  The routine and unique determination of minor phases in microstructures is
critical to materials science. In metallurgy alone, applications include alloy
and process development and the understanding of degradation in service. We
develop a correlative method, exploring superalloy microstructures which are
examined in the scanning electron microscope (SEM) using simultaneous energy
dispersive X-ray spectroscopy (EDS) and electron backscatter diffraction
(EBSD). This is performed at an appropriate length scale for characterisation
of carbide phases' shape, size, location, and distribution. EDS and EBSD data
are generated using two different physical processes, but each provide a
signature of the material interacting with the incoming electron beam. Recent
advances in post-processing, driven by "big data" approaches, include use of
principal component analysis (PCA). Components are subsequently characterised
to assign labels to a mapped region. To provide physically meaningful signals,
the principal components may be rotated to control the distribution of
variance. In this work, we develop this method further through a weighted PCA
approach. We use the EDS and EBSD signals concurrently, thereby labelling each
region using both EDS (chemistry) and EBSD (crystal structure) information.
This provides a new method of amplifying signal-to-noise for very small phases
in mapped regions, especially where the EDS or EBSD signal is not unique enough
alone for classification.
