Identification of hexagonal boron nitride thickness by colourimetry and contrast

The datafiles contain the data used for Figures 2-6 of the paper "Identification of hexagonal boron nitride thickness by colorimetry and contrast" by E. Blundo et al.. A python code used for the analysis of the optical images is also available. The content of the files is described below: "RGBgrey_experimental_and_interpolated_intensity_data__70nm_150nm_280nm__Fig_2":Experimental RGB data and calculated luminance (grey-scale) data; interpolation of the RGB data and calculated grey data. The data for the different substrates are in separate sheets. "RGBgrey_experimental_and_interpolated_intensity_data__90nm_215nm_271nm_297nm__interpolation_of_data_from_literature": Analogous to the previous file but starting from the experimental data available in the literature. The data for the different substrates are in separate sheets. For every substrate, the source for the experimental data is described. It should be noticed that some experimental points were showing clear deviations from the behaviour described bu the other experimental points and were excluded during the interpolation process. "RGBgrey_contrast_and_derivative_data__All_substrates__Figs_3_and_4_and_5": Contrast data (C_X) and its derivative (D_X) for X = RGBL (where L corresponds to grey), calculated starting from the interpolated RGB/grey data contained in the previous two files. Every sheet contains a different C_X or D_X dataset. "RGBgrey_intensity_and_contrast_data__70nm__1-10_layers__Fig_6": RGB/grey intensities and C_X data for the 70 nm SiO2 substrate, for specific hBN thicknesses in the range from 0 to 10 layers. The data were obtained starting from the interpolated data contained in the previous files, for hBN thicknesses t = N*0.33 nm, with N = 0, 1, ..., 10. "average_color_py": Python code which can be used to calculate the average RGB values for a selected area in an image. More specifically, the program allows the user to open the image and manually draw a rectangle to select a region with a given colour; the program then extracts the RGB intensity values for all pixels in the selected region and calculates the average values.