Ionic Conductance of Carbon Nanotubes: Confronting Literature Data with Nanofluidic Theory

The field of ion transport through carbon nanotubes (CNTs) is marked by a large variability of the ionic conductance values reported by different groups. There is also a large uncertainty concerning the relative contributions of channel and access resistances in the experimentally measured currents, both depending on experimental parameters (nanotube length and diameter). In this Perspective, we discuss the ionic conductance values reported so far in the case of individual CNTs and compare them with standard nanofluidic models considering both the access and channel resistances. With a view toward guiding experimentalists, we thus show in which conditions the access or the channel resistance can predominate in CNTs. We explain in particular that it is not justified to use phenomenological models neglecting the channel resistance in the case of micrometer long CNTs. This comparison reveals that most experimental conductance values can be explained in the framework of current nanofluidic models by considering experimental variations of slip length and surface charge density and that just a few extraordinarily high values cannot be accounted for even by using extreme parameter values. Finally, we discuss how to complete existing models and how to improve the statistical reliability of experimental data in the field.

Automated summary

The field of ion transport through carbon nanotubes is characterized by varying reported values and uncertainties regarding channel and access resistances. By comparing experimental data with nanofluidic models, it is possible to determine the conditions under which different resistances predominate in CNTs. Most experimental conductance values can be explained by considering variations in slip length and surface charge density, but a few exceptionally high values cannot be accounted for even with extreme parameter values. Improving existing models and enhancing the statistical reliability of experimental data are important for the advancement of research in this field.