Preprocessing of the spectral data is done by vector normalization and asymmetric least squares (ALS) baseline correction . The NMF classifier with 𝑚 = 3 components is trained on the complete data sets of 7500 spectra with 1,600 channels each. The data sets are decomposed using the pre-trained NMF classifiers, and the resulting component spectra are matched with reference spectra from commercially available Raman data bases (STJapan, ~ 5,000 spectra) to assign them to polymers and deposits respectively. Transformation of the data set using the trained NMF classifiers provided scalar concentrations of every resulting component and their spatial distribution (maps).