A rising interest in entropy-stabilized oxides in recent years has been driven by their attractive functional properties. Their synthesis usually requires prolonged exposure at high temperature to promote solid-state diffusion without the application of pressure. In this work, we report the synthesis of a high entropy perovskite, Sr((Zr_0.94Y_0.06)_0.2Sn_0.2Ti_0.2Hf_0.2Mn_0.2)O_3−x, in a relatively short time (minutes instead of hours) using a spark plasma sintering (SPS) furnace. Comparative analysis showed that conventional pressureless sintering at 1500°C for 2 h results in porous materials with large thermodynamically stable pores (tens of µm), while SPS processing produces dense materials in a single step by reactive sintering at 1475°C in 9 min. SPS is therefore an attractive route for the production, synthesis and sintering of dense high-entropy oxides.

X-ray diffraction (XRD) and X-ray fluorescence (XRF) are widely used analytical techniques for materials characterization; the information they provide can be considered complementary, as the former is mostly used to obtain crystallographic information and analyze phase content, whereas the latter is sensitive to elemental composition. Many researchers and technologists working in a variety of application fields already use them together in some sort of a “combined” approach, by separately performing XRD and XRF data collection and analysis on the same sample and then comparing the analytical results obtained to integrate and complement the respective analytical information. In this work, we propose a true combined approach to merge both XRD and XRF data acquisition and analysis. Custom analytical X-ray instrumentation has been developed to perform the simultaneous data acquisition, by using a single X-ray source and dedicated detectors to collect the diffracted and fluorescent X-ray photons from the same sample volume. Additionally, a combined XRD/XRF data analysis methodology has been implemented by extending Rietveld based code to incorporate the full pattern fitting of XRF spectra starting from the phases instead of a simple matrix elemental composition. We report two analytical examples from different application fields to better illustrate the capabilities of the proposed approach.