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A threshold density of helium bubbles induces a ductile-to-brittle transition at a grain boundary in nickel
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Mechanistic grain growth model for fresh and irradiated UO2 nuclear fuel
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Effect of concurrent grain growth on radiation-induced segregation in nanocrystalline Fe–Cr–Ni alloys
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Microstructural changes of proton irradiated Hastelloy-N and in situ micropillar compression testing of one single grain at different local damage levels
Here, in situ micropillar compression was used to study the deformation of proton-irradiated Hastelloy-N at different damage levels. Multiple pillars were prepared from a single domain along the cross-section of 2.5 MeV proton-irradiated Hastelloy-N. Depending on the location of micropillars, the critical resolved shear stress was obtained as a function of local damage levels. Such an approach eliminates the variation of yield stress due to the difference in the Schmid factor. Microstructural characterization showed that irradiation hardening is contributed by complicated defect structures, including (a) dislocation loops with many in corduroy-like alignments, (2) dislocations pile up, and (3) Cottrell atmosphere. Silicon atoms are found to segregate at dislocation lines and loops and form complicated Cottrell cloud patterns. The critical resolved shear stress, $t_{crss}$, and hardening exponents were both extracted as a function of displacements per atom values up to 2.3. There was a 60% increase in $t_{crss}$ at the highest damage level.
Decoupling the roles of grain boundary oxidation and stress in IASCC of neutron-irradiated 304L stainless steel
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Porosity evolution in proton irradiated microfine-grained POCO graphite
This work investigated the porosity evolution of POCO ZXF-5Q graphite that has been irradiated by 340 kW, 120 GeV protons inside NT02 target system in Fermilab's NuMI beamline. This POCO graphite has undergone direct bulk dimensional swelling at low dose irradiation and its local microstructural change is still not well-understood during this process. In this work, the (sub-) micrometre scale porosity from six locations across proton beam fluence and temperature gradients have been studied using focused ion beam-scanning electron microscopy (FIB-SEM) tomography. Here, a deep learning-based tomographic image segmentation technique has been established and implemented for porosity segmentation and quantification. It has been found that there is a decrease in the total volumetric percentage of the porosity at proton beam centre (~ 8 – 8.4 vol.%), by comparing to un-irradiated POCO (~ 12 – 13vol.%) and to beam 2σ and 5σ radii (~ 12vol.%). This decrease in porosity volume percentage was found to be caused by the reduction in pores with volumes > 0.1 μm 3 induced by material bulk dimensional swelling at proton beam centre area. The porosity reduction in relation to dimensional change and irradiation creep was discussed among with other contributing factors, and further investigations through well-controlled irradiation experiment are still needed.
Automated analysis of grain morphology in TEM images using convolutional neural network with CHAC algorithm
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Calculation of grain boundary diffusion coefficients in γU-Mo using atomistic simulations
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Fracture modes and grain growth of tungsten during extreme cyclic heating
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On the analysis of radiation-induced segregation at ion-irradiated grain boundaries
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Austenitic parent grain reconstruction in martensitic steel using deep learning
In this work we develop a deep convolutional architecture to estimate the prior austenite structure from observed martensite electron backscatter diffraction micrographs. A novel data augmentation strategy randomizes the global reference coordinate system which makes it possible to train our model from only four micrographs. The model is much faster than algorithmic approaches and generalizes well when applied to micrographs of a different material. Empirical evidence suggests the efficacy of the model depends on the scale of the microstructure and receptive field of the vision model. Furthermore, this work demonstrates that modern computer vision approaches are well suited for capturing complex spatial-orientation patterns present in orientation imaging micrographs.
Effect of grain size on Luders-type deformation and plastic deformation of V nanowires/NiTi composit
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