First Principles Study of Electron Tunneling through Ice

Clotilde S. Cucinotta, Ivan Rungger, Stefano Sanvito

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


With the aim of understanding electrochemical scanning tunnel microscopy experiments in an aqueous environment, we investigate electron transport through ice in the coherent limit. This is done by using the nonequilibrium Greens functions method, implemented within density functional theory, in the self-interaction corrected local density approximation. In particular, we explore different ice structures and different Au electrode surface orientations. By comparing the decay coefficient for different thicknesses to the ice complex band structure, we find that the electron transport occurs via tunneling with almost one-dimensional character. The slow decay of the current with the ice thickness is largely due to the small effective mass of the conduction electrons. Furthermore, we find that the calculated tunneling decay coefficients at the Fermi energy are not sensitive to the structural details of the junctions and are at the upper end of the experimental range for liquid water. This suggests that linear response transport measurements are not capable of distinguishing between different ordered ice structures. However, we also demonstrate that a finite bias measurement may be capable of sorting polar from nonpolar interfaces due to the asymmetry of the current-voltage curves for polar interfaces. © 2012 American Chemical Society.
Original languageEnglish (US)
Pages (from-to)22129-22138
Number of pages10
JournalThe Journal of Physical Chemistry C
Issue number42
StatePublished - Oct 11 2012
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Dr. X. Chen is acknowledged for his contribution in the initial stage of this work. This work is sponsored by Science Foundation of Ireland under the CSET grant underpinning CRANN. I.R. acknowledges support from the King Abdullah University of Science and Technology (ACRAB project). Computational resources have been provided by the HEA IITAC project managed by TCHPC and by a grant from the CSCS, under project ID s206.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.


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