Topological transitions in carbon nanotube networks via nanoscale confinement

TL;DR

This study demonstrates that geometric confinement in nanoscale channels can induce topological transitions in carbon nanotube networks, enabling control over their electronic properties for scalable nanoelectronic device applications.

Contribution

It introduces a template-assisted fluidic assembly method to manipulate network topology via confinement, revealing a way to induce semiconductor-to-metallic transitions in SWCNT networks.

Findings

Network alignment increases with decreasing channel width and thickness.

Aligned topology becomes independent of network density.

Confinement can induce semiconductor-to-metallic transitions.

Abstract

Efforts aimed at large-scale integration of nanoelectronic devices that exploit the superior electronic and mechanical properties of single-walled carbon nanotubes (SWCNTs) remain limited by the difficulties associated with manipulation and packaging of individual SWNTs. Alternative approaches based on ultra-thin carbon nanotube networks (CNNs) have enjoyed success of late with the realization of several scalable device applications. However, precise control over the network electronic transport is challenging due to i) an often uncontrollable interplay between network coverage and its topology and ii) the inherent electrical heterogeneity of the constituent SWNTs. In this letter, we use template-assisted fluidic assembly of SWCNT networks to explore the effect of geometric confinement on the network topology. Heterogeneous SWCNT networks dip-coated onto sub-micron wide ultra-thin polymer channels exhibit a topology that becomes increasingly aligned with decreasing channel width and thickness. Experimental scale coarse-grained computations of interacting SWCNTs show that the effect is a reflection of an aligned topology that is no longer dependent on the network density, which in turn emerges as a robust knob that can induce semiconductor-to-metallic transitions in the network response. Our study demonstrates the effectiveness of directed assembly on channels with varying degrees of confinement as a simple tool to tailor the conductance of the otherwise heterogeneous network, opening up the possibility of robust large-scale CNN-based devices.