Models of DG‐Carbon Bands in Raman Spectra: Effects of Basis Functions and Initial Values on the Uniqueness and S/N of Fits Obtained for Atmospheric Aerosol Using Automated Methods

ABSTRACT Soot, coal, graphite, and similar black‐carbon materials contain layered sheets of sp 2 ‐bonded carbon in regions larger than about 4 nm. Such materials typically exhibit Raman spectra (RS) with a peak near 1580 cm −1 (G band) and, except in the case of graphene or highly ordered graphite, a peak in the range 1300–1350 cm −1 (D band). Here such materials are termed DG‐carbon (DGC). To better characterize DGC, the RS can be represented by multiple D and G bands. Comparisons between “best‐fit” D and G bands reported by different researchers are often not possible, partly because in many cases, the choices that must be made in selection of background removal procedures and optimization approach are not stated. Also, automated fitting methods are needed for characterizing large numbers of RS of DGC, such as those measured using Raman hyperspectral imagers, including those used in characterizing atmospheric aerosol particles. To help facilitate both quantitative comparisons of results and automated fits to RS data, we provide here a fitting code which uses MINPACK‐1 as called by the LMFIT python package. To illustrate the use of the code and to investigate optimization using different numbers of basis functions, 15 DGC spectra and four non‐DGC spectra were fitted. We found, for ±20 cm −1 variability of initial peak positions, the RS fits with two Lorentzian functions converged to a single optimized fit. However, for five‐band fits, (1) the final fit demonstrated notable sensitivity to the initial values of the functions in 11 of 15 cases and (2) constraints on the peak center locations were required to keep peak center positions within valid ranges in some cases. When the RS were weaker or the luminescence was large, the variability in final fits was greater.