DOE OSTI2016
Analytical electron microscopy (AEM) in the scanning transmission electron microscope (STEM) has long been a staple of post-irradiation examination (PIE) and materials development campaigns. Recently, new advances in both STEM hardware and post-processing data-analysis software, along with ancillary advances such as in focused ion beam (FIB) sample preparation, has led to exciting advances in the quantity and quality of data that can be obtained. This talk will summarize recent experiments performed at Oak Ridge National Laboratory (ORNL), especially work on neutron-irradiated materials and fuels taking advantage of a newly-installed latest-generation AEM tool in the ORNL irradiated materials laboratories. ORNL installed a new FEI Talos F200X microscope, a 200 keV, high-brightness Schottky emission AEM system optimized for high-speed, high-efficiency X-ray mapping experiments. The F200X features the FEI 'SuperX' four-sector silicon drift detector (SDD) X-ray detector, which provides 0.9 sr solid angle of collection. By combining the high-brightness electron source, latest-generation electron optics, and fast computers and pulse processors, X-ray mapping speed is increased by a factor of 50-100 x compared to the previous-generation instruments. In addition to improvements in hardware, data mining via multivariate statistical analysis (MVSA) allows for maximum insight to the data obtained from the new hardware. MVSA data mining of the X-ray maps allows, for instance, unbiased computational identification of the phases present, and discovery of small phases or precipitates not expected by the human analyst. This talk will present examples of experiments performed using the most modern AEM tools and software. Silicon carbide is a major candidate for next-generation nuclear applications. Nano-infiltration by transient eutectic (NITE) SiC requires low sintering temperatures. X-ray mapping of the NITE structure find pockets of different oxides, such as Zr-Y-oxide, Y-Al-oxide, and yttria. MVSA data mining finds the regions where different oxides are present and indicates that Y additions preferentially wet grain boundaries, where Zr additions are preferentially concentrated at grain triple points. SiC coatings from AGR-I experiment TRISO particles were found to contain significant quantities of fission products (e.g., Pd) as well as actinides (U, Pu). MVSA data mining found complex precipitates and grain boundary films of the fission products and actinides deep (∼several microns) into the SiC layer. Advanced AEM methods, combined with MVSA data mining, makes possible both rapid and detailed PIE. Ferritic alloys, such as accident-tolerant FeCrAl grades, benefit greatly from advanced AEM examination. Neutron-irradiated FeCrAl precipitates the detrimental Cr-rich α' phase. Because the SuperX SDD system has four detectors, it is possible to obtain high X-ray count rates even on a highly tilted specimen, as might be needed to obtain STEM images of dislocation loops. Results on neutron-irradiated FeCrAl indicates that α' size and number density can be obtained by AEM, and MVSA results determine that minor elements (such as Si) has complex radiation-induced segregation behavior at grain boundaries. We have also developed and validated computer models of the AEM experiment, allowing different microstructures' X-ray map results to be simulated for different STEM instruments. This allows X-ray mapping to be more quantitative, such as by estimating what size nanoclusters in an oxide-dispersion strengthened steel would be visible or invisible in STEM. In summary, new advanced AEM technology provides a major leap forward in experiments possible in PIE of irradiated materials. (authors)