Extraction of pure spectral signatures and corresponding chemical maps from EPR imaging data sets: identifying defects on a CaF2 surface due to a laser beam exposure.

Abstract

A calcium fluoride (CaF2) plate was exposed to pulsed laser irradiations inducing surface morphological and ionization changes on its surface. More precisely surface damages mainly correspond to intrinsic defects. Electron paramagnetic resonance (EPR) hyperspectral imaging is a powerful technique able to characterize the defects formed on the CaF2 surface. Indeed, EPR hyperspectral images provide spatial and spectral information about the sample studied. In fact, these images possess a great potential to obtain accurate and reliable knowledge about the chemical composition and the distribution of the component due to the presence of the spatial aspect. However, the complexity of such hyperspectral data sets imposes the use of advanced chemometric tools to extract valuable information on the considered physicochemical system. Therefore, Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) is proposed to identify and locate the different constituents in the images. The originality of this work is that it reports on the application of MCR-ALS, for the first time, on electron paramagnetic resonance (EPR) imaging data sets that will furnish the distribution maps and the spectral signatures of all components present in the sample. The results show the identification of different intrinsic defects on a CaF2 sample from the sole information in the raw image measurements and, therefore, confirm the potential of this methodology and the important role of spatial information contained in the image.