Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a data processing workflow to produce multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely connected units. Two SEM 250× field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.
Abstract Organic-inorganic perovskite materials are revolutionizing photovoltaics with high power conversion efficiencies, but experience significant environmental degradation and instability. In this work, the phase stability and decomposition mechanisms of lead-free all inorganic Cs 2 SnI 6 perovskite upon water and moisture exposure were systematically investigated via in situ synchrotron X-ray diffraction, environmental SEM, and micro-Raman spectroscopy. A critical relative humidity (80%) is identified below which Cs 2 SnI 6 perovskite is stable without decomposition. Under higher humidity or aqueous environment, Cs 2 SnI 6 perovskite decomposes into SnI 4 and CsI through etch pits formation and stepwave propagation, leading to rapid crystal dissolution. A partial reversibility of the Cs 2 SnI 6 perovskite upon dissolution and re-precipitation with subsequent dehydration was identified, suggesting a self-healing capability of Cs 2 SnI 6 and thus enhanced air stability. Mechanistic understanding of the Cs 2 SnI 6 degradation behavior can be a vital step towards developing new perovskites with enhanced environmental stability and materials performance.
Abstract Dense nano‐sized UO 2+ x pellets are synthesized by spark plasma sintering with controlled stoichiometries (UO 2.03 and UO 2.11 ) and grain sizes (~100 nm), and subsequently isothermally annealed to study their effects on grain growth kinetics and microstructure stability. The grain growth kinetics is determined and analyzed focusing on the interaction between grain boundary migration, pore growth, and coalescence. Grains grow much bigger in nano‐sized UO 2.11 than UO 2.03 upon thermal annealing, consistent with the fact that hyper‐stoichiometric UO 2+ x is beneficial for sintering due to enhanced U ion diffusion from excessive O ion interstitials. The activation energies of the grain growth for UO 2.03 and UO 2.11 are determined as ~1.0 and ~2.0 eV, respectively. As compared with the micrometer‐sized UO 2 in which volumetric diffusion dominates the grain coarsening with an activation energy of ~3.0 eV, the enhanced grain growth kinetics in nano‐sized UO 2+ x suggests that grain boundary diffusion controls grain growth. The higher activation energy of more hyper‐stoichiometric nano‐sized UO 2.11 may be attributed to the excessive O interstitials pinning grain boundary migration.
Thermal transport is a key performance metric for thorium dioxide in many applications where defect-generating radiation fields are present. An understanding of the effect of nanoscale lattice defects on thermal transport in this material is currently unavailable due to the lack of a single crystal material from which unit processes may be investigated. In this work, a series of high-quality thorium dioxide single crystals are exposed to 2 MeV proton irradiation at room temperature and 600 °C to create microscale regions with varying densities and types of point and extended defects. Defected regions are investigated using spatial domain thermoreflectance to quantify the change in thermal conductivity as a function of ion fluence as well as transmission electron microscopy and Raman spectroscopy to interrogate the structure of the generated defects. Together, this combination of methods provides important initial insight into defect formation, recombination, and clustering in thorium dioxide and the effect of those defects on thermal transport. These methods also provide a promising pathway for the quantification of the smallest-scale defects that cannot be captured using traditional microscopy techniques and play an outsized role in degrading thermal performance.
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