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Acta Metall Sin  2020, Vol. 56 Issue (2): 249-256    DOI: 10.11900/0412.1961.2019.00203
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Molecular Dynamics Simulation of DisplacementCascades in Nb
MA Xiaoqiang1,2,YANG Kunjie3,XU Yuqiong1,2(),DU Xiaochao1,2,ZHOU Jianjun1,2,XIAO Renzheng1,2
1. College of Mechanical and Power Engineering, China Three Gorges University, Yichang 443002, China
2. Hubei Key Laboratory of Hydroelectric Machinery Design & Maintenance, China Three Gorges University, Yichang 443002, China
3. College of Nuclear Equipment and Nuclear Engineering, Yantai University, Yantai 264005, China
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Abstract  

Refractory metal Nb and its alloys are considered as promising materials in fusion reactor, where they are required to withstand a high neutron irradiation, because their excellent high temperature properties such as high temperature strength, good thermal conductivity and compatibility with most liquid metal coolants. The defects are created in atomic displacement cascade from the primary state of damage and subsequent evolution gives rise to important change in their microstructures and engineering properties. However, the evolution and aggregation of induced radiation defects in atomic level cannot be observed by experiment so far. In this work, molecular dynamics (MD) method is used to explore the microstructural formation and evolution of defects from the atomic displacement cascades in bcc-Nb. In the simulation, the energy range of primary knock-on atom (PKA) is chosen 5~50 keV and the simulation temperature 300 K. It is observed that the most of defects in bcc Nb are point defects at different PKA energies. The vacancy cluster rate varies from 17% to 35% and self-interstitial cluster rate varies from 23% to 40%. As the PKA energy increasing, vacancies usually tend to form larger clusters. The self-interstitial atoms form a dumbbell structure along the direction <110>. The 1/2<111> intermittent dislocation loop and <100> vacancy dislocation loop are produced when the PKA energy greater than 30 keV. The quantitative relationship between energy of PKA (EPKA) and number of survivals Frenkel pairs (NFP) is fitted by a power function with different parameters at low-energies (5~30 keV) and the high-energies (30~50 keV).

Key words:  Nb      molecular dynamics (MD)      displacement cascade      Frenkel pair      defect cluster     
Received:  20 June 2019     
ZTFLH:  TG132  
Fund: Special Fund for Talents of China Three Gorges University(2016KJX03);Open Science Foundation of Hubei Key Laboratory of Hydroelectric Machinery Design & Maintenance(2019KJX08)
Corresponding Authors:  Yuqiong XU     E-mail:  yuqiongxu@ctgu.edu.cn

Cite this article: 

MA Xiaoqiang,YANG Kunjie,XU Yuqiong,DU Xiaochao,ZHOU Jianjun,XIAO Renzheng. Molecular Dynamics Simulation of DisplacementCascades in Nb. Acta Metall Sin, 2020, 56(2): 249-256.

URL: 

https://www.ams.org.cn/EN/10.11900/0412.1961.2019.00203     OR     https://www.ams.org.cn/EN/Y2020/V56/I2/249

EPKA / keVCell sizeNumber of atomSimulation time / ps
520a×20a×20a1600020
1020a×20a×20a1600020
2030a×30a×30a5400025
3040a×40a×40a12800025
4060a×60a×60a43200030
5080a×80a×80a102400040
Table 1  Cell size and number of atoms in the atomic displacement cascade simulation with different primary knock-on atom (PKA) energies (EPKA)
Fig.1  The number of Frenkel pairs induced by 30 keV PKA moving in [235] direction as a function of simulated time (Insets show the simulated snapshots of local structures near the cascade center, t—the time of simulation, black lines in insets show the size of the vacancy zone, PKA—primary knock-on atom)
Fig.2  Visual screenshots of defect evolution induced by 30 keV PKA moving in [235] direction during displacement cascades (The blue, yellow and red atoms represent vacancy, single interstitial atom and double interstitial atom, respectively)(a) t=0.051 ps (b) t=0.11 ps (c) t=0.38 ps (d) t=1.49 ps(e) t=5.09 ps (f) t=10.09 ps (g) t=15.09 ps (h) t=25.00 ps
Fig.3  The number of Frenkel pairs as a function of simulated time for different PKA energies (EPKA)
Fig.4  Curves of average number of surviving Frenkel pairs and cascade efficiency vsEPKA
Fig.5  Curves of vacancy cluster and interstitial cluster formation rates vsEPKA
Fig.6  The number of interstitial clusters (a) and vacancy cluster (b) formed in each cascade as a function of the corresponding EPKA
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