How to Recognize Clustering of Luminescent Defects in Single-Wall Carbon Nanotubes

TL;DR

This study compares oxygen and aryl luminescent defects in single-wall carbon nanotubes, revealing defect clustering behavior and providing a spectroscopic method to quantify defect distributions for enhanced optical applications.

Contribution

It introduces a spectroscopic approach to quantify and analyze defect clustering in SWCNTs, particularly distinguishing oxygen defect behaviors under various conditions.

Findings

Oxygen defects tend to cluster in groups of 2-3 along nanotubes.

The clustering of oxygen defects is independent of the functionalization method.

A simple spectroscopic method can determine defect density and clustering in SWCNTs.

Abstract

Semiconducting single-wall carbon nanotubes (SWCNTs) are a promising material platform for near-infrared in-vivo imaging, optical sensing, and single-photon emission at telecommunication wavelengths. The functionalization of SWCNTs with luminescent defects can lead to significantly enhanced photoluminescence (PL) properties due to efficient trapping of highly mobile excitons and red-shifted emission from these trap states. Among the most studied luminescent defect types are oxygen and aryl defects that have largely similar optical properties. So far, no direct comparison between SWCNTs functionalized with oxygen and aryl defects under identical conditions has been performed. Here, we employ a combination of spectroscopic techniques to quantify the number of defects, their distribution along the nanotubes and thus their exciton trapping efficiencies. The different slopes of Raman D/G+ ratios versus calculated defect densities from PL quantum yield measurements indicate substantial dissimilarities between oxygen and aryl defects. Supported by statistical analysis of single-nanotube PL spectra at cryogenic temperatures it reveals clustering of oxygen defects. The clustering of 2-3 oxygen defects, which act as a single exciton trap, occurs irrespective of the functionalization method and thus enables the use of simple equations to determine the density of oxygen defects and oxygen defect clusters in SWCNTs based on standard Raman spectroscopy. The presented analytical approach is a versatile and sensitive tool to study defect distribution and clustering in SWCNTs and can be applied to any new functionalization method.