Multivariate statistical analysis of STEM–EDX data from radiation‐induced sensitization in stainless steel

A series of energy-dispersive X-ray spectra acquired in a field-emission gun scanning transmission electron microscope to generate compositional profiles across a grain boundary in a neutron-irradiated stainless steel were subjected to a multivariate statistical analysis (MSA). The complex profiles generated by conventional spectrum processing were factored by MSA into two independent components of information, one associated with both the pre-irradiation heat treatment and radiation-induced segregation (RIS) and the other with diffusion prior to precipitate formation. The two experimental components were separately modelled to deconvolute simple theoretical distributions of composition, which were then recombined to give the full variation in composition across the boundary. A new observation was that the commonly observed RIS enhancement of Ni and Si did not persist in the boundary plane, the composition of which was dominated by pre-irradiation segregation. The potential benefits of MSA for segregation studies are discussed.