Building Chiral Representations of Carbon Nanotube RBM Spectra for Sythesis Control and Analysis

The Radial Breathing Mode (RBM) region of single-walled carbon nanotube Raman spectra encodes information about the diameter and chirality of the tubes. These parameters require careful control to enable widespread adoption of carbon nanotubes as an electrically and mechanically workable material. Determining diameter and chirality is done by fitting peaks to the region and comparing the peak positions to known vibrational modes on a Kataura plot. This top-down approach of fitting a small number of peaks to a spectrum that may contain tens of convoluted peaks provides limited insight, due to the averaging effects of fitting many peaks with only a few. Borrowing from the machine learning community, a bottom-up approach that reconstructs the Raman response as a linear combination of known RBMs is produced using the Least Absolute Shrinkage and Selection Operator (LASSO) model selection algorithm. This method allows for automated analysis of the relative abundances of chiralities present in nanotube Raman spectra and creates a powerful feedback tool to further develop diameter and chirality control in any method of carbon nanotube synthesis.