MULTIVARIATE STATISTICAL ANALYSIS OF FEG-STEM EDX SPECTRA

A multivariate statistical analysis method has been used to examine the information content of a series of EDX spectra acquired using a FEG-STEM recorded across a segregated grain boundary in a ferritic steel. The spectra have been factored into a set of orthogonal information components (eigenspectra), each of which corresponds to an independent source of information. Two meaningful eigenspectra are identified: one is related to the segregation of P and Cr and the other to a combination of self-absorption and coherent bremsstrahlung. Spectra are reconstructed from the meaningful eigenspectra to reduce noise and improve the sensitivity for detection of trace element segregation.