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Water/Alcohol Separation in Graphene Oxide Membranes: Insights from Molecular Dynamics and Monte Carlo Simulations

Published online by Cambridge University Press:  13 February 2018

Daiane Damasceno Borges*
Affiliation:
Applied Physics Department and Center of Computational Engineering and Science, University of Campinas - UNICAMP, Campinas-SP13083-959, Brazil.
Cristiano F. Woellner
Affiliation:
Applied Physics Department and Center of Computational Engineering and Science, University of Campinas - UNICAMP, Campinas-SP13083-959, Brazil.
Pedro A. S. Autreto
Affiliation:
Center for Natural and Human Sciences, Federal University of ABC - UFABC, Santo Andre-SP, 09210-580, Brazil
Douglas S. Galvao
Affiliation:
Applied Physics Department and Center of Computational Engineering and Science, University of Campinas - UNICAMP, Campinas-SP13083-959, Brazil.
*

Abstract

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Graphene-based membranes have been investigated as promising candidates for water filtration and gas separation applications. Experimental evidences have shown that graphene oxide can be impermeable to liquids, vapors and gases, while allowing a fast permeation of water molecules. This phenomenon has been attributed to the formation of a network of nano capillaries that allow nearly frictionless water flow while blocking other molecules by steric hindrance effects. It is supposed that water molecules are transported through the percolated two-dimensional channels formed between graphene-based sheets. Although these channels allow fast water permeation in such materials, the flow rates are strongly dependent on how the membranes are fabricated. Also, some fundamental issues regarding the nanoscale mechanisms of water permeation are still not fully understood and their interpretation remains controversial. In this work, we have investigated the dynamics of water permeation through pristine graphene and graphene oxide model membranes that have strong impact on water/alcohol separation. We have carried out fully atomistic classical molecular dynamics simulations of systems composed of multiple layered graphene-based sheets into contact with a pure water reservoir under controlled thermodynamics conditions (e. g., by varying temperature and pressure values). We have systematically analysed how the transport dynamics of the confined nanofluids depend on the interlayer distances and the role of the oxide functional groups. Our results show the water flux is much more effective for graphene than for graphene oxide membranes. These results can be attributed to the H-bonds formation between oxide functional groups and water, which traps the water molecules and precludes ultrafast water transport through the nanochannels.

Type
Articles
Copyright
Copyright © Materials Research Society 2018 

References

REFERENCES

Liu, G., Jin, W., and Xu, N., Chem. Soc. Rev. 44, 5016 (2015).Google Scholar
Sun, P., Zhu, M., Wang, K., Zhong, M., Wei, J., Wu, D., Xu, Z., and Zhu, H., ACS Nano 7, 428 (2013).CrossRefGoogle Scholar
Abraham, J. et al. ., Nature Nanotech. 12, 546 (2017).CrossRefGoogle Scholar
Boffa, V., Etmimi, H., Mallon, P.E., Tao, H.Z., Magnacca, G., and Yue, Y.Z., Carbon 118, 458 (2017).Google Scholar
Tsou, C.-H. et al. ., J. Memb. Sci. 477, 93 (2015).Google Scholar
Joshi, R.K. et al. ., Science 343, 752 (2014).Google Scholar
Nair, R.R., Wu, H.A., Jayaram, P.N., Grigorieva, I. V., and Geim, A.K., Science 335, 442 (2012).CrossRefGoogle Scholar
Falk, K., Sedlmeier, F., Joly, L., Netz, R.R., and Bocquet, L., Nano Lett. 10, 4067 (2010).Google Scholar
Wei, N., Peng, X., and Xu, Z., ACS Appl. Mater. Interfaces 6, 5877 (2014).CrossRefGoogle Scholar
Wei, N., Peng, X., and Xu, Z., Phys. Rev. E - Stat. Nonlinear, Soft Matter Phys. 89, 1 (2014).CrossRefGoogle Scholar
Willcox, J.A.L. and Kim, H.J., ACS Nano 11, 2187 (2017).Google Scholar
Damasceno Borges, D., Woellner, C.F., Autreto, P.A.S., and Galvão, D.S., Carbon 127, 280 (2018).CrossRefGoogle Scholar
Lerf, A., He, H., Forster, M. and Klinowski, J., J. Phys. Chem. B. 102, 4477 (1998)Google Scholar
Erickson, K., Erni, R., Lee, Z., Alem, N., Gannett, W. and Zettl, A., Adv. Mater. 22, 4467 (2010)Google Scholar
Martinez, L., Andrade, R., Birgin, E.G., and Martínez, J.M., J. Comput. Chem. 30, 2157 (2009).CrossRefGoogle Scholar
Nosé, S., J. Chem. Phys. 81, 511 (1984).Google Scholar
Hoover, W.G., Phys. Rev. A 31, 1695 (1985).Google Scholar
Vanommeslaeghe, K. et al. ., J. Comput. Chem. 31, 671 (2010).CrossRefGoogle Scholar
Yu, W., He, X., Vanommeslaeghe, K., and MacKerell, A.D., J. Comput. Chem. 33, 2451 (2012).CrossRefGoogle Scholar
Jiao, S. and Xu, Z., ACS Appl. Mater. Interfaces 7, 9052 (2015).CrossRefGoogle Scholar
Berendsen, H. J. C., Grigera, J.R., and Straatsma, T.P., J. Phys. Chem. 91, 6269 (1987).Google Scholar
Plimpton, S., J. Comput. Phys. 117, 1 (1995).CrossRefGoogle Scholar