1. In-situ TEM investigation of void swelling in nickel under irradiation with analysis aided by computer vision.
- Author
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Chen, Wei-Ying, Mei, Zhi-Gang, Ward, Logan, Monsen, Brandon, Wen, Jianguo, Zaluzec, Nestor J., Yacout, Abdellatif M., and Li, Meimei
- Subjects
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DEEP learning , *COMPUTER vision , *IRRADIATION , *NICKEL , *LOW temperatures , *HIGH temperatures - Abstract
Understanding the stability of irradiation-induced voids in materials is important for engineering material's swelling behavior under irradiation. In-situ TEM offers a spatial and temporal resolution that is suitable for investigating the evolution of voids under irradiation. However, the in-situ videos have often been too large to be analyzed manually, leaving the valuable data underutilized. We developed a deep learning-based semantic segmentation model to consistently study the growth and shrinkage of voids in nickel under 1 MeV krypton ion irradiation at various temperatures from 525 °C to 650 °C. With a foil thickness near 100 nm and ion flux of 6.3 × 1011 ions⋅ cm−2⋅s−1, the pre-existing voids, which were created beforehand by irradiation at 600 °C to 0.5 dpa, shrank at low temperatures and grew at high temperatures under irradiation, where the transition occurred at 575 °C (∼0.5 T M). The observed stability transition provided new insight for the shrinkage mechanism of voids under irradiation. In addition, an annealing experiment on nickel, previously irradiated at 600 °C to 3 dpa, was performed sequentially at 650 °C to 720 °C to reveal the shrinkage rate of void as a function of temperature and void size. The advantage of combining computer vision and in-situ TEM to obtain comprehensive void evolution was demonstrated. [Display omitted] [ABSTRACT FROM AUTHOR]
- Published
- 2023
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