Improved Background Removal Method Using Principal Components Analysis for Spatially Resolved Electron Energy Loss Spectroscopy
Source abstract
Abstract
Principal components analysis (PCA) factor filtering is implemented for the improvement of background removal in noisy spectra. When PCA is used as a method for filtering before background removal in electron energy loss spectroscopy elemental maps, an improvement in the accuracy of the background fit with very short fitting intervals is achieved, leading to improved quality of elemental maps from noisy spectra. This opens the possibility to use shorter exposure times for elemental mapping, leading to fewer problems with, for example, drift and beam damage.
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Research context
OpenAlex topics: Electron and X-Ray Spectroscopy Techniques · Electrochemical Analysis and Applications · Machine Learning in Materials Science
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References (10)
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