Statistical sampling of carbon nanotube populations by thermogravimetric analysis

Carbon nanotubes are one of the most promising nanomaterials available with applications in electronics devices, sensing, batteries, composites and medicine. Strict control of the carbon nanotube chemistry and properties is necessary as the applications proceed into more specialized areas. Thermogravimetric analysis (TGA) is one analytical method currently utilized for the characterization of carbon nanotubes. Though TGA can provide quantitative measurements of the composition of a sample, many researchers do not ensure the variance of the sample is properly captured. This research demonstrates for four single-wall carbon nanotube (SWCNT) samples how to statistically evaluate the material with TGA to ensure that the variance within the material is represented. SEM results are used to help reach conclusions about purity of the material by providing a visual means for inspection. This data is used to select the SWCNT material with the lowest variability and highest quality, as evaluated by composition and reproducibility.