Variance Spectroscopy and its Application to the Study of Single-Wall Carbon Nanotubes
Sanchez, Stephen R
Weisman, R. Bruce
Doctor of Philosophy
This thesis describes the novel method of variance spectroscopy and its application to characterize single-wall carbon nanotube (SWCNT) dispersions. This technique measures and analyzes changes in photoluminescence intensity caused by statistical variations in the local composition of dilute nanoparticle samples. The data are spectrally resolved, allowing for the analysis of individual SWCNT emitters in a complex sample. Several thousand statistically independent spectra from different regions are measured using custom instrumentation. The mean and variance of the emission intensity at each wavelength are used to extract abundances of different SWCNT species and their relative emission efficiencies. Correlations between intensity fluctuations at different wavelengths are also analyzed to reveal the earliest stages of nanoparticle aggregation and provide spectra of homogeneous sub-populations within a well-dispersed sample. Variance spectroscopy has been applied to the following SWCNT studies. A new method was developed combining variance and absorption analysis to determine absolute E11 absorption cross sections for eleven different (n,m) species. The measured absorption cross sections were found to increase nonlinearly with decreasing diameter. A set of measured and estimated absorptivities was compiled as a standard reference for quantitating SWCNT sample concentrations. In another project, variance spectroscopy was applied to track the salt-induced aggregation of individual (n,m) species. Changes in relative abundance showed homoaggregation (same species) while covariance analysis revealed heteroaggregation (different species). The effect of ultrasonication on emission intensity and relative (n,m) abundances was also investigated as a function of sonication parameters. Relative abundance changes were compared to length distributions to estimate debundling effects. Finally, the use of skewness in variance data was introduced to measure aggregation in single-component samples.