Computational Materials Science2022,Vol.2036.DOI:10.1016/j.commatsci.2021.111084

Probing the displacement damage mechanism in Si, Ge, GaAs by defects evolution analysis

Zhang, Qin Zhuang, Yu Aierken, Abuduwayiti Song, Qiaogang Yang, Xin Zhang, Shuyi Wang, Qian Dou, Youbo
Computational Materials Science2022,Vol.2036.DOI:10.1016/j.commatsci.2021.111084

Probing the displacement damage mechanism in Si, Ge, GaAs by defects evolution analysis

Zhang, Qin 1Zhuang, Yu 1Aierken, Abuduwayiti 1Song, Qiaogang 1Yang, Xin 1Zhang, Shuyi 1Wang, Qian 1Dou, Youbo1
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作者信息

  • 1. Yunnan Normal Univ
  • 折叠

Abstract

With the rapid development of space technology, the requirements for the radiation resistance of solar cells are higher and higher. A clear understanding of the radiation damage mechanism of materials is very important for radiation hardening of space solar cells. Therefore, molecular dynamics (MD) method was utilized to simulate the irradiated defects evolution in mainly used materials (Si, Ge, and GaAs) for multi-junction solar cells. By simulating the cascade collision process took placed in different materials under different interatomic potential, it is determined that Tersoff potential was more suitable for radiation damage simulation of semiconductor materials. By comparing the number of Frenkel pair defects (FPs) produced in the three materials during irradiation, the radiation resistance of each material was obtained. The MD results were verified by comparing with empirical NRT model. The displacement evolution of off-site atoms and the final clusters formed by point defects, i.e. interstitials and vacancies were further quantitatively analyzed. The atomic image of irradiated defects provides new physical insights for displacement damage mechanism and gives better understanding for explaining the degradation of irradiated multi-junction solar cells.

Key words

Displacement damage/Molecular dynamics simulation/Cascade collision/Defects evolution/Cluster analysis/SOLAR-CELLS/SILICON/EFFICIENCY/RADIATION/IRRADIATION/ENERGIES/CASCADES

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出版年

2022
Computational Materials Science

Computational Materials Science

EISCI
ISSN:0927-0256
被引量2
参考文献量39
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