Extraction of Information From Stem-Edx Segregation Profiles Using Multivariate Statistical Analysis

Abstract

Multivariate Statistical Analysis (MSA) has been applied to spectroscopic data acquired by various methods but only recently to EDX spectra acquired in the transmission electron microscope where segregation sensitivity was improved by a factor of x2-3. Equilibrium segregation data were ideally suited for MSA analysis. Each spectrum was composed of a linear sum of contributions from the segregation layer and the two adjacent grains or phases, in proportions determined by the probe current distribution and location. MSA successfully identified an eigenvalue explicitly associated with segregation. Smaller eigenvalues related to self-absorption and coherent bremsstrahlung (CB) were also revealed. The use of an orthogonal MSA constrained the information sources to be independent. This constraint, which was reasonable for equilibrium segregation, has now been examined for a more complicated case: thermally and radiation-induced diffusion near an interface where profiles derived by conventional processing have varying features (Fig.l) from which it is difficult to extract real concentration profiles or even qualitative correlations between elements.