Abstract
Both at the academic and the industrial level, material scientists are exploring routes for mass production and functionalization of graphene, carbon nanotubes, carbon dots, 2D materials, and heterostructures of these. Proper application of the novel materials requires fast and thorough characterization of the samples. Raman spectroscopy stands out as a standard non-invasive technique capable of giving key information on the structure and electronic properties of nanomaterials, including the presence of defects, degree of functionalization, diameter (in the case of carbon nanotubes), different polytypes, doping, etc. Here, we present a computational tool to automatically analyze the Raman spectral features of nanomaterials, which we illustrate with the example of carbon nanotubes and graphene. The algorithm manages hundreds of spectra simultaneously and provides statistical information (distribution of Raman shifts, average values of shifts and relative intensities, standard deviations, correlation between different peaks, etc.) of the main spectral features defining the structure and electronic properties of the samples, as well as publication-ready graphical material.
Supplementary materials
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matlab code
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Code for matlab
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Python code
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Code for python
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Readme matlab
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Instructions for matlab code
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Readme python
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Instructions for python code
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data (6,5) SWNTs
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data (6,5) SWNTs
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Data CuMINTs
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Data CuMINTs
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2D map example
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Data for the 2D Raman map in the main text
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Graphical User Interface for Matlab
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Graphical User Interface for Matlab
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Graphical User Interface for Python
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Graphical User Interface for Python
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Lorentz fitting Matlab
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Lorentz fitting Matlab
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Voigt fitting Matlab
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Voigt fitting Matlab
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Lorentz fitting Python
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Lorentz fitting Python
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ReadMe file
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ReadMe file
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Supplementary weblinks
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Dataset and code files
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The codes and experimental data reported in this manuscript are openly available in IMDEA nanoscience repository
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