Understanding stacking fault tetrahedron formation in FCC stainless steel: A fusion of transmission electron microscopy, molecular dynamics, and machine learning

被引:0
|
作者
Lin, Pan-dong [1 ,3 ]
Nie, Jun-feng [2 ]
Cui, Wen-dong [2 ]
He, Lei [2 ]
Cui, Shu-gang [1 ,3 ]
Gu, Guo-chao [1 ,3 ]
Xiao, Gui-yong [1 ,3 ]
Lu, Yu-peng [1 ,3 ]
机构
[1] Shandong Univ, Key Lab Liquid Solid Struct Evolut & Proc Mat, Minist Educ, Jinan 250061, Peoples R China
[2] Tsinghua Univ, Inst Nucl & New Energy Technol, Key Lab Adv Reactor Engn & Safety, Minist Educ, Beijing 100084, Peoples R China
[3] Shandong Univ, Sch Mat Sci & Engn, Jinan 250061, Peoples R China
基金
中国国家自然科学基金;
关键词
Stacking fault tetrahedron; Twin boundary; Alloy element; Molecular dynamics; Machine learning; DEFECT CLUSTERS; STABILITY; COPPER; ALLOY; NI; DISLOCATIONS; DEFORMATION; TEMPERATURE; EVOLUTION; MIGRATION;
D O I
10.1016/j.ijplas.2024.104157
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The stacking fault tetrahedron (SFT) formation displays a pronounced size effect, progressing from vacancy equilateral triangular plate to perfect SFT, and eventually to truncated SFT, as demonstrated in numerous irradiated face-centered cubic metals. However, the presence of distinct SFT structures in F321 stainless steel has not been reported. This study explored the SFT formation mechanism in irradiated F321 stainless steel using transmission electron microscopy (TEM), molecular dynamics (MD) simulations, and machine learning. SFTs, Frank loops, and Lomer-Cottrell locks were found to be widely generated in the irradiated F321 steel. The critical size for truncated and perfect SFTs was determined using MD simulations; the results were consistent with the theoretical predictions. Additionally, the twin boundaries observed through TEM, which were attributed to the elevated tensile stress near the boundaries, facilitated the formation of perfect SFTs. Moreover, interstitial Frank loops also facilitated the formation of perfect SFTs. This study also explored the influence of variations in Ni and Cr concentrations on the critical size n1 for the transition from vacancy plates to perfect SFTs and n2 for the transition from perfect SFTs to truncated SFTs, using a combination of MD and machine learning methods. As the Ni concentration increased and the Cr concentration decreased, n1 and n2 increased; conversely, the critical sizes decreased when the Ni concentration decreased and the Cr concentration increased. These insights reveal the systematic mechanism of SFT formation under varied conditions, offering new perspectives for understanding the nano-defects in F321 stainless steel.
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页数:18
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