Identification of carbon nanomaterials by deconvolution of thermogravimetric analysis signals

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In order to link fundamental properties to performance in real-world applications, carbon nanomaterials, especially carbon nanotubes, require detailed compositional information such as the number of distinct species, their relative amounts, and thermochemical data such as kinetic prefactors and activation energies for combustion. Thermogravimetric analysis (TGA) is used widely to measure these values, but the signals can be deceptive, especially with respect to the number of different nanomaterial types. In this work, the Fraser-Suzuki equation is used as the basis of a nonlinear least squares technique to deconvolute the mass loss curves of carbon nanotubes, confirming through subsequent use of the Kissinger equation that there are indeed multiple species present in the sample and they differ in their activation energies for combustion.