Authors: Weiying Chen | Zhi-Gang Mei | Logan Ward | Vincent Cauilan | Jianguo Wen | Nestor J. Zaluzec | Brandon Monsen | Abdellatif M. Yacout | Meimei Li
Source: Microscopy and Microanalysis (article, 2023-07-22)
Field: Materials Science — Materials Chemistry

Computer Vision-aided <i>in situ</i> TEM Studies of Microstructure Evolution under Irradiation Materials used in nuclear reactors are exposed to irradiation that causes detrimental microstructural modification such as the formation of point defects, defect clusters, voids, dislocation loops, segregation, and precipitation.In situ TEM has unique ability to record videos that provide quantitative information of dynamic process that cannot be obtained with ex situ experiments.For example, the lifetime of cascade-induced vacancy clusters in nickel under irradiation at 700°C requires a time resolution less than tens of milliseconds to reveal the detailed time dependence [1].While in situ video is useful, manual extracting the quantitative information from in situ videos is dauntingly tedious and impractical, often leaving the valuable data underutilized.A solution to this challenge is computer vision [1,2,3].This study applied computer vision to investigate the shrinkage and growth of voids in materials under irradiation.Understanding the stability of irradiation-induced voids in materials is important for engineering material's swelling behavior in nuclear reactors.While first reported in 1970s [5], the shrinkage of voids, being observed under certain irradiation conditions, is still under active research [3,5] because the shrinkage mechanism remains unclear [5].We performed in situ TEM to observe the voids growing or shrinking in nickel at various temperatures from 525°C to 650°C under 1 MeV krypton ion irradiation with a flux of 6.3x10 11 ions⋅ cm -2 ⋅s -1 .At first, all specimens were irradiated at 600°C to 0.5 dpa to create pre-existing voids inside the TEM foil.After that, the temperature was changed individually to 525°C, 550°C, 575°C, 600°C, 625°C and 650°C, and then the irradiation resumed for another 1 dpa.The stability of voids at the new temperatures was observed with in situ videos on areas with a foil thickness near 100 nm.The videos were taken in under-focused (Δf = -2 µm) kinematic bright field with a frame rate of 1 fps.We found that the pre-existing voids shrank at low temperatures and grew at high temperatures under irradiation, where the transition occurred at 575°C (∼0.5 melting temperature).In addition to the above experiment, we performed an annealing experiment on a nickel specimen that was previously irradiated at 600°C to 3 dpa and then annealed sequentially at 650°C to 720°C.The annealing study showed the shrinkage rate of void as a function of temperature and their size.To extract the detailed size and density evolution of voids, we developed a deep learning-based semantic segmentation model to automatically analyze each frame of the in situ video (a total of ∼ 5000 frames for irradiation experiments and ∼3000 frames for annealing experiment).The final segmentation model is a soft-voting ensemble of 15 models, selected out of about 100 tested models, each based on varying architectures (U-Net++, U-Net and FPN), Encoders (VGG19, SE-ResNeXt50, EfficientNet-B3 and EfficientNet-B5), Loss functions (DiceBCE and Jaccard) and batch sizes.The final segmentation model can achieve a performance with an IoU score of 0.81 and an F1 score of 0.89, respectively.With computer vision, we showed the detailed void evolution over a wide temperature range based on a large video dataset.The observed stability transition will provide new insight for the shrinkage mechanism of voids under irradiation.The advantage of combining computer vision and in situ TEM for nuclear material studies will be discussed. In situ ; Irradiation ; Microstructure ; Materials science ; Optics ; Metallurgy ; Chemistry ; Physics ; Nuclear physics ; Organic chemistry Fusion materials and technologies ; Additive Manufacturing Materials and Processes ; High Temperature Alloys and Creep