Statistical Analysis Of SEM-EDX Spectrum Images Of A Metal-Ceramic Braze

Abstract Spectrum imaging, where a complete spectrum is acquired at each pixel in an image, is potentially a very powerful technique for the characterization of materials. The primary challenge to overcome is to extract all of the relevant information from what are typically large data sets that cannot be readily visualized in their entirety. For energy-dispersive X-ray (EDX) spectrum images, simple mapping has typically been done. In this work, the application of multivariate statistical analysis (MSA) to the characterization of a metal/alumina braze by SEM-EDX spectrum images is described. The braze characterized in this work joins polycrystalline alumina and a copper-silver eutectic alloy containing some titanium (an ‘active’ metal). The specimen geometry consisted of a sandwich of two pieces of alumina, two braze layers and a Kovar (primarily Fe, Ni and Co) filler layer in the middle. The entire assembly was heat-treated to bond the interfaces and then a polished cross-section was prepared.