr. Technol. 2, 10–19 (2020). https://doi.org/10.1134/S2517751620010072

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  • DOI: https://doi.org/10.1134/S2517751620010072

Keywords:

  • nanopore
  • conductive surface
  • Stern layer
  • ionic selectivity
  • membrane potential
  • mathematical modelling