Fast Ion Diffusion in Carbon Nanotube Channels

Many simulations and experiments have investigated pressure-driven fluid flow in carbon nanotubes (CNTs) and demonstrated enormous transport rates through these channels. Comparatively little attention has been given so far to concentration-driven transport^1,2 in CNTs despite its importance in a large variety of fields. While several studies assumed bulk/hindered diffusion for small molecules confined in nm-wide CNTs, other simulations have predicted self-diffusion coefficients several times larger than in the bulk. These large uncertainties in the magnitude of the diffusion rates through CNTs have hampered their full exploitation in nanofluidic devices.³

To obtain a precise quantification of the diffusive flow under CNT graphitic confinement, we have fabricated membranes with a large but known number of single-walled carbon nanotubes (SWCNT) as fluid transport pathways. Contrary to previous membrane systems, this platform enables us to minimize uncertainties in the calculation of the per-pore flow rate. A series of stringent control experiments confirms that these membranes are defect free and that transport occurs only through SWCNTs. Once corrected for the boundary layer resistance at the membrane/fluid interface, our measurements reveal that the transport diffusivity of small ions in single-walled carbon nanotubes is more than one order of magnitude faster than in the bulk.⁴ The dependence of the flow enhancement on the ion chemico-physical properties is also discussed. Together with indicating that CNT membranes could enable dialysis processes with unprecedented efficiency, these results have important implications for a broad range of applications such as energy storage/harvesting and chemical separation/detection, where ion permeation through nanoporous carbon materials is key.

References

1. Bui, E. R. Meshot, S. Kim, J. Peña, P. W. Gibson, K. J. Wu, F. Fornasiero, Adv. Mater., 28 (2016) 5871.
2. Li, C. Chen, E. R. Meshot, S. F. Buchsbaum, M. Herbert, R. Zhu, O. Kulikov, B McDonald, N. Bui, M. L. Jue, S. J. Park, C. Valdez, S. Hok, C. J. Doona, K. J. Wu, T. M. Swager, F. Fornasiero, Adv. Funct. Mater, in press (2020)
3. S. Guo, E. R. Meshot, T. Kuykendall, S. Cabrini, F. Fornasiero, Adv. Mater. 28 (2015), 5871.
4. S. F. Buchsbaum, M. L. Jue, A. Sawvel, C. Chen, E. R. Meshot, S. J. Park, M. Wood, K. J. Wu, C. L. Bilodeau, T. A. Pham, E. Y. Lau, F. Fornasiero*, submitted (2020)

This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-797189