Matthew Swenson

In situ TEM Mechanical Testing: An Emerging Approach for Characterization of Polycrystalline, Irradiated Alloys

In situ transmission electron microscopic (TEM) mechanical testing techniques enable concurrent TEMresolution imaging/video and mechanical testing of sub-micron-sized electron-transparent specimens. Because nuclear materials are often volume-limited, due to constraints imposed either by radioactivity levels or near-surface ion irradiation damage layers, in situ TEM mechanical testing presents great potential for analyzing these small specimen volumes. But thus far, only a few studies have conducted in situ TEM mechanical tests on irradiated or engineering alloys. Irradiated alloy work [1] focused on single-crystal Cu that was irradiated after the TEM specimen was fabricated, while the oxide dispersion strengthened (ODS) alloy tested [2] was unirradiated. The objective of the present study, then, is to extend the use of in situ TEM mechanical tests to ODS alloys that have previously been irradiated in bulk form, which is a conventional specimen configuration amongst the nuclear materials community.

Collected Data Set Size Considerations for Atom Probe Cluster Analysis

Atom probe tomography is increasingly being used to complement transmission electron microscopy (TEM) to characterize microstructures, particularly for nano-featured materials containing phases that are below TEM resolution limits. Local electrode atom probe (LEAP) tomographic cluster analysis algorithms provide an objective means to identify and measure the size and number density of these nano-scale phases. However, there is a lack of standardized methodology for quantifying average cluster size, which presents ambiguities and challenges when attempting to compare nanocluster morphology between different specimens. A critical consideration in LEAP data analysis is the number of ions collected from each needle. Thus, the objective of this study is to consider the effect of LEAP collected sample size on the measured cluster size, and to suggest methods to improve the fidelity of comparing average cluster sizes between larger and smaller data sets.