Real-time in-situ three-dimensional observation of dislocations during tensile deformation

被引:0
作者
Zhao, Yifang [1 ]
Gao, Hongye [2 ]
Bo, Jingkai [1 ]
Guo, Zimeng [3 ]
Zhang, Qi [1 ]
Ma, Yiming [1 ]
Hata, Satoshi [2 ,3 ]
机构
[1] Kyushu Univ, Interdisciplinary Grad Sch Engn Sci, Fukuoka 8168580, Japan
[2] Kyushu Univ, Ultramicroscopy Res Ctr, Fukuoka 8190395, Japan
[3] Kyushu Univ, Fac Engn Sci, Fukuoka 8168580, Japan
关键词
Scanning transmission electron microscopy; (STEM); Electron tomography (ET); Three-dimensional (3D); Dislocations; In-situ observation; Machine learning; Real-time; TRANSMISSION ELECTRON-MICROSCOPY; HOLDER; RECONSTRUCTION; TOMOGRAPHY; DYNAMICS; CONTRAST; LOOPS;
D O I
10.1016/j.matchar.2025.114725
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The three-dimensional (3D) morphological evolution of dislocations during crystal plastic deformation has been challenging in electron microscopy research. Although the temporal resolution of in-situ 3D observation of dislocations has improved to a few minutes, it is still not fast enough to capture the dislocation motion in realtime. Here, we propose a new method for real-time 3D in-situ observation of dislocations. This method combines machine learning-assisted rapid scanning transmission electron microscopy imaging and stereographic 3D reconstruction. Using this approach, we achieved real-time 3D observation of dislocations induced by tensile deformation in a single-crystal copper, with a temporal resolution ranging from 0.28 to 0.70 s. The observation results show a continuous evolution of the 3D dislocation morphology with millisecond temporal resolution. This new method provides a platform for future research on the dynamic behavior of dislocations.
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页数:10
相关论文
共 54 条
[51]   A compact design of four-degree-of-freedom transmission electron microscope holder for quasi-four-dimensional characterization [J].
Zhang, YiZhi ;
Bu, YeQiang ;
Fang, XiaoYang ;
Wang, HongTao .
SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2020, 63 (07) :1272-1279
[52]   Five-second STEM dislocation tomography for 300 nm thick specimen assisted by deep-learning-based noise filtering [J].
Zhao, Yifang ;
Koike, Suguru ;
Nakama, Rikuto ;
Ihara, Shiro ;
Mitsuhara, Masatoshi ;
Murayama, Mitsuhiro ;
Hata, Satoshi ;
Saito, Hikaru .
SCIENTIFIC REPORTS, 2021, 11 (01)
[53]   ResNet-based image inpainting method for enhancing the imaging speed of single molecule localization microscopy [J].
Zhou, Zhiwei ;
Kuang, Weibing ;
Wang, Zhengxia ;
Huang, Zhen-Li .
OPTICS EXPRESS, 2022, 30 (18) :31766-31784
[54]  
Zuiderveld K., 1994, Graphics gems, P474